WO2021016892A1 - Procédé d'analyse d'informations d'évaluation de régularité, dispositif de surveillance et système de surveillance - Google Patents

Procédé d'analyse d'informations d'évaluation de régularité, dispositif de surveillance et système de surveillance Download PDF

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WO2021016892A1
WO2021016892A1 PCT/CN2019/098456 CN2019098456W WO2021016892A1 WO 2021016892 A1 WO2021016892 A1 WO 2021016892A1 CN 2019098456 W CN2019098456 W CN 2019098456W WO 2021016892 A1 WO2021016892 A1 WO 2021016892A1
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pulse
value
evaluation information
characteristic value
pulse wave
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PCT/CN2019/098456
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English (en)
Chinese (zh)
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张飞
金星亮
何先梁
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深圳迈瑞生物医疗电子股份有限公司
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Priority to CN201980098034.XA priority Critical patent/CN114040705A/zh
Priority to PCT/CN2019/098456 priority patent/WO2021016892A1/fr
Publication of WO2021016892A1 publication Critical patent/WO2021016892A1/fr

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure

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  • This application relates to the field of medical devices, in particular to an evaluation method, monitoring equipment and monitoring system for regular evaluation information.
  • ECG Electrocardiograph, electrocardiogram
  • This application provides an analysis method, monitoring equipment, and monitoring system for regularity evaluation information, which can realize the accurate monitoring of the regularity of the heart rhythm by the monitoring equipment through non-ECG technology.
  • An embodiment of the present application provides a method for analyzing regularity evaluation information.
  • the method includes: acquiring a periodic physiological signal of a measurement object through a sensor, wherein the sensor is a non-cardiac sensor; and from the periodic physiological signal The pulse wave signal related to the measurement object is extracted; according to the pulse wave signal, regularity evaluation information is obtained by analysis.
  • An embodiment of the present application also provides a method for analyzing regularity evaluation information.
  • the method includes: acquiring periodic physiological signals of a measurement object through a first sensor, wherein the first sensor is a non-cardiograph sensor;
  • the second sensor acquires signals of other physiological signs of the human body; extracts pulse wave signals related to the measurement object from the periodic physiological signals; and obtains regularity evaluation information according to the pulse wave signals and the other physiological signs.
  • An embodiment of the present application also provides a monitoring device, which includes a sensor and a processor.
  • the sensor is used to obtain periodic physiological signals of the measuring object.
  • the processor is configured to extract a pulse wave signal related to the measurement object from the periodic physiological signal, and obtain regularity evaluation information according to the analysis of the pulse wave signal; wherein the sensor is a non-cardiac sensor.
  • An embodiment of the application also provides a monitoring device, which includes a first sensor, at least one second sensor, and a processor.
  • the first sensor is used to obtain periodic physiological signals of the measurement object, wherein the first sensor is a non-cardiograph sensor; the at least one second sensor is used to obtain signals of other physiological signs of the human body.
  • the processor is configured to extract a pulse wave signal related to the measurement object from the periodic physiological signal; obtain regularity evaluation information according to the pulse wave signal and the other physiological sign signals.
  • An embodiment of the present application also provides a monitoring system, the monitoring system includes a monitoring device, the monitoring device includes a sensor and a processor; the sensor is used to obtain the periodic physiological signal of the measurement object; the processor is used to The pulse wave signal related to the measurement object is extracted from the periodic physiological signal, and regularity evaluation information is obtained by analyzing the pulse wave signal; wherein the sensor is a non-cardiograph sensor.
  • the monitoring device includes a first sensor, at least one second sensor, and a processor.
  • the first sensor is used to obtain periodic physiological signals of the measurement object, wherein the first sensor is a non-cardiograph sensor; the at least one second sensor is used to obtain other physiological signs of the human body; the processor is used Extracting the pulse wave signal related to the measurement object from the periodic physiological signal; obtaining regularity evaluation information according to the pulse wave signal and the other physiological sign signals.
  • the embodiment of the present application also provides a computer-readable storage medium, in which program instructions are stored, and the program instructions are used to execute an analysis method after being called by a computer.
  • the method includes: acquiring a periodic physiological signal of a measuring object through a sensor, wherein the sensor is a non-electrocardiographic sensor; extracting a pulse wave signal related to the measuring object from the periodic physiological signal; The pulse wave signal is analyzed to obtain the regularity evaluation information.
  • the method includes: acquiring a periodic physiological signal of the measurement object through a first sensor, wherein the first sensor is a non-cardiac sensor; acquiring other physiological signs of the human body through at least one second sensor; The pulse wave signal related to the measurement object is extracted from the periodic physiological signal; the regularity evaluation information is obtained according to the pulse wave signal and the other physiological sign signals.
  • the analysis method, monitoring equipment, and monitoring system disclosed in the present application extract pulse wave signals from periodic physiological signals obtained by sensors, and identify the fluctuation rhythm of the pulse wave based on the pulse wave signals, which is information associated with the heart beat rhythm, To obtain the regularity evaluation information, the monitoring equipment can be used to accurately obtain the regularity evaluation information through non-ECG technology.
  • Fig. 1 is a schematic diagram of a monitoring system used in a hospital according to an embodiment of the application.
  • FIG. 2 is a flowchart of a method for analyzing regularity evaluation information in an embodiment of the application.
  • FIG. 3 is a schematic diagram of displaying prompt information in an embodiment of the application.
  • FIG. 4 is a schematic diagram of displaying prompt information in another embodiment of the application.
  • FIG. 5 is a schematic diagram of displaying prompt information in still another embodiment of the application.
  • FIG. 6 is a schematic diagram of displaying prompt information in other embodiments of the application.
  • FIG. 7 is a schematic diagram of displaying prompt information in other embodiments of the application.
  • FIG. 8 is a schematic diagram of displaying prompt information in other embodiments of the application.
  • FIG. 9 is a schematic diagram of an interface displaying prompt information in an embodiment of the application.
  • FIG. 10 is a schematic diagram of an interface displaying prompt information in another embodiment of the application.
  • FIG. 11 is a flowchart of the quality evaluation process in the evaluation method shown in FIG. 2.
  • FIG. 12 is a flowchart of a method for analyzing regularity evaluation information in another embodiment of the application.
  • FIG. 13 is a further flowchart of the analysis method shown in FIG. 12.
  • FIG. 14 is another further flowchart of the analysis method shown in FIG. 12.
  • Fig. 15 is a flowchart of the filter selection process in the evaluation method shown in Fig. 12.
  • Fig. 16 is a block diagram of a monitoring device in an embodiment of the application.
  • FIG. 17 is a block diagram of a monitoring device in another embodiment of the application.
  • FIG. 18 is a system framework diagram of a multi-parameter monitor or module assembly in an embodiment of the application.
  • FIG. 1 is a schematic diagram of a monitoring system 100 used in a hospital.
  • the monitoring system 100 can store the data monitored by wearable monitors or bedside monitors as a whole, and centrally manage patient information and nursing information, both The associated storage is convenient for the preservation of historical data and associated alarms.
  • the monitoring system 100 shown in FIG. 1 the monitoring system 100 includes at least one monitoring device 200 and at least one monitoring management device 300.
  • the at least one monitoring device 200 may include one of a mobile monitoring device and a bedside monitoring device, which is used to directly monitor measurement objects such as patients.
  • the at least one monitoring management device 300 includes at least one of department-level workstation equipment and hospital-level data center/hospital-level emergency center management equipment.
  • the at least one monitoring device 200 may include a mobile monitoring device 201 and a bedside monitoring device 202.
  • the portable monitoring device 200 is a wearable monitoring device.
  • a bedside monitoring device 202 may be provided for each hospital bed, and the bedside monitoring device 202 may be a multi-parameter monitor or a plug-in monitor.
  • each bedside monitoring device 202 can also be paired and transmitted with a mobile monitoring device 201.
  • the mobile monitoring device 201 provides a simple and portable multi-parameter monitor or module component, which can be worn on the patient's body and corresponding to the patient's mobile For monitoring, after wired or wireless communication between the mobile monitoring device 201 and the bedside monitoring device 202, the patient status data generated by the mobile monitoring can be transmitted to the bedside monitoring device 202 for display.
  • the monitoring management equipment 300 may include department-level workstation equipment 301 and hospital-level data center/hospital-level emergency center management equipment 302.
  • the mobile monitoring equipment 201 transmits patient status data generated by mobile monitoring to the department-level workstation equipment 301 is for viewing by doctors or nurses, or transmitted to hospital-level data center/hospital-level emergency center management equipment 302 through the bedside monitoring device 202 for storage and/or display.
  • the mobile monitoring device 201 can also directly transmit the patient status data generated by mobile monitoring to the department-level workstation device 301 for storage and display through the wireless network node N1 set in the hospital, or transfer the patient status data generated by the mobile monitoring device 301 through the wireless network node N1 set in the hospital.
  • the patient status data generated by the mobile monitoring is transmitted to the hospital-level data center/hospital-level emergency center management equipment 302 for storage.
  • the data corresponding to the patient status parameters displayed on the bedside monitoring device 202 can be derived from a sensor accessory directly connected to the bedside monitoring device 202, or from the mobile monitoring device 201, or from the department-level workstation device 301, Hospital-level data center/hospital-level emergency center management equipment 302.
  • each mobile monitoring device 201 can also store the patient status data collected by itself, and the bedside monitoring device 202 can also store the patient status data collected by the sensor accessory connected to the bedside monitor, and store the data from the mobile monitoring device 201.
  • Department-level workstation equipment 301 and hospital-level data center/hospital-level emergency center management equipment 302 can store patient status data sent by any mobile monitoring device 201.
  • FIG. 2 is a flowchart of a method for analyzing regularity evaluation information in an embodiment of this application.
  • the analysis method of the present application can be applied to, for example, the monitoring system 100 or the monitoring device 200 described above.
  • the monitoring device 200 is equipped with a sensor.
  • the method for analyzing regularity evaluation information includes the following steps:
  • the periodic physiological signal of the measurement object is acquired by a sensor, wherein the sensor is a non-cardiograph sensor (S21).
  • a pulse wave signal related to the measurement object is extracted from the periodic physiological signal (S22).
  • the step S22 includes: filtering, amplifying, and A/D conversion (digital-to-analog conversion) processing on the periodic physiological signal to extract the pulse wave signal.
  • the pulse wave signal contains at least one single pulse wave waveform.
  • the regularity evaluation information is obtained by analysis (S23).
  • the current ECG technology collects real-time changes in the potential difference of the human body surface through an electrocardiogram sensor, and records it in the form of lead waveforms with an electrocardiogram.
  • the electrical activity of the heart reflected on the electrocardiogram can assist doctors in diagnosing lesions in the corresponding position of the heart.
  • the “non-cardiac sensor” used in this application can also be connected to the human body to collect and transmit physiological signals used to assist in the diagnosis of the heart.
  • the biggest difference of "electric sensors” is that "non-cardioelectric sensors” do not collect the potential difference of the human body surface in real time.
  • this type of sensor is referred to as a "non-cardiac sensor".
  • the non-cardiac sensor can radiate light of different wavelengths into the tissue area of the corresponding part of the subject, detect the light signal sent through the tissue area, and extract the light signal from the light signal. The photoplethysmography signal generated by the light absorption of the tissue area is used to obtain the pulse wave signal.
  • the non-ECG sensor can control the cuff to be inflated to a certain pressure by setting the cuff on a specified part of the body, so that the cuff compresses the artery, and then gradually deflates. In the deflation process or During the inflation process, the pressure in the cuff is sampled, the pulse wave under this pressure is detected, and the pulse wave signal is obtained.
  • the pulse wave signal is extracted from the periodic physiological signal obtained by the sensor, and the fluctuation rhythm of the pulse wave is identified based on the pulse wave signal, which is related to the heart beat rhythm, to obtain regularity evaluation information
  • the ability to use "non-ECG sensors" instead of ECG technology can accurately obtain regularity evaluation information.
  • the pulse wave is screened for regularity according to the pulse wave signal extracted above, and the corresponding pulse and pulse related information and/or regularity evaluation information within a period of time are obtained.
  • the wave-related information and/or regularity evaluation information includes at least the corresponding pulse wave-related information and/or regularity evaluation information when an irregular pulse wave occurs.
  • the step S23 "analyzing and obtaining regularity evaluation information according to the pulse wave signal" includes: "obtaining a characteristic value representing the fluctuation rhythm of the pulse wave according to the pulse wave signal; analyzing the characteristic value To regular evaluation information".
  • the step of "obtaining characteristic values that characterize the fluctuation rhythm of the pulse wave according to the pulse wave signal” includes: adopting at least one analysis technique of time domain technology, frequency domain technology, and nonlinear dynamics technology Perform feature extraction on the pulse wave signal to obtain corresponding at least one feature value.
  • one analysis technique or multiple analysis techniques may be used in combination to perform feature extraction on the pulse wave signal to obtain the corresponding at least one/class feature value.
  • the step of "obtaining a characteristic value representing the fluctuation rhythm of the pulse wave according to the pulse wave signal” includes: using a time domain technique to perform feature extraction on the pulse wave signal to obtain at least one time domain characteristic value.
  • only the time domain technique may be used to perform feature extraction on the pulse wave signal to obtain at least one time domain feature value.
  • the at least one time domain characteristic value includes a waveform shape characteristic value
  • the waveform shape characteristic value includes at least one of pulse interval, pulse amplitude, pulse area, pulse slope, pulse envelope, pulse width, etc.
  • the pulse interval refers to the time interval between two single pulses, which can be the time interval between the peak and the peak, the valley and the valley, or the time interval between any corresponding points on two single pulses. The interval can be adjacent or non-adjacent.
  • the single pulse in this article can be a pulse wave or a single pulse collected using other forms. Pulse amplitude refers to the difference between the peak and trough of the wave.
  • the pulse slope refers to the slope of either the rising section or the falling section of the pulse wave.
  • Pulse area refers to the time integral of the pulse wave between two adjacent troughs or between the start to the end of a single pulse.
  • Pulse envelope refers to the envelope formed by the connection between wave crests and crests (or troughs and troughs).
  • Pulse width refers to the length of time from the start to the end of a single pulse.
  • the step of "obtaining characteristic values that characterize the fluctuation rhythm of the pulse wave according to the pulse wave signal” may further include: using frequency domain technology to convert the pulse wave signal into a frequency domain signal, and then comparing the frequency domain signal Perform feature extraction to obtain at least one frequency domain feature value.
  • only frequency domain technology may be used to perform feature extraction on the pulse wave signal to obtain at least one frequency domain feature value.
  • the frequency domain feature value includes one of a spectrum feature and a power spectrum feature.
  • the spectrum feature may include: one of the characteristic information of spectrum peak, spectrum interval, spectrum amplitude, spectrum area, spectrum slope, and spectrum envelope, etc.
  • the spectrum peak includes the spectrum peak amplitude, which refers to the height of the spectrum peak;
  • the spectral peak includes the position of the spectral peak, which refers to the frequency position corresponding to the spectral peak; the spectral peak may also include the number of spectral peaks, which refers to the number of spectral peaks in the frequency band in the frequency spectrum.
  • the spectrum interval refers to the interval between any two frequencies
  • the spectrum amplitude refers to the amplitude corresponding to each frequency in the spectrum
  • the spectrum area refers to the integral of the spectrum in the frequency band
  • the spectrum slope refers to any rise in the spectrum
  • the spectrum envelope refers to the envelope formed by the connection between the spectrum peaks.
  • the power spectrum feature may include: power spectrum peak, power spectrum interval, power spectrum amplitude, power spectrum area, power spectrum slope, power spectrum envelope, etc., and power spectrum peak includes power spectrum peak amplitude, which refers to Is the height of the power spectrum peak; the power spectrum peak includes the power spectrum peak position, which refers to the frequency position corresponding to the power spectrum peak; the power spectrum peak can also include the number of power spectrum peaks, which refers to the power spectrum in the frequency band in the power spectrum The number of peaks.
  • the power spectrum interval refers to the interval between any two frequencies
  • the power spectrum amplitude refers to the amplitude corresponding to each frequency in the power spectrum
  • the power spectrum area refers to the integral of the power spectrum in the frequency band
  • the power spectrum slope refers to It is the slope of any rising or falling section in the power spectrum
  • the power spectrum envelope refers to the envelope formed by connecting power spectrum peaks.
  • the step of "obtaining characteristic values that characterize the fluctuation rhythm of the pulse wave according to the pulse wave signal” may further include: using nonlinear dynamics technology to perform feature extraction on the pulse wave signal to obtain at least one non- Characteristic values of linear dynamics.
  • only the nonlinear dynamics technology may be used to perform feature extraction on the pulse wave signal to obtain at least one nonlinear dynamics feature value.
  • the calculation result of the nonlinear dynamic characteristic value is compared with the corresponding preset threshold, so as to identify the irregular pulse wave signal, extract the irregular pulse wave signal in a period of time, based on the irregular pulse wave signal in a period of time Signal, output pulse wave related information and/or regularity evaluation information corresponding to the irregular pulse wave signal.
  • analysis methods such as time domain analysis, frequency domain analysis, and machine learning can be used to determine pulse wave waveform related information, such as pulse interval.
  • the user can further determine the regularity evaluation information based on the pulse wave waveform related information displayed by the output.
  • the nonlinear dynamics characteristic value includes entropy or complexity.
  • the entropy includes, but is not limited to, information entropy, spectral entropy, approximate entropy, sample entropy, fuzzy entropy and other entropy features.
  • the method further includes: converting the extracted characteristic value into an intermediate characteristic value; the step " Analyzing the characteristic value to obtain regularity evaluation information” may include: analyzing the intermediate characteristic value to obtain regularity evaluation information.
  • the intermediate characteristic value includes a pulse rate value
  • the converting the extracted characteristic value into an intermediate characteristic value includes: converting the extracted characteristic value into a pulse rate value.
  • the analyzing based on the intermediate characteristic value to obtain regularity evaluation information includes: performing analysis based on the pulse rate value to obtain regularity evaluation information.
  • the analysis based on the pulse rate value to obtain the regularity evaluation information includes: obtaining the difference between pulse rates, when it is satisfied that the difference between several consecutive adjacent pulse rates exceeds the threshold, or Among N adjacent pulse rate differences, at least n exceed the threshold, or there is a pulse rate that exceeds or is less than the average pulse rate (threshold), or the standard deviation of the pulse rate divided by the average pulse rate exceeds the threshold When it is judged to be irregular.
  • the intermediate characteristic value includes a pulse sound characteristic value
  • converting the extracted characteristic value into an intermediate characteristic value includes: converting the extracted characteristic value into a pulse sound characteristic value.
  • the analyzing based on the intermediate characteristic value to obtain the regularity evaluation information includes: analyzing based on the pulse sound characteristic value to obtain the regularity evaluation information.
  • the analysis based on the pulse sound characteristic value to obtain the regularity evaluation information includes: obtaining the pulse sound interval, and when the difference between several consecutive adjacent intervals exceeds a threshold, or in N phases When the difference between adjacent intervals meets at least n differences exceeding the threshold, or there is an interval exceeding or smaller than the interval average value (threshold), or the interval standard deviation divided by the interval average exceeding the threshold, it is judged that it is suspected to be irregular.
  • said converting the extracted characteristic value into a pulse sound characteristic value includes: determining the arrival time of the peak or trough of the pulse according to the extracted characteristic value, and marking the peak or trough at the arrival time of the peak or trough; The peak or trough mark generates pulse sound characteristic values.
  • the analysis based on the characteristic value of the pulse sound to obtain the regularity evaluation information may further include: marking the peaks or troughs of the pulse wave signal within a period of time or several cycles to obtain at least two To obtain at least two pulse sound feature values generated by at least two wave crest marks or at least two trough marks; statistical analysis and/or machine learning methods are used to compare the at least two pulse sound feature values Perform analysis to obtain the regularity evaluation information.
  • At least two pulse sound feature values can be generated based on at least two wave crest marks, or at least two pulse sound feature values can be generated based on at least two wave trough marks.
  • the pulse sound characteristic value may also be a certain value selected between the peaks and troughs according to a preset rule, as long as it can represent the pulse interval, which is not limited here.
  • the analyzing the at least two pulse sound characteristic values through statistical analysis and/or machine learning to obtain the regularity evaluation information may include: performing statistical analysis on the at least two pulse sound Analyzing the characteristic values of pulse sounds to obtain statistical analysis data, and obtaining the regularity evaluation information according to the statistical analysis data; and/or using machine learning methods to use the at least two pulse sound characteristic values as inputs, and The output of the regularity evaluation information is obtained.
  • the use of at least one analysis technology of time domain technology, frequency domain technology, and nonlinear dynamics technology to perform feature extraction on the pulse wave signal to obtain at least one feature value may also specifically include: At least one analysis technology of time domain technology, frequency domain technology and nonlinear dynamics technology is used to extract features of the pulse wave signal to obtain at least two types of feature values, according to the two types of feature values and the weight of each type of feature value It is worth the final characteristic value.
  • the same pulse wave signal can be analyzed by multiple analysis techniques Analyze, integrate the multiple types of feature values obtained by multiple technologies and the weight value of each type of feature value to obtain the final feature value of the waveform, which improves the accuracy of feature value acquisition.
  • the weight value of the time domain feature value and the weight value of the frequency domain feature value may be preset.
  • the multiple different feature values include multiple types of feature values (such as time domain feature values, frequency domain feature values, etc.) analyzed through different analysis techniques and/or multiple types of different features analyzed through the same analysis technology. Characteristic values (such as pulse interval, slope, etc.).
  • the step of "analyzing the characteristic value to obtain regularity evaluation information” includes: comparing the at least one characteristic value with the corresponding at least one characteristic value threshold, and obtaining the regularity evaluation according to the comparison result Information; and/or through a machine learning method, the at least one feature value is used as an input to obtain the output of the regularity evaluation information. Understandably, “rules” and “irregularities” can be identified in a variety of ways, rather than just textual representations, as long as they can be used to indicate that the current regularity evaluation information is suspected to be regular or irregular, regular or irregular. can.
  • the regularity evaluation information is the conclusion information indicating "suspected rules", “suspected irregularities”, “rules” or “irregularities”. Due to the homology of pulse and heart rhythm, the regularity evaluation information may include at least one of pulse regularity evaluation information and heart rhythm regularity evaluation information.
  • the regularity evaluation information in the present application refers to: the type of regularity evaluation information includes the evaluation results used to indicate regular or irregular pulse beats and/or heart rhythms.
  • the regularity evaluation information used to indicate the rule or irregularity can be obtained directly according to the characteristic value of the pulse wave signal that represents the fluctuation rhythm of the pulse wave.
  • the characteristic value may include at least one of pulse interval, pulse amplitude, pulse area, pulse slope, pulse envelope, pulse width, and may also include spectral characteristic values, power spectral characteristic values, etc., It can also include entropy, complexity, etc.
  • the at least one characteristic value may be a characteristic value of pulse interval
  • the preset threshold may be a preset pulse interval range
  • the step of "obtaining characteristic values that characterize the fluctuation rhythm of the pulse wave according to the pulse wave signal” may further include: performing feature extraction on the pulse wave signal of a period of time or several cycles to obtain at least two A feature value; the at least two feature values are analyzed by a statistical analysis method and/or a machine learning method to obtain the regularity evaluation information.
  • performing feature extraction on the pulse wave signal of a period of time or several cycles to obtain at least two feature values may also be: using at least one analysis technique of time domain technology, frequency domain technology and nonlinear dynamics technology to Feature extraction is performed on pulse wave signals of a certain period of time or several cycles to obtain at least two feature values.
  • the time period may be a randomly selected time period or a preset time period, and the several cycles may be multiple randomly selected cycles or a preset number of cycles.
  • the “analyzing the at least two characteristic values through a statistical analysis method and/or a machine learning method to obtain the regularity evaluation information” may include: analyzing the at least two characteristic values through a statistical analysis method. The characteristic value is analyzed to obtain statistical analysis data, and the regularity evaluation information is obtained according to the statistical analysis data; and/or the at least two characteristic values are used as input through a machine learning method to obtain the rule The output of sexual evaluation information.
  • the statistical analysis data may be the maximum value, the sum, the ratio, the integral, the difference, the mean, the standard deviation, the maximum interval, the minimum interval, the pulse variability, the number of mutations, and the maximum based on the aforementioned characteristic values.
  • said obtaining the regularity evaluation information according to the statistical analysis data may include adding the maximum value, sum, ratio, integral, difference, Statistical analysis data such as mean, standard deviation, maximum interval, minimum interval, pulse variability, number of variations, maximum pulse rate value, minimum pulse rate value and the preset maximum value, sum, ratio, integral, difference, etc.
  • the mean, standard deviation, maximum interval, minimum interval, pulse variability, number of variations, maximum pulse rate, minimum pulse rate and other preset statistical data are compared, and the results are used to express regular or irregular statistics.
  • the regular evaluation information is compared, and the results are used to express regular or irregular statistics.
  • the statistical analysis data includes at least one of frequency domain statistical analysis data, nonlinear dynamic characteristic statistics, pulse frequency related quantity statistics, time domain characteristic value statistical analysis data, and variation related quantities.
  • the frequency domain statistical analysis data includes at least one of the spectrum feature statistics and the power spectrum feature statistics.
  • the spectrum feature statistics include one of the single spectrum feature statistics and the multiple spectrum feature statistics.
  • the single spectrum feature statistics include: within a single spectrum, different spectrum peak amplitudes, spectrum peak positions, and spectrum The maximum value, mean value, ratio, difference, sum, integral, standard deviation, distribution statistics, etc. of these features such as interval, spectrum amplitude, spectrum area, and spectrum slope, as well as statistical analysis values of spectrum feature statistics, such as spectrum interval difference The average value, the standard deviation of the spectral interval difference, etc.
  • Multi-spectral feature statistics include: the peak amplitude, number of peaks, peak position, spacing, amplitude, area, and slope of these features, such as the maximum value, mean value, Ratio, difference, summation, integral, standard deviation, distribution statistics, etc., as well as statistical analysis values of spectral feature statistics, such as the standard deviation of the maximum spectral peak position difference between spectra, and the maximum spectral peak position difference between spectra exceed a predetermined value The number of values, etc.
  • the power spectrum feature statistics include one of the single power spectrum feature statistics and the multi-power spectrum feature statistics.
  • the single power spectrum feature statistics include: within a single power spectrum, different power spectrum peak amplitudes, Power spectrum peak position, power spectrum interval, power spectrum amplitude, power spectrum area, power spectrum slope and other characteristics of the maximum value, mean value, ratio, difference, sum, integral, standard deviation, distribution statistics, etc., and power spectrum feature statistics The statistical analysis value of the quantity, such as the average value and standard deviation of the power spectrum interval difference.
  • Multi-power spectrum feature statistics include: power spectrum peak amplitude, number of power spectrum peaks, power spectrum peak position, power spectrum interval, power spectrum amplitude, power spectrum area, power spectrum slope between corresponding power spectrums at different time periods within a period of time Such as the maximum value, mean value, ratio, difference, sum, integral, standard deviation, distribution statistics, etc. of these features, as well as the statistical analysis value of the power spectrum feature statistics, such as the standard of the maximum power spectrum peak position difference between the power spectra Difference, the number of the maximum power spectrum peak position difference between power spectra exceeding a predetermined value, etc.
  • the nonlinear dynamic characteristic statistics include statistical analysis data of nonlinear dynamic characteristic values.
  • Time-domain characteristic value statistical analysis data refers to the analysis results of time-domain characteristic values based on statistical analysis methods for a period of time. It can include at least the difference in pulse interval, the difference in pulse amplitude, the difference in pulse slope, and the pulse area.
  • the average value of pulse interval refers to the average value of pulse interval in a period of time.
  • the difference in pulse interval refers to the difference between pulse intervals.
  • the average value of the pulse interval difference refers to the average value of the pulse interval difference in a period of time.
  • the integral of the pulse interval difference refers to the integral value obtained by integrating the pulse interval difference within a time period.
  • the sum of pulse intervals refers to the sum of pulse intervals.
  • the ratio of pulse interval refers to the ratio of different pulse intervals.
  • the standard deviation of the pulse interval refers to the standard deviation of the pulse interval in a period of time.
  • the difference in pulse width refers to the difference in pulse width.
  • the average value of pulse width refers to the average value of pulse width in a period of time.
  • the difference in pulse width refers to the difference between pulse widths.
  • the average value of the pulse width difference refers to the average value of the pulse width difference over a period of time.
  • the integral of the pulse width difference refers to the integral value obtained by integrating the pulse width difference within a time period.
  • the standard deviation of the pulse width refers to the standard deviation of the pulse width in a period of time.
  • the sum of pulse width refers to the sum of pulse widths.
  • the pulse width ratio refers to the ratio between different pulse widths.
  • the difference in pulse amplitude refers to the difference between the pulse amplitudes.
  • the average value of pulse amplitude refers to the average value of pulse amplitude in a period of time.
  • the standard deviation of the pulse amplitude refers to the standard deviation of the pulse amplitude in a period of time.
  • the sum of pulse amplitudes refers to the sum of pulse amplitudes in a period of time.
  • the ratio of pulse amplitude refers to the ratio between different pulse amplitudes.
  • the average value of the pulse amplitude difference refers to the average value of the pulse amplitude difference in a period of time.
  • the integral of the pulse amplitude difference refers to the integral value obtained by integrating the pulse amplitude difference within a time period.
  • the difference in pulse slope refers to the difference between the pulse slopes.
  • the average value of pulse slope refers to the average value of pulse slope in a period of time.
  • the standard deviation of the pulse slope refers to the standard deviation of the pulse slope in a period of time.
  • the sum of pulse slopes refers to the sum of pulse slopes in a period of time.
  • the ratio of pulse slope refers to the ratio between different pulse slopes.
  • the average value of the pulse slope difference refers to the average value of the pulse slope difference in a period of time.
  • the integral of the pulse slope difference refers to the integral value obtained by integrating the pulse slope difference within a time period.
  • the difference of pulse area refers to the difference between pulse areas
  • the mean value of pulse area refers to the mean value of the pulse area in a period of time
  • the standard deviation of pulse area refers to the standard deviation of the pulse area in a period of time. .
  • the sum of pulse areas refers to the sum of pulse areas in a period of time.
  • the ratio of pulse area refers to the ratio between different pulse areas.
  • the average value of the pulse area difference refers to the average value of the pulse area difference in a period of time.
  • the integral of the pulse area difference refers to the integral value obtained by integrating the pulse area difference within a time period.
  • Variation related quantity refers to the time domain characteristic value, pulse wave frequency correlation quantity, frequency domain characteristic, nonlinear dynamic characteristic, frequency domain characteristic statistics, nonlinear dynamic characteristic statistics, and pulse frequency correlation statistics within a period of time.
  • a measure of the change of at least one of the time-domain feature value statistics, for example, the variation related quantity includes at least one of the degree of variation and the number of variations.
  • the signal characteristic information here includes at least the time domain characteristic value, the pulse wave frequency related quantity, One of frequency domain feature values, nonlinear dynamic features, frequency domain feature statistics, nonlinear dynamic feature statistics, pulse frequency related statistics, time domain feature value statistics, etc.
  • the degree of variability may be one of the time domain feature value, the pulse wave frequency correlation value, the frequency domain feature, the nonlinear dynamics feature, and the time domain feature value statistical analysis data over a period of time, a period of time
  • the degree of difference in this article can be obtained by the combination of difference, quotient, difference and quotient.
  • the statistical analysis methods mentioned in this article include one of the mathematical statistical methods such as mean calculation, difference calculation, and standard deviation calculation.
  • the aforementioned degree of variability may refer to the degree of variability of a pulse wave with respect to the pulse wave in any period of time.
  • the aforementioned degree of variability may refer to the current pulse wave relative to the pulse wave within a period of time.
  • the degree of variability such as the variability of pulse interval. The following takes the variability of the pulse interval as an example. If the current pulse wave is the seventh pulse wave, there are six pulse intervals. Calculate at least one of the six pulse intervals and any number of pulses in the six pulse intervals. The difference between the mean of the interval, and the ratio of the difference to the mean is taken as the variability of the pulse interval.
  • the aforementioned degree of variability refers to the degree of variation of the current pulse wave relative to the previous pulse wave. For example, if the current pulse wave is the seventh pulse wave, there are six pulse intervals, and the sixth pulse wave is calculated. The difference between a pulse interval and the average of the first five pulse intervals, and the ratio of the difference to the average of the first five pulse intervals is used as the pulse interval variability.
  • the number of mutations mentioned above may refer to the number of pulse wave variations that occur within a period of time, for example, time domain feature values, pulse wave frequency correlation quantities, frequency domain features, nonlinear dynamics features, and frequency domain feature statistics within a period of time.
  • Non-linear dynamic characteristic statistics, pulse frequency related statistics, and time domain characteristic value statistics exceed the predetermined value.
  • the number of variations may be the number of times the pulse interval difference exceeds a predetermined value, or the pulse interval, the average pulse interval, the average pulse interval difference, the standard deviation of the pulse interval, and the pulse amplitude in a period of time.
  • Difference mean value of pulse amplitude, standard deviation of pulse amplitude, difference of pulse slope, mean value of pulse slope, standard deviation of pulse slope, difference of pulse area, mean value of pulse area, standard deviation of pulse area, pulse rate The number of times that one of the pulse wave signal characteristic information such as the value, the maximum pulse rate value, and the minimum pulse rate value exceeds a predetermined value.
  • rhythm quantization parameter value may include at least the feature value and the statistics of the feature value.
  • the analysis data and the preset threshold may include at least one of frequency domain characteristics, nonlinear dynamic characteristics, pulse frequency related quantities, and time domain characteristic values;
  • the statistical analysis data of the characteristic values may include frequency domain statistical analysis data, nonlinear dynamic characteristic statistics , At least one of the pulse frequency related quantity statistics, the time domain feature value statistics, and the variation related quantity;
  • the preset threshold includes the aforementioned feature value and/or the threshold corresponding to the statistical analysis data of the feature value.
  • the regularity evaluation information can be given based on the comparison of the identified rhythm quantification parameter value with the corresponding preset threshold. For example, it can be based on the comparison of the aforementioned degree of variability with the corresponding threshold, and the aforementioned number of mutations with the corresponding threshold. Compare or compare the aforementioned variation and the number of variation with the corresponding threshold respectively, and give the evaluation information of the pulse rhythm regularity according to the comparison result, so as to determine whether the pulse wave is regular. In some embodiments, it can be compared with a threshold value based on one of the identified characteristic values of the aforementioned rhythm quantization parameter values, so as to provide regularity evaluation information; or, it can also be based on two of the identified aforementioned rhythm quantization parameter values.
  • More than one (including two) feature values are respectively compared with the corresponding thresholds, and a multi-condition combination judgment is performed, thereby giving the evaluation information of the pulse rhythm regularity.
  • at least one characteristic value of the identified rhythm quantization parameter values is continuously compared with a preset threshold value.
  • the multiple comparison results meet the pulse wave rule or the pulse wave irregularity standard , Give the evaluation result about pulse wave rule or pulse wave irregularity, so as to obtain regularity evaluation information.
  • at least one characteristic value of the recognized rhythm quantization parameter value is compared with a preset threshold multiple times in a period of time.
  • the multiple comparison results represent the number of times of the pulse wave rule
  • the evaluation result of the pulse wave rule is output
  • the proportion of the number of times characterizing the pulse wave irregularity in the multiple comparison results meets the pulse wave irregular standard
  • the statistical analysis data is the pulse variability and/or the number of variability based on the aforementioned characteristic values.
  • the obtaining the regularity evaluation information according to the statistical analysis data includes:
  • the degree of variation and/or the number of variations is compared with the preset statistical data of the degree of variation and/or the number of variations to obtain the regularity evaluation information. For example, for the pulse wave signal collected within a period of time, the variability and/or the number of variability of the pulse wave signal can be counted for multiple times in succession, and the variability and/or the number of variability obtained from each statistics can be compared with the preset The variability and/or the preset statistical data of the number of variations are compared, and a preset threshold for the number of consecutive statistics is N times.
  • the variability and/or the pulse wave signal of the continuous statistics If the comparison result is greater than or equal to N times, the variability and/or the pulse wave signal of the continuous statistics If the number of mutations exceeds the preset degree of mutation and/or the preset statistical data of the number of mutations, it is determined that the regularity evaluation information of the pulse wave signal is irregular pulse. For another example, in other embodiments, the variability and/or the number of variability of the pulse wave signal in any period of time are counted multiple times, and the variability and/or the number of variability obtained from each statistic are respectively compared with the predicted number.
  • the preset statistical data of the set variance and/or the number of variances are compared, and the number of times that the variance and/or number of variances of the recorded pulse wave signal exceeds the preset statistical data of the preset variance and/or the number of variances is N1 times, the result of the N1 times of statistics can be judged that the regularity evaluation information of the pulse wave signal is irregular pulse.
  • a percentage X is preset. When the proportion of N1 in the total number of statistics is greater than or equal to X , The final judgment result is irregular pulse, otherwise, the final judgment result is regular pulse.
  • the statistical analysis data is obtained, and then the rules for representing the rule or the irregularity are obtained.
  • Sexual evaluation information may be that after statistical analysis is performed on the characteristic values representing the fluctuation rhythm of the pulse wave obtained according to the pulse wave signal, the statistical analysis data is obtained, and then the rules for representing the rule or the irregularity are obtained.
  • the time-domain feature value statistics include waveform morphological feature statistics.
  • the waveform morphological feature statistics refer to the results of analyzing waveform morphological feature values for a period of time based on statistical analysis methods, and may include at least the difference in pulse interval, Difference in pulse amplitude, difference in pulse slope, difference in pulse area, difference in pulse envelope, difference in pulse width, average pulse interval, average pulse amplitude, average pulse slope, average pulse area , The mean value of pulse envelope, the mean value of pulse width, the standard deviation of pulse interval, the standard deviation of pulse amplitude, the standard deviation of pulse wave slope, the standard deviation of pulse area, the standard deviation of pulse envelope, the standard deviation of pulse width, The sum of pulse interval, the sum of pulse amplitude, the sum of pulse slope, the sum of pulse area, the sum of pulse envelope, the sum of pulse width, the ratio of pulse interval, the ratio of pulse amplitude, the ratio of pulse slope Ratio, ratio of pulse area, ratio of pulse envelope, ratio of pulse width, average of pulse interval difference, average of pulse
  • the machine learning method may be to establish a machine learning model, such as a neural network model, through model training, so that the at least two feature values can be used as input to the machine learning model and automatically derived to represent rules or irregularities The output of the regularity evaluation information.
  • a machine learning model such as a neural network model
  • using the at least two feature values as input to obtain the output of the regularity evaluation information through a machine learning method includes:
  • machine learning models can be established through model training, such as neural network models.
  • the correlation between pulse wave related information and regularity evaluation information can be input into the training machine learning model to obtain the machine learning model after the training is completed.
  • performing machine learning on the aforementioned pulse wave signal to obtain pulse wave related information includes: the pulse wave obtained based on the pulse wave signal after time domain analysis, frequency domain analysis, or nonlinear dynamics analysis Relevant information is input into the machine learning model after training, and regular evaluation information can be automatically obtained.
  • the feature extraction is performed on the pulse wave signal of a certain period of time or several cycles to obtain at least two feature values that are different feature values obtained by feature extraction on different periods of the pulse wave signal,
  • they can be the same type of feature value or different types of feature value.
  • feature extraction is performed on multiple different time periods within a certain time period through time domain technology to obtain multiple characteristic values of the type of multiple pulse intervals.
  • it is also possible to perform feature extraction on multiple different time periods within a certain time period for example, three time periods using time domain technology, frequency domain technology, and nonlinear dynamics technology to obtain corresponding time domain features. Value, frequency domain characteristic value and nonlinear dynamic characteristic value.
  • the at least two characteristic values are characteristic values obtained by characteristic extraction of pulse wave signals of different time periods in a period of time or several cycles
  • the method of extracting each characteristic value may also be At least one analysis technology of time domain technology, frequency domain technology, and nonlinear dynamics technology performs feature extraction on the same waveform segment of the pulse wave signal to obtain at least two types of feature values, according to the two types of feature values and each type of feature
  • the weight of the value gives the final characteristic value of the waveform segment.
  • the method further includes: evaluating the quality of the pulse wave signal to obtain a quality factor; and According to the quality factor, it is determined whether to adopt or discard the pulse wave signal currently obtained. Understandably, the quality factor may be a feature obtained during the analysis and processing of the periodic physiological signal or the pulse wave signal according to step S22 or S23.
  • the method of obtaining the quality factor may be the same as the method of “obtaining the characteristic value of the fluctuation rhythm of the pulse wave according to the pulse wave signal” described above, except that the characteristic obtained is the quality factor. value.
  • the quality factor may be at least one time domain value of pulse interval, pulse amplitude, pulse area, pulse slope, pulse envelope, and pulse width obtained through time domain technology, or may be obtained through frequency domain technology.
  • the output includes at least one frequency domain value such as a frequency spectrum feature, a power spectrum feature value, etc., and may also be at least one nonlinear dynamics value such as entropy value and complexity obtained by nonlinear dynamics technology.
  • the quality factor may be the maximum value, ratio, sum, integral, difference, mean, standard deviation, maximum interval, minimum interval, pulse variability, number of variations, maximum pulse rate, minimum pulse rate At least one of the values.
  • the step of "analyzing the characteristic value to obtain regularity evaluation information" may include: when it is determined according to the quality factor that the currently obtained pulse wave signal can be used, according to the obtained characteristic Value is further analyzed to obtain regularity evaluation information.
  • the characteristic value is credible, and further analysis is performed directly based on the acquired characteristic value to obtain a regularity evaluation information.
  • the step of "analyzing the characteristic value to obtain regularity evaluation information" may further include: when it is determined according to the quality factor that the currently obtained pulse wave signal can be used, according to the quality factor and the acquisition The eigenvalues obtained are further analyzed to obtain regularity evaluation information.
  • the further analysis according to the quality factor and the acquired characteristic value to obtain regularity evaluation information includes: determining the weight value of the characteristic value and the weight value of the quality factor according to the quality factor; The weight value of the characteristic value and the weight value of the quality factor perform weighted calculation on the characteristic value and the quality factor to obtain a weighted characteristic value; and analyze according to the weighted characteristic value to obtain the regularity evaluation information.
  • the quality of the pulse wave signal can be analyzed according to the characteristic value to obtain the quality factor indicating the quality of the pulse wave signal, because the quality factor itself is another derived from the characteristic value.
  • the quality factor and the characteristic value obtained according to the pulse wave signal can be weighted to obtain a weighted adjustment value, and then analyzed according to the weighted characteristic value to obtain the regularity evaluation information, which can effectively improve the regularity evaluation The accuracy of the information.
  • the determining the weight value of the characteristic value and the weight value of the quality factor according to the quality factor may specifically include: comparing the obtained quality factor with a corresponding quality factor threshold, and determining the quality factor of the quality factor according to the comparison result Weight value j1; and determine the weight value of the feature value (1-j1).
  • the quality factor may include at least one quality factor, and may be different types of quality factors obtained by different analysis techniques or different types of quality factors obtained by the same analysis technique.
  • the quality factor obtained by time domain technology As an example, through time domain analysis, the following values are obtained: pulse wave amplitude standard deviation, peak-peak interval average, peak-peak interval maximum, then the pulse wave amplitude standard deviation, The peak-to-peak interval average value, the peak-to-peak interval maximum and minimum values are compared with the standard deviation threshold, the interval average threshold, and the interval maximum threshold, and the weighted value j1 of the quality factor is determined according to the comparison result. Among them, when the signal quality is better, the weight value of the corresponding quality factor is smaller; conversely, when the signal quality is worse, the weight value of the corresponding quality factor is larger.
  • the threshold may be a single threshold, or may include two thresholds, for example, a threshold range formed by the first threshold and the second threshold.
  • the weight value j1 of the quality factor ranges from 0 to 1
  • the weight value 1-j1 of the feature value also ranges from 0 to 1.
  • the better the quality signal is set the smaller the weighting value of the corresponding quality factor is: when the quality signal is better, the quality factor should be weakened, and the characteristic value obtained from the pulse wave signal at this time is also more accurate.
  • the eigenvalues should be strengthened, so in this case, the smaller the weight value of the quality factor, the greater the weight value of the eigenvalue; and vice versa.
  • the weighting value of the quality factor can be a smaller value, such as 0.2, and the eigenvalue should be strengthened, so the weight of the eigenvalue
  • the frequency spectrum of a signal can be obtained for a period of time, and the number of spectrum peaks whose spectrum peak amplitude>a is counted.
  • the further analysis based on the quality factor and the acquired characteristic value to obtain regularity evaluation information may further include:
  • the characteristic value and the quality factor coefficient are calculated to obtain the corrected characteristic value, and then the regularity evaluation information is obtained according to the corrected characteristic value.
  • the calculation is multiplication. Understandably, the calculation includes at least one of multiplication, division, subtraction, and addition. For example, when the calculation includes division, the characteristic value is divided by the quality factor coefficient. When the signal quality is higher, the quality factor coefficient is larger, and the maximum is equal to 1. When the signal quality is worse, the quality factor coefficient is smaller.
  • the method for obtaining the quality factor is the same as before, and will not be repeated here.
  • mapping the quality factor to the quality factor coefficient of the acquired feature value includes: comparing the quality factor with a corresponding quality factor threshold, and mapping the quality factor to The quality factor coefficient of the acquired characteristic value.
  • the threshold may be a single threshold, or may include two thresholds, for example, a threshold range formed by the first threshold and the second threshold.
  • the signal quality when it is satisfied that the amplitude standard deviation is ⁇ a, and the peak-to-peak interval average value/peak-to-peak interval maximum value ⁇ b, the signal quality is judged to be good, and the corresponding quality factor coefficient can be 1.
  • the signal quality is judged to be medium, and the quality factor coefficient is 0.8; when the standard deviation of amplitude> c, and the maximum value (minimum value) of the peak-to-peak interval/average value of the peak-to-peak interval>d, the signal quality is judged to be low, and the quality factor coefficient is 0.5.
  • the frequency spectrum of a signal can be obtained for a period of time, and the number of spectrum peaks whose spectrum peak amplitude>a is counted.
  • the quality factor coefficient multiplied by the eigenvalue is smaller, so that the interference signal corresponding to the eigenvalue is greatly reduced, thereby effectively avoiding interference.
  • the method further includes the step of: when the signal quality is judged to be low, obtaining a noise template signal, and performing denoising processing on the pulse wave signal based on the noise template signal to obtain the denoised pulse Wave signal.
  • the step of "obtaining the characteristic value representing the fluctuation rhythm of the pulse wave according to the pulse wave signal” may include: obtaining the characteristic value representing the fluctuation rhythm of the pulse wave according to the pulse wave signal after noise removal.
  • performing denoising processing on the pulse wave signal based on the noise template signal to obtain the denoised pulse wave signal may include: removing components corresponding to the noise template signal from the pulse wave signal to obtain the denoising Pulse wave signal after noise.
  • the analysis method further includes: outputting prompt information according to the type of the regularity evaluation information. Understandably, the way of outputting the prompt information may include text, voice, sound, light, etc. for output.
  • the prompt information includes at least one of pulse wave related information, executable function related information, and the regularity evaluation information;
  • the type of the regularity evaluation information includes an evaluation result used to indicate a rule or an irregularity
  • the pulse wave related information includes a pulse wave waveform and/or a rhythm quantization parameter value
  • the executable function is the regularity The function that can be executed next when the evaluation information meets the preset conditions.
  • the pulse wave waveform may at least include the pulse wave waveform when the regularity evaluation information is an evaluation result indicating irregularity, and may also be included when the regularity evaluation information indicates a regularity.
  • the pulse wave waveform at the time of the evaluation result may also include the pulse wave waveform shape obtained in real time in the process of acquiring the periodic physiological signal of the measuring object by the sensor.
  • the pulse wave waveform may include a waveform shape over a period of time, or a continuously generated pulse wave shape. For example, when the pulse wave waveform is a continuously generated pulse wave shape, it may be at least in the pulse wave shape.
  • a certain segment of wave form contains irregular pulse wave waveforms over a period of time.
  • the method further includes: evaluating the quality of the pulse wave signal to obtain a quality factor; and According to the quality factor, it is determined whether to adopt or discard the pulse wave signal currently obtained. Understandably, the quality factor may be a feature obtained during the analysis and processing of the periodic physiological signal or the pulse wave signal according to step S22 or S23.
  • the pulse wave The waveform may include at least the corresponding pulse wave waveform when the quality of the pulse wave signal is good, and may also include the corresponding pulse wave waveform when the quality of the pulse wave signal is bad. In other words, regardless of whether the quality factor finally determines whether to discard the currently obtained pulse wave signal, the corresponding pulse wave waveform can be output or not displayed.
  • the corresponding pulse wave waveform may include fragments of irregular pulse wave waveforms, or may include fragments of regular pulse wave waveforms.
  • the corresponding pulse wave waveform may include an irregular pulse wave waveform over a period of time.
  • Rhythm quantization parameter values may include at least one of frequency domain characteristics, nonlinear dynamic characteristics, pulse frequency related quantities, time domain feature values, statistics of time domain feature values, and variation related quantities.
  • Frequency domain features include at least one of spectrum features, power spectrum features, and so on.
  • Non-linear dynamic features include at least one of entropy and complexity, and entropy includes but is not limited to entropy features such as information entropy, spectral entropy, approximate entropy, sample entropy, and fuzzy entropy.
  • the pulse rate-related quantity includes pulse rate and a statistical analysis quantity of the pulse rate. For example, the pulse rate statistical analysis quantity includes a maximum pulse rate value and/or a minimum pulse rate value.
  • N-1 pulse rates in a period of time, in a signal with N pulse waves, N-1 pulse rates can be calculated according to the interval between adjacent pulse waves, in which the maximum and minimum pulse rates are The value is defined as the maximum pulse rate and the minimum pulse rate.
  • the time domain characteristic value includes at least one of pulse interval, pulse amplitude, pulse area, pulse slope, pulse envelope, pulse width, etc.
  • the rhythm quantization parameter value includes at least one of the following:
  • Statistical analysis including at least one of the maximum value, ratio, sum, integral, difference, mean, standard deviation, maximum interval, minimum interval, displayed variability, and the number of variations based on statistical analysis of at least one characteristic value data;
  • At least one threshold including the threshold of the degree of variability and the threshold of the number of mutations.
  • At least one of the threshold of the degree of variation and the threshold of the number of variations is used for reference to confirm the regularity evaluation information.
  • the monitoring device 200 further includes a display screen
  • the regularity evaluation information can be displayed in the first display area of the display screen
  • the pulse wave related information can be displayed in the second display area of the display screen.
  • Information about executable functions can be displayed in the third display area of the display screen. That is, the prompt information may specifically include at least one of the following:
  • Pulse wave related information displayed in the second display area of the display screen displayed in the second display area of the display screen
  • the type of the regularity evaluation information may include an evaluation result used to indicate a rule or an irregularity.
  • the regularity evaluation information is displayed in at least one of the following forms: text, pattern, and light.
  • the output of the prompt information according to the type of the regularity evaluation information may include: displaying the corresponding prompt information according to the type of the regularity evaluation information for indicating a rule or an irregularity.
  • the prompt information may only include the regular evaluation information P1 of "suspected irregular pulse".
  • the first display area A1 may be the entire display area of the display screen or a certain area in the current interface displayed on the display screen.
  • the current interface may be a certain functional interface or system interface of the monitoring device 200.
  • the prompt information can be displayed on the current interface in a pop-up window.
  • the prompt information may be displayed on the prompt interface after switching from the current interface to a prompt interface.
  • the regularity evaluation information P1 may also include “irregular pulse”, “irregular”, “abnormal pulse”, “abnormal”, “irregular pulse interval”, “irregular pulse rate”, and “suspected irregular pulse” “, “Suspected Atrial Fibrillation”, “Suspected Irregular Heart Rhythm” and other words that indicate irregular pulse evaluation and/or indicate the results of irregular heart rhythm evaluation, as long as it can prompt the measurement subject to present pulse/heart rhythm irregularities or There may be irregular pulse/heart rhythm, and there is no restriction on the form of expression.
  • the prompt information may be "regular pulse”, “rule”, "normal” and other text information that can prompt the measurement subject that the current pulse and/or heart rhythm is normal.
  • the prompt information includes regular evaluation information
  • the user can directly see the results of the device's intelligent analysis, which is convenient and intuitive, and facilitates the user to perform follow-up examinations, such as booking an ECG examination, ultrasound examination, etc.
  • the prompt information may only include pulse wave related information P2 displayed in the second display area A2.
  • the pulse wave related information P2 displayed in the second display area A2 includes the pulse interval: 31, 43, 33, 48, 29; the average pulse interval is 36.8; the pulse interval difference is: 12, 10, 15, 19; The average pulse interval is 14.
  • the second display area A2 may be the entire display area of the display screen or a certain area in the current interface displayed on the display screen.
  • the prompt information can be displayed on the current interface through a pop-up window.
  • the prompt information may be displayed on the prompt interface after switching from the current interface to a prompt interface.
  • the prompt information includes pulse wave related information P2
  • it can provide the user with a waveform reference for the user to confirm the regular evaluation information.
  • the prompt information may also include, for example, the regularity evaluation displayed in the first display area A1 of FIG.
  • the first display area A1 where the regularity evaluation information P1 is located is adjacent to the second display area A2 where the pulse wave related information P2 is located. Understandably, the first display area A1 and the second display area A2 may not be adjacent to each other, and may be set arbitrarily.
  • the adjacent settings of the first display area A1 and the second display area A2 can facilitate the user to intuitively view the regularity evaluation information and combine the pulse wave related information to determine the occurrence regularity of the measurement object based on the pulse wave related information Specific reasons for evaluating information.
  • the prompt information may also include, for example, regularity evaluation information P1 displayed in the first display area A1 of FIG.
  • regularity evaluation information P1 displayed in the first display area A1 of FIG.
  • the pulse wave related information P2 displayed in the second display area A2 of FIG. 4
  • the executable function related information P3 displayed in the third display area A3 of FIG. 6. Displaying the relevant information P3 of the executable function can play a role of prompting and guiding the relevant operation to be performed in the next step, so that the user can learn and execute the operation to be performed in the next step.
  • the relevant information P3 of the executable function includes: “print “(For example, print pulse wave waveform), “Schedule ECG”, “Schedule ultrasound” at least one, and may also include other functions, such as user-defined common functions.
  • the first display area A1, the second display area A2, and the third display area A3 are arranged adjacent to each other in order.
  • the first display area A1, the third display area A3, and the second display area A2 may be arranged adjacently in sequence, as long as it is ensured that multiple areas are arranged adjacently. , The order can be adjusted arbitrarily.
  • the first display area A1, the second display area A2, and the third display area A3 may also be arranged non-adjacently, and may be multiple non-adjacent areas.
  • the at least two display areas are adjacently located on the display screen. Understandably, the at least two display areas are arranged adjacently on the display screen to facilitate the user to view the regularity evaluation information, pulse wave related information, and executable function related information. In other embodiments of the present application, the display areas may not be arranged adjacently.
  • FIG. 7 is a schematic diagram of displaying prompt information in other embodiments.
  • a plurality of vital sign data item areas are displayed on the display screen of the monitoring device 200 to display different vital sign measurement parameters respectively.
  • the area of each vital sign data item shows whether the measurement parameter of non-invasive blood pressure NIBP is 120/80 (mmHg), the measurement parameter of blood oxygen SPO2 is 98 (%), the measurement parameter of pulse is 64 (bpm), and the measurement parameter of body temperature is The measurement parameter is 102.5 (F), and the measurement parameter of respiration is 20 BPM.
  • the first display area P1 and the second display area P2 are not adjacent.
  • the display screen further includes a touch area T for retracting or expanding the second display area P2 to hide or display the pulse wave related information A2 accordingly.
  • a touch area T for retracting or expanding the second display area P2 to hide or display the pulse wave related information A2 accordingly.
  • FIG. 8 Please refer to FIG. 8 together.
  • the first display area P1 is set next to the pulse measurement parameters, which is convenient for the user to confirm the regularity evaluation information when observing the pulse measurement parameters.
  • the setting of the touch area T allows the user to choose to view or hide according to actual needs Pulse wave related information.
  • the display interface is neat and beautiful; when the user's regular evaluation information A1 prompts "irregular" or the user needs to view the pulse wave related information A2 for other reasons, you can click to touch Area T, expand the second display area P2 for viewing.
  • the prompt information including at least one of the regularity evaluation information, pulse wave related information, and executable function related information prompt information can also be displayed on the current interface in a pop-up window, or switch from the current interface After reaching a prompt interface, it is displayed in the prompt interface.
  • the regularity evaluation information is displayed in at least one of the following forms: text, pattern, and light.
  • the prompt information when the prompt information is displayed in a pop-up window and includes at least two of the regularity evaluation information, pulse wave related information, and executable function related information, the regularity evaluation information, pulse wave At least two of the wave-related information and the relevant information prompt information of the executable function may be displayed in the same window, or may be displayed in different windows. That is, at least two of the first display area A1, the second display area A2, and the third display area A3 may be located in the same window, or may be located in different windows.
  • the regularity evaluation information may include both text and patterns: "Suspected irregular pulse Obviously, an indicator light can also be provided on the display, and the regularity evaluation information can also be indicated by the light emitted by the indicator light. For example, when a red light is emitted, it indicates “irregularity”, and when a green light is emitted When the time, it indicates “rules”, where the indicator light can be a hardware indicator light or a virtual light displayed on the display screen.
  • the second display area A2 further includes a first sub display area A21, and the pulse wave related information includes pulse wave waveforms displayed in the first sub display area for a period of time.
  • the pulse wave waveform is a corresponding pulse wave waveform obtained by extracting a pulse wave signal related to the measurement object from the periodic physiological signal in step S22. By displaying the pulse wave waveform, the pulsation of the pulse can be visually displayed.
  • the second display area A2 includes a second sub display area A22
  • the pulse wave related information also includes rhythm quantization parameter values
  • the rhythm quantization parameter values include displayed in the second sub display area
  • the statistical analysis data includes the maximum value, ratio, sum, integral, difference, mean, standard deviation, maximum interval, minimum interval, display variability, number of variations, and maximum pulse rate of the characteristic value At least one of the minimum pulse rate values; the characteristic value includes: at least one of pulse interval, pulse amplitude, pulse area, pulse slope, pulse envelope, and pulse width.
  • the rhythm quantization parameter value may also include the characteristic values representing the fluctuation rhythm of the pulse wave obtained directly from the pulse wave signal, and/or statistical analysis data obtained after statistical analysis of these characteristic values, And preset thresholds, for example, the variability threshold, the one-time input threshold and so on. .
  • the first sub-display area A21 and the second sub-display area A22 are adjacently arranged.
  • the specific positional relationship between the first sub-display area A21 and the second sub-display area A22 is not limited.
  • the second sub-display area A22 is on the upper side, or as shown in FIG. 5-6
  • the first sub-display area A21 may be at the top.
  • the information related to the executable function includes guide information of the executable function and/or function icon of the executable function.
  • the guide information of the executable function is used to inform the user of the executable function that can be performed by the monitoring device 200 after the monitoring device 200 outputs the prompt information.
  • the guide information can be text or pattern to guide the user to understand the monitoring The executable functions of the device 200 and how to trigger the executable functions.
  • the relevant information of the executable function may also directly include the function icon B1 of the executable function, so that the function icon B1 of each executable function is displayed in a more direct manner, and the function icon B1 of each executable function is displayed for user operation to trigger The corresponding executable function.
  • the evaluation method may further include: in response to a trigger operation on the function icon B1, controlling to execute the function corresponding to the function icon B1.
  • the executable functions include at least one of printing pulse wave waveforms, scheduling ECG examinations, and scheduling ultrasound examinations, and may also include other functions, such as user-defined common functions.
  • the function icon B1 may include at least one function icon including a pulse wave waveform printing function icon, a scheduled ECG examination function icon, and an scheduled ultrasound examination function icon.
  • the type of regularity evaluation information includes an evaluation result used to indicate regular or irregular pulse and/or heart rhythm.
  • the method further includes: When the evaluation information is irregular, output alarm information.
  • the presentation form of the alarm information includes at least one of text, pattern, light, sound, and vibration.
  • the text and pattern may be output through the display screen of the monitoring device 200, the light may be output through the display screen or indicator light of the monitoring device 200, the sound may be output through the speaker of the monitoring device 200, and the vibration may be output through The vibrator of the monitoring device 200 is generated.
  • outputting alarm information includes: determining an alarm gear according to the acquired characteristic value, and controlling the output of the alarm information of the corresponding alarm gear, wherein the The alarm gear includes at least two gears.
  • the determining the alarm gear according to the acquired characteristic value may include: comparing the acquired characteristic value with multiple reference values, determining the characteristic value interval in which the characteristic value is located, and determining the characteristic value interval according to the determined characteristic value interval and the characteristic Correspondence between the value interval and the alarm gear to determine the corresponding alarm gear.
  • the corresponding alarm gear is determined to be the first alarm gear, and the control is issued Green light or audible alarm information with a lower decibel; when the slope is greater than or equal to the second slope and less than the third slope, determine the corresponding alarm gear as the second alarm gear, and control to emit orange light or a medium-decibel sound Alarm information; when the slope is greater than or equal to the third slope, the corresponding alarm gear is determined to be the third alarm gear, and the red light or the highest decibel sound alarm information is controlled to be emitted.
  • the first slope is smaller than the second slope, and the second slope is smaller than the third slope.
  • the first alarm gear is smaller than the second alarm gear
  • the second alarm gear is smaller than the third alarm gear
  • the number of the alarm gears can be any suitable value such as 2, 3, 4, etc.
  • the corresponding relationship between the characteristic value interval and the alarm gear can be a pre-stored corresponding relationship table, a corresponding relationship curve, and the like.
  • the method further includes the step of changing or confirming the regularity evaluation information that is used to indicate rules or irregularities in response to a result change operation or confirmation operation input by the user.
  • FIG. 9 is a schematic diagram of an interface displaying prompt information in an embodiment.
  • the prompt information can be displayed on an interface in a pop-up window.
  • the prompt information includes a detailed information area Z1 and a judgment area Z2.
  • the detailed information area Z1 displays detailed information for the user to make judgments. Whether it is a rule or not, the judgment zone Z2 includes options of "rule” and "irregular", and the options of "rule” and "irregular” are used for the user to select to obtain the regularity evaluation information.
  • the detailed information includes: pulse wave waveform ("pleth" area in the figure), pulse identifier, pulse interval measurement value, maximum interval, minimum interval, display variability and other information.
  • the content of the detailed information does not overlap with the content of the prompt information at all, and the detailed information gives more information than the prompt information. Understandably, in other embodiments of the present application, the content contained in the detailed information may also be partially or completely consistent with the content contained in the prompt information.
  • the regularity evaluation information is determined to be a rule, or in response to the selection operation of the "irregular” option, the regularity evaluation information is confirmed to be irregular.
  • the interface may be an interface such as a monitoring result interface, a system interface, etc.
  • FIG. 10 is a schematic diagram of an interface displaying prompt information in another embodiment.
  • the prompt information includes "rule” and "irregular” selection boxes displayed on an interface of the monitoring device 200.
  • the options of "rule” and “irregular” are used for the user to choose to confirm or change the regular evaluation information.
  • the current regularity evaluation information is prompted through the currently selected "rule" selection box S1 and “irregular” selection box S2, and the user can respond to the user's response to the "rule" selection box S1 or "irregular "Select box S2 to change the regular evaluation information.
  • the entire interface may be a prompt information interface.
  • the prompt information also includes an interface to provide an operation interface for the user to call up detailed information to assist the user in judgment.
  • the detailed information includes: pulse wave waveform ("pleth" area in the figure), pulse identifier , Pulse interval measurement value, maximum pulse interval, minimum pulse interval, pulse interval variability and other information, or further including variability threshold, number of mutations, threshold of number of mutations, maximum pulse rate, minimum pulse rate and other information.
  • the steps S22-S23 can all be performed in the monitoring device 200, that is, “extract the pulse wave signal related to the measurement object from the periodic physiological signal", “according to all The processing processes such as “describe the pulse wave signal and analyze the regularity evaluation information” can be executed by the monitoring device 200.
  • the method before outputting the prompt information according to the regularity evaluation information, the method further includes: determining the prompt information to be displayed according to the regularity evaluation information.
  • the regularity evaluation information is a rule
  • the regularity evaluation information in the prompt information to be displayed is a text or pattern such as "rules”
  • the regularity evaluation information is irregular
  • the prompt information to be displayed is determined
  • the regularity evaluation information in is “irregular” and other characters or patterns.
  • the method further includes the step of sending prompt information to monitoring management equipment 300 such as department-level workstation equipment and/or hospital-level data center/hospital-level emergency center management equipment, through the department-level workstation equipment and /Or the hospital-level data center/hospital-level emergency center management equipment outputs the prompt information.
  • monitoring management equipment 300 such as department-level workstation equipment and/or hospital-level data center/hospital-level emergency center management equipment, through the department-level workstation equipment and /Or the hospital-level data center/hospital-level emergency center management equipment outputs the prompt information.
  • the above steps may also be: sending the prompt information to the bedside monitoring device 202, department-level workstation equipment, and/or hospital-level data center/hospital-level emergency center
  • the monitoring management equipment 300 such as management equipment outputs the prompt information through the bedside monitoring equipment 202, department-level workstation equipment and/or hospital-level data center/hospital-level emergency center management equipment.
  • the prompt information can also be sent to the bedside monitoring device 202 for display output.
  • the monitoring equipment 200 and the monitoring management equipment 300 such as the department-level workstation equipment and/or the hospital-level data center/hospital-level emergency center management equipment can output prompt information, or only the monitoring equipment 200 and the monitoring management equipment 300 A kind of output prompt information.
  • the steps S22-S23 may all be executed in the monitoring management device 300, that is, "extract the pulse wave signal related to the measurement object from the periodic physiological signal", " According to the pulse wave signal, the regularity evaluation information is obtained by analysis, etc., which can also be executed in department-level workstation equipment and/or hospital-level data center/hospital-level emergency center management equipment.
  • the method further includes: sending the periodic physiological signal to department-level workstation equipment and/or hospital-level data center/hospital-level emergency center management equipment, through department-level workstation equipment and/or hospital-level data center/hospital-level emergency management equipment
  • the central management equipment performs processing operations such as "extracting the pulse wave signal related to the measurement object from the periodic physiological signal", "analyzing the pulse wave signal to obtain the regularity evaluation information", etc. to obtain the regularity evaluation information .
  • the output of prompt information according to the regularity evaluation information further includes: receiving regularity evaluation information from department-level workstation equipment and/or hospital-level data center/hospital-level emergency center management equipment, and according to the received rules sexual evaluation information output prompt information.
  • the monitoring device 200 when it is a mobile monitoring device 201, it may be sending the periodic physiological signals to the bedside monitoring device 202, department-level workstation equipment and/or hospital-level data center/hospital-level emergency center management equipment Etc., through the bedside monitoring equipment 202, department-level workstation equipment, and/or hospital-level data center/hospital-level emergency center management equipment, etc., to obtain regular evaluation information; and from the bedside monitoring equipment 202, department-level workstation equipment And/or hospital-level data center/hospital-level emergency center management equipment receives regular evaluation information, and outputs prompt information based on the received regular evaluation information.
  • the prompt information may also be determined by department-level workstation equipment and/or hospital-level data center/hospital-level emergency center management equipment, and then sent to the monitoring device 200 for display output.
  • the method in this application can be executed in one device of the monitoring device 200, and can also be executed in multiple different devices in the monitoring system 100.
  • the senor includes at least one of a photoelectric sensor, a pressure sensor, an electromagnetic sensor, a sound sensor, and an acceleration sensor.
  • the photoelectric sensor may include a blood oxygen sensor
  • the pressure sensor may include a blood pressure sensor and other sensors that detect pressure changes caused by pulse pulsation.
  • a photoelectric sensor may include a blood oxygen sensor
  • the pressure sensor may include a blood pressure sensor and other sensors that detect pressure changes caused by pulse pulsation.
  • FIG. 11 is a flowchart of the quality evaluation process in the evaluation method shown in FIG. 2.
  • the quality evaluation process includes the following steps:
  • the quality of the pulse wave signal is analyzed to obtain a quality evaluation value (S111).
  • the quality evaluation value may be the aforementioned quality factor.
  • the quality evaluation value is compared with a preset threshold (S112). Wherein, when it is determined that the quality evaluation value is less than the preset threshold, step S113 is executed, and when it is determined that the quality evaluation value is greater than or equal to the preset threshold, step S114 is executed.
  • the prompt information is directly output (S113).
  • the subsequent analysis step of the regularity evaluation information (S114) is performed.
  • the "subsequent analysis step of regularity evaluation information” may include the aforementioned “obtaining characteristic values that characterize the fluctuation rhythm of the pulse wave according to the pulse wave signal” and “analyzing the characteristic values to obtain regularity evaluation information" Within the steps.
  • the performing quality analysis on the pulse wave signal to obtain the quality evaluation value may include: using at least one of the time domain technology, frequency domain technology, and nonlinear dynamics technology to analyze the pulse wave signal Performing feature extraction to obtain at least one feature value; and obtaining a quality evaluation value based on the at least one feature value.
  • the use of at least one analysis technology of time domain technology, frequency domain technology, and nonlinear dynamics technology to perform feature extraction on the pulse wave signal to obtain at least one feature value may include: using time domain technology, frequency domain technology
  • One of the analysis techniques in the technology and the nonlinear dynamics technology performs feature extraction on the pulse wave signal to obtain at least one feature value.
  • the use of at least one analysis technique of time domain technology, frequency domain technology, and nonlinear dynamics technology to perform feature extraction on the pulse wave signal to obtain at least one feature value may also include: using time domain technology or frequency domain technology And at least one analysis technique in the nonlinear dynamics technology performs feature extraction on the pulse wave signal to obtain at least two types of feature values, and obtain a final feature value based on the two types of feature values and the weight of each type of feature value.
  • the “output prompt information directly without performing the subsequent analysis step of regularity evaluation information” in the step 113 refers to outputting the prompt information based on the rule evaluation information.
  • the prompt information includes pulse wave related information, that is, pulse wave related information is directly output, where the pulse wave related information includes pulse wave waveform and rhythm quantization parameter values.
  • the prompt information only includes the pulse wave waveform in the pulse wave related information. Further, after displaying the prompt information that only includes the pulse wave waveform, the method further includes: receiving an input instruction and executing the step of "obtaining a characteristic value representing the fluctuation rhythm of the pulse wave according to the pulse wave signal", and according to the The characteristic value outputs the rhythm quantization parameter value.
  • Rhythm quantization parameter values are as described above, for example, include pulse interval, pulse amplitude, pulse area, pulse slope, pulse envelope, pulse width, etc., which will not be repeated here.
  • doctors and other users see the pulse wave waveform, if they want to further see the relevant rhythm quantification parameter values, they can also input instructions to trigger the monitoring device to perform the step "Acquire the characteristics of the pulse wave fluctuation rhythm according to the pulse wave signal. Value", and obtain parameters including characteristic values such as pulse interval, pulse amplitude, pulse area, pulse slope, pulse envelope, pulse width, etc., and can obtain further information to assist doctors in obtaining regularity evaluation analysis through manual judgment.
  • the step S114 "performing the subsequent step of analyzing regularity evaluation information" may further include: determining the weight value of the characteristic value and the weight value of the quality quality evaluation value according to the quality evaluation value; The weight value of the characteristic value and the weight value of the quality evaluation value perform weighted calculation on the characteristic value and the quality evaluation value to obtain a weighted characteristic value; and analyze according to the weighted characteristic value to obtain the regularity evaluation information.
  • the step S114 "performing the subsequent step of analyzing the regularity evaluation information" may further include: mapping the quality evaluation value to the quality factor coefficient of the acquired characteristic value; The value and the quality factor coefficient are calculated to obtain the corrected characteristic value; the analysis is performed according to the corrected characteristic value to obtain the regularity evaluation information.
  • FIG. 12 is a flowchart of a method for evaluating regularity evaluation information in another embodiment of this application.
  • the evaluation method can be applied to the aforementioned monitoring system 100 or monitoring device 200, where the monitoring system 100 or the monitoring device 200 includes a first sensor and at least one second sensor, and the first sensor is a non-cardiac sensor.
  • the method includes:
  • the periodic physiological signal of the measurement object is acquired by the first sensor, where the first sensor is a non-cardiograph sensor (S121).
  • a pulse wave signal related to the measurement object is extracted from the periodic physiological signal (S123).
  • the regularity evaluation information is obtained by combining the pulse wave signal and other physiological sign signals respectively obtained by multiple sensors.
  • FIG. 13 is a further flowchart of the evaluation method of regularity evaluation information shown in FIG. 12.
  • the method includes:
  • the periodic physiological signal of the measuring object is acquired by the first sensor, where the first sensor is a non-cardiograph sensor (S131).
  • a pulse wave signal related to the measurement object is extracted from the periodic physiological signal (S133).
  • the pulse wave signal is filtered out of the influence of other physiological signs to obtain a filtered pulse wave signal (S134).
  • a characteristic value representing the fluctuation rhythm of the pulse wave is obtained (S135).
  • the characteristic value is analyzed to obtain regularity evaluation information (S136).
  • step S124 in the flowchart shown in FIG. 12 may specifically include steps S134 to S136 in the flowchart shown in FIG. 13.
  • the "obtain regularity evaluation information based on the pulse wave signal and the other physiological sign signals” specifically includes: “filter the influence of other physiological sign signals in the pulse wave signal to obtain the filtered information The steps of "pulse wave signal”, “obtaining characteristic values representing the fluctuation rhythm of the pulse wave according to the filtered pulse wave signal”, and “analyzing the characteristic values to obtain regularity evaluation information”.
  • the filtering out the influence of other physiological signs signals from the pulse wave signal to obtain the filtered pulse wave signal includes: obtaining the rhythm quantization parameter value according to the pulse wave signal and according to the other physiological signs.
  • the physical sign signal obtains other physiological sign parameter values; the filtering scheme is determined according to the rhythm quantization parameter value and the other physiological sign parameter values; the filtering scheme is obtained by filtering out the influence of other physiological sign signals in the pulse wave signal according to the filtering scheme The filtered pulse wave signal.
  • the filtering scheme includes selected filters and filtering parameters
  • the determining the filtering scheme according to the rhythm quantization parameter value and the other physiological sign signals includes: according to the rhythm quantization parameter value and the other physiological sign parameters The ratio or difference of the values determines the corresponding target filter and target filter parameter.
  • the target filter and the target filter parameter can also be determined according to other relationships between the rhythm quantization parameter value and the other physiological sign parameter value, such as a product.
  • the filtering out the influence of other physiological signs from the pulse wave signal according to the filtering scheme to obtain the filtered pulse wave signal includes: applying the target filter parameter to the pulse wave signal After filtering, the filtered pulse wave signal is obtained.
  • the filter is a hardware filter in the monitoring device 200.
  • the monitoring device 200 includes multiple filters, and each filter corresponds to multiple filter parameters.
  • the determining the corresponding target filter and target filtering parameter according to the ratio or difference between the rhythm quantification parameter value and the other physiological sign parameter value further includes: according to a preset ratio or difference Correspondence with the filtering scheme, determine the filtering scheme corresponding to the ratio or difference between the rhythm quantification parameter value and the other physiological sign parameter value; determine that the filter and filtering parameter in the filtering scheme are the target filter and Target filtering parameters.
  • the corresponding relationship between the ratio or difference and the filtering scheme may be a pre-stored corresponding relationship table.
  • the second sensor includes a respiration sensor
  • the other physiological sign signal includes a respiration signal
  • the other physiological sign parameter value includes a respiration rate
  • the rhythm quantization parameter value includes a pulse rate value
  • the specific content of the "acquiring the characteristic value of the fluctuation rhythm of the pulse wave according to the filtered pulse wave signal” It can be the same as the embodiment shown in FIG. 2 of "obtaining characteristic values that characterize the rhythm of the pulse wave according to the pulse wave signal", except that this application is based on the filtered pulse wave signal.
  • FIG. 2 Related description.
  • acquiring the characteristic value representing the fluctuation rhythm of the pulse wave according to the filtered pulse wave signal includes: using at least one analysis technology of time domain technology, frequency domain technology and nonlinear dynamics technology to analyze the The filtered pulse wave signal is subjected to feature extraction to obtain at least one corresponding feature value.
  • the obtaining of the pulse wave signal from the filtered pulse wave signal a characteristic value representing the fluctuation rhythm of the pulse wave includes: using time domain technology to perform feature extraction on the filtered pulse wave signal to obtain at least one time domain characteristic value.
  • the at least one time domain characteristic value includes at least one of pulse interval, pulse amplitude, pulse area, pulse slope, pulse envelope, and pulse width.
  • Said obtaining the characteristic value representing the fluctuation rhythm of the pulse wave according to the filtered pulse wave signal includes: using frequency domain technology to convert the filtered pulse wave signal into a frequency domain signal, and then performing feature extraction on the frequency domain signal. Obtain at least one frequency domain feature value.
  • the acquiring the characteristic value representing the fluctuation rhythm of the pulse wave according to the filtered pulse wave signal includes: using nonlinear dynamics technology to perform characteristic extraction on the pulse wave signal to obtain at least one nonlinear dynamic characteristic value.
  • the nonlinear dynamics characteristic value includes entropy or complexity.
  • said acquiring the characteristic value representing the fluctuation rhythm of the pulse wave according to the filtered pulse wave signal further includes: performing characteristic extraction on the filtered pulse wave signal for a period of time or several cycles to obtain at least two The characteristic value; the analyzing the characteristic value to obtain the regularity evaluation information includes: analyzing the at least two characteristic values through a statistical analysis method and/or a machine learning method to obtain the regularity evaluation information.
  • the analyzing the at least two characteristic values by a statistical analysis method and/or a machine learning method to obtain the regularity evaluation information includes: analyzing the at least two characteristic values by a statistical analysis method , Obtain statistical analysis data, and obtain the regularity evaluation information according to the statistical analysis data; and/or obtain the regularity evaluation information by using the at least two characteristic values as input through a machine learning method One output.
  • the use of at least one analysis technology of time domain technology, frequency domain technology and nonlinear dynamics technology to perform feature extraction on the filtered pulse wave signal to obtain the corresponding at least one feature value may further include: At least one analysis technology of time domain technology, frequency domain technology, and nonlinear dynamics technology is used to perform feature extraction on the filtered pulse wave signal to obtain at least two types of feature values, according to the two types of feature values and each type of feature The weight of the value gives the final at least one characteristic value.
  • the at least two different characteristic values include at least two characteristic values analyzed by different analysis techniques and/or at least two different characteristic values analyzed by the same analysis technique.
  • the same analysis method as in the embodiment shown in FIG. 2 is that after the pulse wave signal obtains the characteristic value of the fluctuation rhythm of the pulse wave according to the filtered pulse wave signal, the method further includes: The extracted feature values are converted into intermediate feature values.
  • the analyzing the characteristic value to obtain the regularity evaluation information includes: performing analysis based on the intermediate characteristic value to obtain the regularity evaluation information.
  • the intermediate characteristic value includes a pulse rate value
  • converting the extracted characteristic value into an intermediate characteristic value includes: converting the extracted characteristic value into a pulse rate value.
  • the analyzing based on the intermediate characteristic value to obtain regularity evaluation information includes: performing analysis based on the pulse rate value to obtain regularity evaluation information.
  • the intermediate feature value may also include a pulse sound feature value
  • converting the extracted feature value into an intermediate feature value includes: converting the extracted feature value into a pulse sound feature value.
  • the analyzing based on the intermediate characteristic value to obtain the regularity evaluation information includes: analyzing based on the pulse sound characteristic value to obtain the regularity evaluation information.
  • said converting the extracted characteristic value into a pulse sound characteristic value includes: determining the arrival time of the peak or trough of the pulse according to the extracted characteristic value, marking the peak or trough at the arrival time of the peak; marking according to the peak or trough Generate pulse sound characteristic values.
  • the analysis based on the characteristic value of the pulse sound to obtain the regularity evaluation information may further include: marking the peaks or troughs of the pulse wave signal in a period of time or several cycles to obtain at least two peak marks or Trough markers to obtain at least two pulse sound characteristic values generated by at least two peak markers or at least two trough markers; the at least two pulse sound characteristic values are analyzed through statistical analysis and/or machine learning, and Obtain the regularity evaluation information.
  • the method further includes: outputting prompt information according to the regularity evaluation information.
  • the output of the prompt information according to the regularity evaluation information is also the same as the related content of the analysis method in the embodiment shown in FIG. 2. For details, please refer to the related description of FIG. 2.
  • the prompt information includes at least one of pulse wave related information, executable function related information, and the regularity evaluation information;
  • the type of regularity evaluation information includes an evaluation result used to indicate regular or irregular pulse beats and/or heart rhythms
  • the pulse wave-related information includes pulse wave waveforms and/or rhythm quantification parameter values
  • the executable function is a function that can be executed in the next step when the regularity evaluation information meets the preset condition.
  • the pulse wave waveform is a waveform pattern obtained by a pulse wave signal.
  • the rhythm quantification parameter value includes at least one characteristic value including pulse interval, pulse amplitude, pulse area, pulse slope, and pulse envelope, and/or includes the maximum value, ratio, and sum based on statistical analysis of at least one characteristic value , Integral, difference, mean, standard deviation, maximum interval, minimum interval, pulse variability, statistical analysis data including at least one of the number of mutations, and/or at least one including the threshold of variability and number of mutations A threshold.
  • the regularity evaluation information is displayed in at least one of the following forms: text, pattern, and light.
  • the type of the regularity evaluation information includes a pulse and/or heart rhythm used to indicate regular or irregular, and the method further includes: outputting alarm information when the regularity evaluation information is irregular.
  • the content of the output alarm information is also the same as the related content of the analysis method in the embodiment shown in FIG. 2, and for details, please refer to the related description of FIG.
  • the presentation form of the alarm information includes at least one of text, pattern, light, sound, and vibration.
  • outputting alarm information includes: determining an alarm gear according to the acquired characteristic value, and controlling the output of the alarm information of the corresponding alarm gear, wherein the alarm gear includes At least two gears.
  • the analysis method in FIG. 13 is to obtain signals through multiple types of sensors, and to obtain pulses from periodic physiological signals obtained from the first sensor. After filtering out the physiological sign signal obtained by at least one second sensor from the wave signal, the filtered pulse wave signal is analyzed to obtain the regularity evaluation information.
  • the pulse wave is obtained only according to the periodic physiological signal obtained by one sensor. The wave signal is then analyzed to obtain regularity evaluation information.
  • Other specific analysis steps are the same and can be referred to each other.
  • the first sensor includes at least one of a photoelectric sensor, a pressure sensor, an electromagnetic sensor, a sound sensor, and an acceleration sensor.
  • FIG. 14 is another further flowchart of the method for evaluating regularity evaluation information shown in FIG. 12.
  • the method includes:
  • the periodic physiological signal of the measuring object is acquired by the first sensor, where the first sensor is a non-cardiograph sensor (S141).
  • a pulse wave signal related to the measurement object is extracted from the periodic physiological signal (S143).
  • a characteristic value representing the fluctuation rhythm of the pulse wave is obtained (S145).
  • the characteristic value is analyzed to obtain the first regularity evaluation information and the physiological sign parameter value is analyzed to obtain the second regularity evaluation information (S146).
  • the final regularity evaluation information is obtained (S147).
  • step S124 in the flowchart shown in FIG. 12 may specifically include steps S144-S146 in the flowchart shown in FIG. 14.
  • the "obtain regularity evaluation information according to the pulse wave signal and the other physiological sign signals” specifically includes: “extract physiological sign parameter values from the other physiological sign signals", "according to the pulse The wave signal acquires the characteristic value that characterizes the fluctuation rhythm of the pulse wave", "Analyze the characteristic value to obtain the first regularity evaluation information and analyze the physiological sign parameter value to obtain the second regularity evaluation information", "According to the first Regular evaluation information and the second regular evaluation information to obtain the final regular evaluation information" these steps.
  • the other physiological sign signal is an electrocardiographic signal
  • the physiological sign parameter value is an electrocardiographic parameter value
  • the final regularity evaluation information is obtained based on the first regularity evaluation information and the second regularity evaluation information , Including: when the first regularity evaluation information and the second regularity evaluation information are consistent, any one of them is selected as the final regularity evaluation information; and when the first regularity evaluation information and the second regularity evaluation information When the evaluation information is inconsistent, the second regularity evaluation information is selected as the final regularity evaluation information.
  • the method further includes: using the feature value obtained according to the analysis to obtain the first regularity evaluation information as the input of the machine learning model, and using the final regularity evaluation information as the machine learning model Output and bind each other to further improve the machine learning model.
  • the at least one second sensor includes an ECG sensor, which can directly detect ECG signals and obtain regularity evaluation information, while the first sensor detects pulse waves obtained by non-ECG sensors.
  • the regularity evaluation information obtained by signal analysis is verified, and the regularity evaluation information obtained based on the ECG signal is used as the final regularity evaluation information, so as to train and improve the machine learning model, and improve the use of non-ECG sensors According to the accuracy of the regularity evaluation information obtained from the detected pulse wave signal, the regularity evaluation information of a single feature value or multiple feature values can be directly obtained according to the machine learning model.
  • the machine learning model can be stored in the memory of the monitoring equipment, or set in various data management systems such as department-level workstation equipment/hospital-level data center/hospital-level emergency center management equipment for summary, storage, and real-time update.
  • the regularity evaluation information After periodically sharing the characteristic values sent by the monitoring device or receiving the monitoring device in a wired or wireless manner, the regularity evaluation information will be analyzed through the machine learning model, and the regularity evaluation information will be sent to the monitoring device for storage or display. Understandably, as long as the feature value can be input into the machine learning model to obtain regularity evaluation information, there are no restrictions on the storage mode, storage device, and operating device of the machine learning model.
  • the ECG sensor and non-ECG sensor can be used for detection at the same time in the first several times, and in the subsequent, only the non-ECG sensor can be used for periodic physiological signals.
  • the detection, and the regular evaluation information based only on the signal obtained by the non-ECG sensor, can still ensure the accuracy of the evaluation.
  • FIG. 14 The difference between FIG. 14 and FIG. 13 lies in the specific implementation manner of "obtaining regularity evaluation information according to the pulse wave signal and the other physiological sign signals".
  • the analysis process of "analyzing the characteristic value to obtain the first regularity evaluation information” is the same as the analysis process of "analyzing the characteristic value to obtain the regularity evaluation information" in the embodiment shown in FIGS.
  • the “analyzing the physiological sign parameter value to obtain the second regularity evaluation information” may be the same as the “analyzing the characteristic value to obtain the first regularity evaluation information", and for details, please refer to the examples of FIGS. 2, 13 and other embodiments. Related description.
  • FIG. 15 is a flowchart of the filter selection process in the evaluation method shown in FIG.
  • the corresponding relationship between the ratio interval or the difference interval and the filter is also pre-stored, and the ratio is the aforementioned rhythm quantization parameter value and the other physiological signs parameter.
  • the filter selection process may also specifically include the following steps:
  • the first filter is selected for filtering (S152).
  • the second filter is selected for filtering (S154).
  • the third filter is selected for filtering (S155).
  • the first filter is selected for filtering.
  • the second filter is selected for filtering.
  • the third filter is selected for filtering.
  • the filter parameter can be determined according to the ratio interval or the difference interval at the same time as the filter, that is, after the filter is determined according to the ratio interval or the difference interval, the corresponding filter can also be determined according to the ratio interval or the difference interval.
  • Parameters, that is, different ratio intervals or difference intervals can also correspond to different filtering parameters.
  • FIG. 16 is a block diagram of a monitoring device 200 in an embodiment of the application.
  • the monitoring device 200 includes a sensor 210 and a processor 220.
  • the sensor 210 is used to obtain periodic physiological signals of the measuring object.
  • the processor 220 is connected to the sensor 210, and is configured to extract a pulse wave signal related to the measurement object from the periodic physiological signal, and obtain regularity evaluation information according to the pulse wave signal analysis.
  • the processor 220 performs filtering processing, amplifying processing, and A/D conversion (digital-to-analog conversion) processing on the periodic physiological signal to extract the pulse wave signal.
  • the processor 220 obtains regularity evaluation information according to the pulse wave signal analysis, including: the processor 220 obtains the characteristic value of the fluctuation rhythm of the pulse wave according to the pulse wave signal, and analyzes The characteristic value obtains regularity evaluation information.
  • the processor 220 is specifically configured to use at least one analysis technology of time domain technology, frequency domain technology, and nonlinear dynamics technology to perform feature extraction on the pulse wave signal to obtain corresponding at least one Eigenvalues.
  • the processor 220 may use an analysis technique or a combination of multiple analysis techniques to perform feature extraction on the pulse wave signal to obtain corresponding at least one/class of feature values.
  • the processor 220 may use time domain technology to perform feature extraction on the pulse wave signal to obtain at least one time domain feature value.
  • the processor 220 may only use time domain technology to perform feature extraction on the pulse wave signal to obtain at least one time domain feature value.
  • the at least one time domain characteristic value includes at least one of pulse interval, pulse amplitude, pulse area, pulse slope, pulse envelope, and pulse width.
  • the processor 220 uses frequency domain technology to convert the pulse wave signal into a frequency domain signal, and then performs feature extraction on the frequency domain signal to obtain at least one frequency domain feature value.
  • only frequency domain technology may be used to perform feature extraction on the pulse wave signal to obtain at least one frequency domain feature value.
  • the frequency domain characteristic value includes, but is not limited to, including but not limited to characteristic values such as spectrum characteristics and power spectrum characteristics.
  • the processor 220 may use nonlinear dynamics technology to perform feature extraction on the pulse wave signal to obtain at least one nonlinear dynamics feature value.
  • only the nonlinear dynamics technology may be used to perform feature extraction on the pulse wave signal to obtain at least one nonlinear dynamics feature value.
  • the nonlinear dynamics characteristic value includes entropy or complexity.
  • the entropy includes, but is not limited to, information entropy, spectral entropy, approximate entropy, sample entropy, fuzzy entropy and other entropy features.
  • the processor 220 uses at least one analysis technology of time domain technology, frequency domain technology, and nonlinear dynamics technology to perform feature extraction on the pulse wave signal to obtain at least one feature value, or Specifically, it includes: using at least one analysis technology of time domain technology, frequency domain technology, and nonlinear dynamics technology to perform feature extraction on the pulse wave signal to obtain at least two types of feature values, according to the two types of feature values and each type of feature The weight of the value yields the final characteristic value.
  • the processor 220 can obtain the final characteristic value according to the weighted calculation formula ax+by.
  • x can be the time domain eigenvalue
  • y can be the frequency domain eigenvalue
  • a is the weight value of the time domain eigenvalue
  • b is the weight value of the frequency domain eigenvalue
  • the monitoring device further includes a memory 230, and the weight value of the time domain characteristic value and the weight value of the frequency domain characteristic value may be preset and stored in the memory 230.
  • the multiple different feature values include multiple types of feature values (such as time domain feature values, frequency domain feature values, etc.) analyzed through different analysis techniques and/or multiple types of different features analyzed through the same analysis technology. Characteristic values (such as pulse interval, slope, etc.).
  • analyzing the characteristic value by the processor 220 to obtain regularity evaluation information may include: comparing the at least one characteristic value of the processor 220 with the corresponding at least one characteristic value threshold, and comparing As a result, regular evaluation information is obtained.
  • the regularity evaluation information used to indicate the rule or irregularity can be obtained directly according to the characteristic value of the pulse wave signal that represents the fluctuation rhythm of the pulse wave.
  • the characteristic value may include at least one of pulse interval, pulse amplitude, pulse area, pulse slope, pulse envelope, pulse width, and may also include spectrum characteristics, power spectrum characteristic values, etc. Can include entropy, complexity, etc.
  • the at least one characteristic value may be a characteristic value of pulse interval
  • the preset threshold may be a preset pulse interval range
  • the processor 220 compares the at least one characteristic value with the corresponding at least one characteristic value threshold
  • And obtaining regularity evaluation information according to the comparison result may further include: the processor 220 compares the pulse interval with a preset pulse interval range, and when the pulse interval is determined to be outside the preset pulse interval range, it is obtained as "irregular "Regularity evaluation information", when it is determined that the pulse interval is within the preset pulse interval range, the "rule" regularity evaluation information is obtained.
  • the processor 220 obtains the characteristic value representing the fluctuation rhythm of the pulse wave according to the pulse wave signal, and may further include: the processor 220 performs processing on the pulse wave signal for a period of time or several cycles. At least two feature values are obtained by feature extraction; and the at least two feature values are analyzed by a statistical analysis method and/or a machine learning method to obtain the regularity evaluation information.
  • the processor 220 performs feature extraction on the pulse wave signal of a period of time or several cycles to obtain at least two feature values.
  • the processor 220 may also adopt time domain technology, frequency domain technology and nonlinear dynamics.
  • At least one analysis technology in the science technology performs feature extraction on the pulse wave signal of a period of time or several cycles to obtain at least two feature values.
  • the statistical analysis data may be the maximum value, ratio, sum, integral, difference, mean, standard deviation, maximum interval, minimum interval, pulse variability, number of mutations, and maximum based on the aforementioned characteristic values. At least one of the pulse rate value and the minimum pulse rate value, said obtaining the regularity evaluation information according to the statistical analysis data may include adding the maximum value, ratio, sum, integral, difference, Statistical analysis data such as mean, standard deviation, maximum interval, minimum interval, pulse variability, number of variations, maximum pulse rate value, minimum pulse rate value and the preset maximum value, ratio, sum, integral, difference, etc. The mean, standard deviation, maximum interval, minimum interval, pulse variability, number of variations, maximum pulse rate, minimum pulse rate and other preset statistical data are compared, and the results are used to express regular or irregular statistics. The regular evaluation information.
  • the processor 220 may perform statistical analysis on the characteristic values representing the fluctuation rhythm of the pulse wave obtained according to the pulse wave signal, and obtain statistical analysis data, and then obtain the data used to express the rule or Irregular regularity evaluation information.
  • the machine learning method may be to establish a machine learning model, for example, a neural network model, through model training, so that the processor 220 may use the at least two feature values as input to the machine learning model and automatically obtain them for use.
  • a machine learning model for example, a neural network model
  • the processor 220 may use the at least two feature values as input to the machine learning model and automatically obtain them for use.
  • the regularity evaluation information indicating regularity or irregularity.
  • the feature extraction is performed on the pulse wave signal of a certain period of time or several cycles to obtain at least two feature values that are different feature values obtained by feature extraction on different periods of the pulse wave signal,
  • they can be the same type of feature value or different types of feature value.
  • feature extraction is performed on multiple different time periods within a certain time period through time domain technology to obtain multiple characteristic values of the type of multiple pulse intervals.
  • it is also possible to perform feature extraction on multiple different time periods within a certain time period for example, three time periods using time domain technology, frequency domain technology, and nonlinear dynamics technology to obtain corresponding time domain features. Value, frequency domain characteristic value and nonlinear dynamic characteristic value.
  • the at least two characteristic values are characteristic values obtained by characteristic extraction of pulse wave signals in a certain period of time or in different periods of several cycles, and the extraction method of each characteristic value may also be At least one analysis technology of time domain technology, frequency domain technology, and nonlinear dynamics technology is used to extract features of the same waveform segment of the pulse wave signal to obtain at least two types of feature values. According to the two types of feature values and each type The weight of the eigenvalue is the final eigenvalue of the waveform segment.
  • the processor 220 after the processor 220 obtains the characteristic value representing the fluctuation rhythm of the pulse wave according to the pulse wave signal, it is further configured to evaluate the quality of the pulse wave signal according to the characteristic value to obtain the quality factor; And determining whether to adopt or discard the pulse wave signal currently obtained according to the quality factor.
  • the method of obtaining the quality factor may be the same as the method of “obtaining the characteristic value of the fluctuation rhythm of the pulse wave according to the pulse wave signal” described above, except that the characteristic obtained is the quality factor. value.
  • the quality factor may be at least one time domain value of pulse interval, pulse amplitude, pulse area, pulse slope, pulse envelope, and pulse width obtained through time domain technology, or may be obtained through frequency domain technology.
  • the output includes at least one frequency domain value such as a frequency spectrum feature, a power spectrum feature value, etc., and may also be at least one nonlinear dynamics value such as entropy value and complexity obtained by nonlinear dynamics technology.
  • the quality factor may be the maximum value, ratio, sum, integral, difference, mean, standard deviation, maximum interval, minimum interval, pulse variability, number of variations, maximum pulse rate, minimum pulse rate At least one of the values.
  • the processor 220 determines that the currently obtained pulse wave signal can be used according to the quality factor, further analysis is performed according to the obtained characteristic value to obtain regularity evaluation information.
  • the characteristic value is credible, and further analysis is performed directly based on the acquired characteristic value to obtain a regularity evaluation information.
  • the processor 220 performs further analysis according to the acquired characteristic value to obtain regularity evaluation information, which is the same as the aforementioned processing procedure of "analyzing the characteristic value to obtain regularity evaluation information".
  • the processor 220 is further configured to perform further analysis according to the quality factor and the acquired characteristic value when it is determined that the currently obtained pulse wave signal can be used according to the quality factor to obtain regularity evaluation information .
  • the processor 220 performs further analysis according to the quality factor and the acquired characteristic value to obtain regularity evaluation information, which may include: the processor 220 determines the weight value of the characteristic value according to the quality factor and The weight value of the quality factor; weighted calculation of the characteristic value and the quality factor according to the weight value of the characteristic value and the weight value of the quality factor to obtain a weighted characteristic value; analysis according to the weighted characteristic value to obtain The regularity evaluation information.
  • the processor 220 may analyze the quality of the pulse wave signal to obtain a quality factor indicating the quality of the pulse wave signal. Since the quality factor itself is obtained in the same manner as the characteristic value, Therefore, the quality factor and the characteristic value obtained according to the pulse wave signal can be weighted to obtain a weighted adjustment value, and then analyzed according to the weighted characteristic value to obtain the regularity evaluation information, which can effectively improve the accuracy of the regularity evaluation information.
  • the determining the weight value of the characteristic value and the weight value of the quality factor according to the quality factor may specifically include: comparing the obtained quality factor with a corresponding quality factor threshold, and determining the quality factor of the quality factor according to the comparison result Weight value j1; and determine the weight value of the feature value (1-j1).
  • the quality factor may include at least one quality factor, and may be different types of quality factors obtained by different analysis techniques or different types of quality factors obtained by the same analysis technique.
  • the quality factor obtained by time domain technology As an example, through time domain analysis, the following values are obtained: pulse wave amplitude standard deviation, peak-peak interval average, peak-peak interval maximum, then the pulse wave amplitude standard deviation, The peak-to-peak interval average value, the peak-to-peak interval maximum and minimum values are compared with the standard deviation threshold, the interval average threshold, and the interval maximum threshold, and the weighted value j1 of the quality factor is determined according to the comparison result. Among them, when the signal quality is better, the weight value of the corresponding quality factor is smaller; conversely, when the signal quality is worse, the weight value of the corresponding quality factor is larger.
  • the threshold may be a single threshold, or may include two thresholds, for example, a threshold range formed by the first threshold and the second threshold.
  • the weight value j1 of the quality factor ranges from 0 to 1
  • the weight value 1-j1 of the feature value also ranges from 0 to 1.
  • the better the quality signal is set the smaller the weighting value of the corresponding quality factor is: when the quality signal is better, the quality factor should be weakened, and the characteristic value obtained from the pulse wave signal at this time is also more accurate.
  • the eigenvalues should be strengthened, so in this case, the smaller the weight value of the quality factor, the greater the weight value of the eigenvalue; and vice versa.
  • the weighting value of the quality factor can be a smaller value, such as 0.2, and the eigenvalue should be strengthened, so the weight of the eigenvalue
  • the frequency spectrum of a signal can be obtained for a period of time, and the number of spectrum peaks whose spectrum peak amplitude>a is counted.
  • the further analysis based on the quality factor and the acquired characteristic value to obtain regularity evaluation information may further include:
  • the characteristic value and the quality factor coefficient are calculated to obtain the corrected characteristic value, and then the regularity evaluation information is obtained according to the corrected characteristic value.
  • the characteristic value and the quality factor coefficient are calculated to obtain the corrected characteristic value, and then the regularity evaluation information is obtained according to the corrected characteristic value.
  • the calculation is multiplication. Understandably, the calculation includes at least one of multiplication, division, subtraction, and addition. For example, when the calculation includes division, the characteristic value is divided by the quality factor coefficient. When the signal quality is higher, the quality factor coefficient is larger, and the maximum is equal to 1. When the signal quality is worse, the quality factor coefficient is smaller.
  • the method for obtaining the quality factor is the same as before, and will not be repeated here.
  • mapping the quality factor to the quality factor coefficient of the acquired feature value includes: comparing the quality factor with a corresponding quality factor threshold, and mapping the quality factor to The quality factor coefficient of the acquired characteristic value.
  • the threshold may be a single threshold, or may include two thresholds, for example, a threshold range formed by the first threshold and the second threshold.
  • the signal quality when it is satisfied that the amplitude standard deviation is ⁇ a, and the peak-to-peak interval average value/peak-to-peak interval maximum value ⁇ b, the signal quality is judged to be good, and the corresponding quality factor coefficient can be 1.
  • the signal quality is judged to be medium, and the quality factor coefficient is 0.8; when the standard deviation of amplitude> c, and the maximum value (minimum value) of the peak-to-peak interval/average value of the peak-to-peak interval>d, the signal quality is judged to be low, and the quality factor coefficient is 0.5.
  • the frequency spectrum of a signal can be obtained for a period of time, and the number of spectrum peaks whose spectrum peak amplitude>a is counted.
  • the quality factor coefficient multiplied by the eigenvalue is smaller, so that the interference signal corresponding to the eigenvalue is greatly reduced, thereby effectively avoiding interference.
  • the processor 220 is further configured to obtain a noise template signal when the signal quality is determined to be low, and perform denoising processing on the pulse wave signal based on the noise template signal to obtain the denoising Pulse wave signal.
  • the processor 220 acquiring the characteristic value representing the fluctuation rhythm of the pulse wave according to the pulse wave signal may include: the processor 220 acquiring the characteristic value representing the fluctuation rhythm of the pulse wave according to the denoised pulse wave signal.
  • the processor 220 may remove the component corresponding to the noise template signal from the pulse wave signal to obtain the pulse wave signal after noise removal.
  • the processor 220 after the processor 220 obtains the characteristic value representing the fluctuation rhythm of the pulse wave according to the pulse wave signal, it is further configured to convert the extracted/acquired characteristic value into an intermediate characteristic value; the processor 220 and used to analyze based on the intermediate characteristic value to obtain regularity evaluation information.
  • the intermediate feature value includes a pulse rate value
  • the processor 220 converting the extracted feature value into an intermediate feature value includes: the processor 220 converts the extracted feature value into a pulse rate value.
  • the processor 220 is further configured to perform analysis based on the pulse rate value to obtain regularity evaluation information.
  • the processor 220 performs analysis based on the pulse rate value to obtain the regularity evaluation information, including: the processor 220 obtains the difference between pulse rates, and when the difference between consecutive pulse rates is satisfied The difference exceeds the threshold, or at least n of the N adjacent pulse rate differences meet the threshold, or there is a pulse rate that exceeds or is less than the average pulse rate (threshold), or the standard deviation of the pulse rate divided by When the average pulse rate exceeds the threshold, it is judged that it is suspected to be irregular.
  • the intermediate feature value may further include a pulse sound feature value.
  • the processor 220 converting the extracted feature value into an intermediate feature value includes: the processor 220 converting the extracted feature value It is the characteristic value of pulse sound.
  • the processor 220 is also configured to perform analysis based on the pulse sound characteristic value to obtain regularity evaluation information.
  • the processor 220 performs analysis based on the pulse sound characteristic value to obtain regularity evaluation information, including: the processor 220 obtains the pulse sound interval, and when the difference value of several consecutive adjacent intervals is satisfied Exceeds the threshold, or at least n differences in N adjacent interval differences exceed the threshold, or there is an interval that exceeds or is less than the average of the interval (threshold), or the standard deviation of the interval divided by the average of the interval exceeds At the threshold value, it is judged that it is suspected to be irregular.
  • the processor 220 converting the extracted characteristic value into a pulse sound characteristic value includes: the processor 220 determines the arrival time of the peak or trough of the pulse according to the extracted characteristic value. Mark the peaks or troughs at all times; generate pulse sound characteristic values according to the markers of the peaks or troughs.
  • the processor 220 analyzes based on the pulse sound characteristic value to obtain regularity evaluation information, which may further include: the processor 220 evaluates the pulse wave signal within a certain period of time or several cycles The peaks or troughs are marked to obtain at least two peaks or trough markers, and at least two pulse sound characteristic values generated from at least two peak markers or at least two trough markers are obtained; the statistical analysis and/or machine learning methods The at least two pulse sound characteristic values are analyzed to obtain the regularity evaluation information.
  • the processor 220 analyzes the at least two pulse sound feature values through statistical analysis and/or machine learning to obtain the regularity evaluation information, which may include: the processor 220 performs statistical analysis The scientific analysis method analyzes the at least two pulse sound characteristic values to obtain statistical analysis data, and obtains the regularity evaluation information according to the statistical analysis data; and/or combines the at least two pulse sound The pulse sound characteristic value is used as input, and the output of the regularity evaluation information is obtained. That is, the at least two pulse sound feature values are used as the input of the machine learning model to obtain the output of the regularity evaluation information.
  • the processor 220 is further configured to output prompt information according to the regularity evaluation information.
  • the prompt information includes at least one of pulse wave related information, executable function related information, and the regularity evaluation information;
  • the type of regularity evaluation information includes an evaluation result used to indicate regular or irregular pulse beats and/or heart rhythms
  • the pulse wave-related information includes pulse wave waveforms and/or rhythm quantification parameter values
  • the executable function is a function that can be executed in the next step when the regularity evaluation information meets the preset condition.
  • the rhythm quantitative parameter value includes at least one characteristic value including pulse interval, pulse amplitude, pulse area, pulse slope, pulse envelope, and pulse width, and/or at least includes the maximum value statistically analyzed according to at least one characteristic value , Ratio, Sum, Integral, Difference, Mean, Standard Deviation, Maximum Interval, Minimum Interval, show the degree of variability, statistical analysis data including one of the times of variation.
  • the monitoring device 200 further includes a display screen 240, the regularity evaluation information can be displayed on the first display area of the display screen, and the pulse wave related information can be displayed on the second display area of the display screen.
  • relevant information about executable functions can be displayed in the third display area of the display screen. That is, the prompt information may specifically include at least one of the following: the regularity evaluation information displayed in the first display area of the display screen 240; and the pulse wave displayed in the second display area of the display screen 240 Related information; related information of the executable function displayed in the third display area of the display screen 240, wherein the executable function is the next executable function when the regularity evaluation information meets the preset condition.
  • the regularity evaluation information may include evaluation results used to indicate rules or irregularities.
  • the regularity evaluation information is displayed in at least one of the following forms: text, pattern, light, sound, and vibration.
  • the processor 220 displays corresponding prompt information according to whether the regularity evaluation information is used to indicate a rule or an irregularity.
  • the prompt information may only include the regular evaluation information P1 of "suspected irregular pulse".
  • the first display area A1 may be the entire display of the display screen. Area or a certain area in the current interface displayed on the screen.
  • the current interface may be a certain functional interface or system interface of the monitoring device 200.
  • the regularity evaluation information P1 can also include other words such as "irregular pulse”, “irregular”, “abnormal pulse”, “abnormal”, “irregular pulse interval”, etc., as long as it can prompt the measurement object to be present. Irregular pulse or irregular pulse may occur, and there is no restriction on its written expression.
  • the prompt information may be "regular pulse”, “rule”, "normal” and other text information that can prompt the measurement subject to have a normal pulse.
  • the prompt information includes regular evaluation information
  • the user can directly see the results of the device's intelligent analysis, which is convenient and intuitive, and facilitates the user to perform follow-up examinations, such as booking an ECG examination, ultrasound examination, etc.
  • the prompt information may only include the pulse wave related information P2 displayed in the second display area A2.
  • the second display area A2 may be the entire display area of the display screen or a certain area in the current interface displayed on the display screen.
  • the prompt information can be displayed on the current interface through a pop-up window.
  • the prompt information may be displayed on the prompt interface after switching from the current interface to a prompt interface.
  • the prompt information includes pulse wave related information P2
  • it can provide the user with a waveform reference for the user to confirm the regular evaluation information.
  • the prompt information may also include the regularity evaluation information P1 and the pulse wave related information P2.
  • the first display area A1 where the regularity evaluation information P1 is located is adjacent to the second display area A2 where the pulse wave related information P2 is located. Understandably, the first display area A1 and the second display area A2 may not be adjacent to each other, and may be set arbitrarily. In this embodiment, the adjacent settings of the first display area A1 and the second display area A2 can facilitate the user to intuitively view the regularity evaluation information and combine the pulse wave related information to determine the occurrence regularity of the measurement object based on the pulse wave related information Specific reasons for evaluating information.
  • the prompt information may include regularity evaluation information P1 displayed in the first display area A1, pulse wave related information P2 displayed in the second display area A2, and pulse wave related information P2 displayed in the second display area A2.
  • Information P3 related to the executable function of the area A3 is displayed. Displaying the relevant information P3 of the executable function can play a role of prompting and guiding the relevant operation to be performed in the next step, so that the user can learn and execute the operation to be performed in the next step.
  • first display area A1, the second display area A2, and the third display area A3 are sequentially arranged adjacent to A3.
  • the first display area A1, the third display area A3, and the second display area A2 may be arranged adjacently in sequence, as long as it is ensured that multiple areas are arranged adjacently. The order can be adjusted arbitrarily.
  • the at least two display areas are located on the display screen 240 adjacently. Understandably, the at least two display areas are arranged adjacently on the display screen to facilitate the user to view the regularity evaluation information, pulse wave related information, and executable function related information. In other embodiments of the present application, the display areas may not be arranged adjacently.
  • the display screen further includes a touch area T for retracting or expanding the second display area P2 to hide or display the pulse wave related information A2 accordingly.
  • the regularity evaluation information A1 is displayed in the first display area P1, which is convenient for the user to pay attention to the regularity evaluation information A1, the second display area P2 is retracted, and the pulse wave related information A2 is hidden. This setting allows users to choose to view or hide pulse wave related information according to actual needs.
  • the prompt information including at least one of the regularity evaluation information, pulse wave related information, and executable function related information prompt information can also be displayed on the current interface in a pop-up window, or switch from the current interface After reaching a prompt interface, it is displayed in the prompt interface.
  • the regularity evaluation information is displayed in at least one of the following forms: text, pattern, and light.
  • the regularity evaluation information may include both text and patterns: "Suspected irregular pulse Obviously, an indicator light can also be provided on the display, and the regularity evaluation information can also be indicated by the light emitted by the indicator light. For example, when a red light is emitted, it indicates “irregularity", and when a green light is emitted When, indicate "rules”.
  • the prompt information when the prompt information is displayed in a pop-up window and includes at least two of the regularity evaluation information, pulse wave related information, and executable function related information, the regularity evaluation information, pulse wave At least two of the wave-related information and the relevant information prompt information of the executable function may be displayed in the same window, or may be displayed in different windows. That is, at least two of the first display area A1, the second display area A2, and the third display area A3 may be located in the same window, or may be located in different windows.
  • the second display area A2 further includes a first sub display area A21, and the pulse wave related information includes pulse wave waveforms displayed in the first sub display area for a period of time.
  • the pulse wave waveform is a corresponding pulse wave waveform obtained by extracting a pulse wave signal related to the measurement object from the periodic physiological signal. By displaying the pulse wave waveform, the pulsation of the pulse can be visually displayed.
  • the second display area A2 includes a second sub display area A22
  • the pulse wave related information also includes rhythm quantization parameter values
  • the rhythm quantization parameter values include displayed in the second sub display area
  • the statistical analysis data includes the maximum value, ratio, sum, integral, difference, mean, standard deviation, maximum interval, minimum interval, display variability, number of variations, and maximum pulse rate of the characteristic value At least one of the minimum pulse rate values;
  • the characteristic value includes: at least one of pulse interval, pulse amplitude, pulse area, pulse slope, pulse envelope, and pulse width. That is, the pulse wave-related information may also include characteristic values representing the fluctuation rhythm of the pulse wave obtained directly from the pulse wave signal, and/or statistical analysis data obtained after statistical analysis of these characteristic values.
  • the first sub-display area A21 and the second sub-display area A22 are adjacently arranged.
  • the specific positional relationship between the first sub-display area A21 and the second sub-display area A22 is not limited.
  • the second sub-display area A22 is on the upper side, or as shown in FIG. 5-6
  • the first sub-display area A21 may be at the top.
  • the information related to the executable function includes guide information of the executable function and/or function icon of the executable function.
  • the guide information of the executable function is used to inform the user of the executable function that can be performed by the monitoring device 200 after the monitoring device 200 outputs the prompt information.
  • the guide information can be text or pattern to guide the user to understand the monitoring The executable functions of the device 200 and how to trigger the executable functions.
  • the relevant information of the executable function may also directly include the function icon B1 of the executable function, so that the function icon B1 of each executable function is displayed in a more direct manner, and the function icon B1 of each executable function is displayed for user operation to trigger The corresponding executable function.
  • the processor 220 is further configured to control the execution of the function corresponding to the function icon B1 in response to the trigger operation on the function icon B1.
  • the executable functions include at least one of printing pulse wave waveforms, scheduling ECG examinations, and scheduling ultrasound examinations, and may also include other functions, such as user-defined common functions.
  • the function icon B1 may include at least one function icon including a function icon for printing pulse wave waveforms, a function icon for scheduled ECG examination, and a function icon for scheduled ultrasound examination.
  • the type of regularity evaluation information includes regular or irregular pulse beats and/or heart rhythms.
  • the processor 220 is also used for evaluating regularity. When the information is irregular, output alarm information.
  • the presentation form of the alarm information includes at least one of text, pattern, light, sound, and vibration.
  • the monitoring device 200 further includes an indicator light 250, a speaker 260, and a vibrator 270.
  • the processor 220 may control the display screen 240 to display the text and/or pattern.
  • the processor 220 may control the display screen 240 to display the text and/or pattern.
  • the processor 220 The display screen or the indicator light 250 can be controlled to display corresponding light, for example, the entire screen or a specific area of the display screen can be controlled to display colors such as red, or the indicator light 250 can be controlled to emit red light.
  • the indicator light 250 may specifically be an indicator light including a red LED light, a green LED light, and a blue LED light.
  • the processor 220 may generate or mix colors by controlling the lighting of different colors and/or numbers of LED lights. The corresponding color light.
  • the processor 220 may control the speaker 260 to output sound.
  • the processor 220 may control the vibrator 270 to generate vibration.
  • the processor 220 when the regularity evaluation information is irregular, the processor 220 also determines the alarm gear according to the acquired characteristic value, and controls the output of the alarm information of the corresponding alarm gear, wherein the alarm The gear positions include at least two gear positions.
  • the processor 220 compares the acquired characteristic value with multiple reference values, determines the characteristic value interval in which the characteristic value is located, and according to the determined characteristic value interval and the corresponding relationship between the characteristic value interval and the alarm gear, Determine the corresponding alarm gear.
  • the processor 220 determines that the corresponding alarm gear is the first alarm gear when the slope is greater than or equal to the first slope and less than the first slope, And control to emit a green light or an audible alarm message with a smaller decibel; when the slope is greater than or equal to the first slope and less than the third slope, the processor 220 determines that the corresponding alarm gear is the second alarm gear, and controls to emit orange Light or medium-decibel sound alarm information; when the slope is greater than or equal to the third slope, the processor 220 determines that the corresponding alarm gear is the third alarm gear, and controls to emit a red light or the highest-decibel sound alarm information.
  • first slope is smaller than the second slope
  • second slope is smaller than the third slope
  • first alarm gear is smaller than the second alarm gear
  • second alarm gear is smaller than the third alarm gear
  • the number of the alarm gears can be any suitable value such as 2, 3, 4, etc.
  • the correspondence relationship between the characteristic value interval and the alarm gear position may be a correspondence relationship table, a correspondence relationship curve, etc., pre-stored in the memory 230.
  • the processor 220 is further configured to respond to a result change operation or confirmation operation input by the user, and change or confirm the regularity evaluation information used to indicate a rule or an irregularity.
  • the prompt information can be displayed on an interface in a pop-up window.
  • the prompt information includes a detailed information zone Z1 and a judgment zone Z2.
  • the detailed information zone Z1 displays The detailed information is for the user to judge whether the rule is ruled or not.
  • the judgment zone Z2 includes the options of “rule” and “irregular”. The options of “rule” and “irregular” are used for the user to select to obtain the regularity. Evaluation information.
  • the detailed information includes: pulse wave signal ("pleth" area in the figure), pulse identification, pulse interval measurement value, maximum interval, minimum interval, display variability and other information.
  • the content of the detailed information does not overlap with the content of the prompt information at all, and the detailed information gives more information than the prompt information. Understandably, in other embodiments of the present application, the content contained in the detailed information may also be partially or completely consistent with the content contained in the prompt information.
  • the processor 220 determines that the regularity evaluation information is a rule in response to a selection operation of the "rule” option, or confirms that the regularity evaluation information is irregular in response to a selection operation of the "irregular" option.
  • the prompt message includes a "rule” and "irregular” selection box displayed on a certain interface of the monitoring device 200.
  • the "rule” and “irregular” options are used for the user to choose to confirm or modify the regular evaluation information.
  • the current regularity evaluation information is prompted through the currently selected "rule" selection box S1 and “irregular” selection box S2, and the user can respond to the user's response to the "rule" selection box S1 or "irregular "Select box S2 to change the regular evaluation information.
  • the entire interface may be a prompt information interface.
  • the prompt information also includes an interface to provide an operation interface for the user to call up detailed information to assist the user in judgment.
  • the detailed information includes: pulse wave signal ("pleth" area in the figure), pulse identifier , Pulse interval measurement value, maximum pulse interval, minimum pulse interval, pulse interval variability and other information, or further including the variability threshold, the number of mutations, the threshold of the number of mutations, the maximum pulse rate, the minimum pulse rate and other information.
  • the prompt information of FIGS. 7-10 may also be output when the processor 220 controls the output of the alarm information, for example, when the sound alarm information is output, the display screen 240 is simultaneously controlled to display corresponding prompt information.
  • the processor 220 is further configured to determine the prompt information to be displayed according to the regularity evaluation information before outputting the prompt information according to the regularity evaluation information.
  • the processor 220 determines that the regularity evaluation information in the prompt information to be displayed is a text or pattern such as "rules", and when the regularity evaluation information is irregular, it determines that the regularity evaluation information is irregular.
  • the regularity evaluation information in the displayed prompt information is text or patterns such as "irregular”.
  • the monitoring device 200 further includes a communication unit 280, which is used to establish communication with a monitoring management device 300 such as department-level workstation equipment and/or hospital-level data center/hospital-level emergency center management equipment. connection.
  • a monitoring management device 300 such as department-level workstation equipment and/or hospital-level data center/hospital-level emergency center management equipment. connection.
  • the communication unit 280 can also be used to communicate with the bedside monitoring device 202 and department-level workstation equipment and/or hospital-level data center/hospital-level emergency center management equipment and other monitoring management equipment 300 Establish a communication connection.
  • the communication unit 280 includes at least one of a Bluetooth module, a WMTS communication module, an NFC communication module, a WIFI communication module, and a mobile communication network module such as 2G/3G/4G/5G.
  • the processor 220 is further configured to send the prompt information to the department-level workstation equipment and/or the hospital-level data center/hospital-level emergency center management equipment and other monitoring and management equipment 300 through the communication unit 280, through the department-level workstation equipment And/or the hospital-level data center/hospital-level emergency center management equipment outputs the prompt information.
  • the processor 220 may send the regularity evaluation information or the prompt information to the bedside monitoring device 202, department-level workstation equipment, and/or hospital-level Monitoring and management equipment 300 such as data center/hospital-level emergency center management equipment, through the bedside monitoring equipment 202, department-level workstation equipment, and/or hospital-level data center/hospital-level emergency center management equipment, output the information according to the regularity evaluation information Prompt information.
  • the prompt information can also be sent to the bedside monitoring device 202 for display output.
  • the processor 220 is further configured to send the periodic physiological signals to department-level workstation equipment and/or hospital-level data center/hospital-level emergency center management equipment through the communication unit 280, through the department-level workstation Equipment and/or hospital-level data center/hospital-level emergency center management equipment performs "extracting the pulse wave signal related to the measurement object from the periodic physiological signal” and “processing the pulse wave signal to extract the pulse wave signal "Acquire the characteristic value of the fluctuation rhythm of the pulse wave according to the pulse wave signal” and "analyze the characteristic value to obtain the regularity evaluation information" to obtain the regularity evaluation information.
  • the processor 220 is further configured to receive regularity evaluation information from department-level workstation equipment and/or hospital-level data center/hospital-level emergency center management equipment through the communication unit 280, and according to the received The regularity evaluation information outputs prompt information.
  • the processor 220 may send the periodic physiological signals to the bedside monitoring device 202, department-level workstation equipment and/or hospital-level data center/hospital. Level emergency center management equipment, etc., through the bedside monitoring equipment 202, department-level workstation equipment and/or hospital-level data center/hospital-level emergency center management equipment, etc., to obtain regular evaluation information; and the processor 220 also Regularity evaluation information can be received from the bedside monitoring equipment 202, department-level workstation equipment, and/or hospital-level data center/hospital-level emergency center management equipment, and output prompt information according to the received regularity evaluation information.
  • the prompt information may also be determined by department-level workstation equipment and/or hospital-level data center/hospital-level emergency center management equipment, and then sent to the monitoring device 200 for display output.
  • the processor 220 may directly receive prompt information from department-level workstation equipment and/or hospital-level data center/hospital-level emergency center management equipment through the communication unit 280.
  • the processor 220 is further configured to perform the following operations: after processing the pulse wave signal to extract the pulse wave signal, perform quality analysis on the pulse wave signal to obtain a quality evaluation value; and compare the quality evaluation value with A preset threshold value for comparison; when it is determined that the quality evaluation value is less than the preset threshold value, the subsequent analysis step of regularity evaluation information is not performed or prompt information is not output, or the subsequent analysis step of regularity evaluation information is not performed In the case of outputting prompt information; when it is determined that the quality evaluation value is greater than or equal to the preset threshold, the subsequent step of analyzing the regularity evaluation information is performed.
  • the quality evaluation value may be the aforementioned quality factor.
  • the “performing the subsequent step of analyzing the regularity evaluation information” may further include: mapping the quality evaluation value to the quality factor coefficient of the acquired characteristic value; and combining the characteristic value and The quality factor coefficient is calculated to obtain the corrected characteristic value; the analysis is performed according to the corrected characteristic value to obtain the regularity evaluation information.
  • the processor 220 uses at least one analysis technique of time domain technology, frequency domain technology, and nonlinear dynamics technology to perform feature extraction on the pulse wave signal to obtain at least one feature value; and
  • the at least one characteristic value obtains a quality evaluation value.
  • the processor 220 may use one of time domain technology, frequency domain technology, and nonlinear dynamics technology to perform feature extraction on the pulse wave signal to obtain at least one feature value.
  • the processor 220 may use at least one analysis technology of time domain technology, frequency domain technology, and nonlinear dynamics technology to perform feature extraction on the pulse wave signal to obtain at least two types of feature values. The value and the weight of each type of feature value yield the final feature value.
  • the processor 220 performing the subsequent step of analyzing the regularity evaluation information may also include: the processor 220 determining the weight value of the characteristic value and the weight value of the quality quality evaluation value according to the quality evaluation value According to the weight value of the characteristic value and the weight value of the quality evaluation value, the characteristic value and the quality evaluation value are weighted and calculated to obtain the weighted characteristic value; the weighted characteristic value is analyzed to obtain the regularity evaluation information.
  • the processor 220 directly outputting the prompt information without performing the subsequent step of analyzing the regularity evaluation information refers to outputting the prompt information not based on the regularity evaluation information.
  • the prompt information includes pulse wave related information, that is, pulse wave related information is directly output, where the pulse wave related information includes pulse wave waveform and rhythm quantization parameter values.
  • the prompt information only includes the pulse wave waveform in the pulse wave related information.
  • the processor 220 is further configured to receive an input instruction to execute the step of "obtain the characteristic value of the fluctuation rhythm of the pulse wave according to the pulse wave signal", and according to The characteristic value outputs a rhythm quantization parameter value.
  • Rhythm quantization parameter values are as described above, for example, include pulse interval, pulse amplitude, pulse area, pulse slope, pulse envelope, pulse width, etc., which will not be repeated here.
  • the monitoring device can also input instructions to trigger the monitoring device to execute the step "Acquire the characteristics of the pulse wave rhythm characteristics according to the pulse wave signal. Value", and obtain parameters including characteristic values such as pulse interval, pulse amplitude, pulse area, pulse slope, pulse envelope, pulse width, etc., and further information can be obtained for artificial judgment to obtain regularity evaluation and analysis.
  • the memory 230 also stores program instructions, which are used by the processor 220 to execute the method steps in FIG. 2 as described above.
  • the aforementioned methods in Fig. 2 and Fig. 11 and the functions of the monitoring device 200 in Fig. 12 can be referred to each other.
  • FIG. 17 is a module architecture diagram of a monitoring device 200 in another embodiment of the application. As shown in FIG. 12, it is a block diagram of the monitoring device 200. As shown in FIG. 17, the monitoring device 200 includes a first sensor 211, at least one second sensor 212 and a processor 220.
  • the first sensor 211 is used to obtain periodic physiological signals of the measuring object.
  • the at least one second sensor 212 is used to obtain signals of other physiological signs of the human body, wherein the first sensor 211 is a non-cardiograph sensor.
  • the processor 220 is configured to extract a pulse wave signal related to the measurement object from the periodic physiological signal, and obtain regularity evaluation information according to the pulse wave signal and the other physiological sign signals.
  • the processor 220 obtains regularity evaluation information according to the pulse wave signal and the other physiological sign signals, including: the processor 220 filters out the influence of other physiological sign signals in the pulse wave signal to obtain The filtered pulse wave signal; obtaining the characteristic value representing the fluctuation rhythm of the pulse wave according to the filtered pulse wave signal; and analyzing the characteristic value to obtain regularity evaluation information.
  • the processor 220 filters out the influence of other physiological signs from the pulse wave signal to obtain the filtered pulse wave signal, which specifically includes: the processor 220 obtains the rhythm based on the pulse wave signal Quantify parameter values and obtain other physiological sign parameter values according to the other physiological sign signals; determine a filtering scheme according to the rhythm quantitative parameter value and the other physiological sign parameter values; filter the pulse wave signal according to the filtering scheme In addition to the influence of other physiological signs, the filtered pulse wave signal is obtained.
  • the monitoring device 200 further includes a plurality of filters 290, for example, the plurality of filters 290 include filter 1, filter 2, filter N, etc., where N is a positive integer, and N is The quantity is set according to needs.
  • the multiple filters 290 may be hardware filters, for example, RC filters composed of adjustable resistors and adjustable capacitors, LC filters composed of adjustable inductors and adjustable capacitors, or digital filters. The filter, therefore, the filter parameters can be adjusted by adjusting resistance, capacitance, inductance, etc., or by digital adjustment.
  • the filtering scheme includes a selected filter 290 and filtering parameters.
  • the processor 220 determining the filtering scheme according to the rhythm quantization parameter value and the other physiological sign signals includes: the processor 220 according to the rhythm The ratio or difference between the quantization parameter value and the other physiological sign parameter value determines the corresponding target filter 290 and target filter parameter.
  • the processor 220 obtains the filtered pulse wave signal by filtering out the influence of other physiological signs in the pulse wave signal according to the filtering scheme, including: the processor 220 passes the target filter 290 to the The target filter parameter filters the pulse wave signal to obtain a filtered pulse wave signal.
  • each filter corresponds to a variety of filter parameters.
  • the target filter and the target filter parameter can also be determined according to other relationships between the rhythm quantization parameter value and the other physiological sign parameter value, such as a product.
  • the processor 220 determines the corresponding target filter and target filter parameter according to the ratio or difference between the rhythm quantization parameter value and the other physiological sign parameter value, including: the processor 220 according to a preset ratio Or the corresponding relationship between the difference and the filtering scheme, determine the filtering scheme corresponding to the ratio or difference between the rhythm quantization parameter value and the other physiological sign parameter value; determine that the filter 290 and the filtering parameter in the filtering scheme are respectively the Target filter 290 and target filter parameters.
  • the correspondence between the ratio and the filtering scheme may be a correspondence table pre-stored in the memory 230.
  • the at least one second sensor 212 includes a respiration sensor
  • the other physiological sign signal includes a respiration signal
  • the other physiological sign parameter value includes a respiration rate
  • the rhythm quantization parameter value includes a pulse rate
  • the first sensor includes at least one of a photoelectric sensor, a pressure sensor, an electromagnetic sensor, a sound sensor, and an acceleration sensor.
  • the photoelectric sensor radiates light of different wavelengths into the tissue area of the measurement object, and detects the optical signal sent through the tissue area as the aforementioned periodic physiological signal.
  • the photosensor may include a blood oxygen sensor.
  • the blood oxygen sensor is used to radiate light of different wavelengths into the tissue area of the measurement object, and detect the optical signal sent through the tissue area, so that the processor 220 can extract the light of the tissue area from the optical signal. Absorb the generated photoplethysmographic signal. That is, the aforementioned pulse wave signal derived from the periodic physiological signal is the photoplethysmographic pulse wave signal.
  • the blood oxygen sensor when the first sensor includes a blood oxygen sensor, the blood oxygen sensor includes a blood oxygen probe, and the blood oxygen probe may have a clamping structure for clamping on a measurement object, such as a patient's finger.
  • the tissue area may be a finger part area of the measurement object.
  • the pressure sensor is used to obtain the periodic physiological signal of the measurement object according to the change of the pressure in the pressure signal.
  • the pressure sensor may be a blood pressure sensor
  • the periodic physiological signal may be a periodic pressure signal generated by vascular fluctuations
  • the “extract the pulse wave signal related to the measurement object from the periodic physiological signal” “Includes: obtaining the pulse wave signal of the measurement object according to the change of the pressure in the pressure signal.
  • the electromagnetic sensor may include a conductive ring worn on the wrist and a Hall sensor and other sensors arranged in the magnetic field of the conductive ring.
  • the conductive ring on the wrist expands and contracts following the pulse of the pulse, resulting in a change in the magnetic field.
  • the Hall sensor detects the change and generates the corresponding electromagnetic induction signal.
  • the periodic physiological signal may be a periodic electromagnetic induction signal, and the "extracting the pulse wave signal related to the measurement object from the periodic physiological signal" includes: according to the change of the induction intensity in the electromagnetic induction signal The pulse wave signal of the measurement object is obtained.
  • the sound signal of pulse pulsation can be collected by the sound sensor sensor, that is, the periodic physiological signal can be a sound signal, and then analyzed by the characteristics of sound frequency, volume, timbre, etc. Can get pulse wave signal.
  • the specific manner in which the processor 220 obtains the characteristic value characterizing the fluctuation rhythm of the pulse wave according to the filtered pulse wave signal may be the same as obtaining the characterizing pulse wave according to the pulse wave signal in the embodiment shown in FIG.
  • the characteristic values of the fluctuating rhythms are the same, except that the pulse wave signal is a filtered pulse wave signal.
  • the pulse wave signal is a filtered pulse wave signal.
  • the processor 220 obtains the characteristic value of the fluctuation rhythm of the pulse wave according to the filtered pulse wave signal, including: the processor 220 adopts the time domain technology, the frequency domain technology and the nonlinear dynamics technology. At least one analysis technique performs feature extraction on the pulse wave signal to obtain corresponding at least one feature value.
  • the processor 220 uses time domain technology to perform feature extraction on the pulse wave signal to obtain at least one time domain feature value.
  • the at least one time domain characteristic value includes at least one of pulse interval, pulse amplitude, pulse area, pulse slope, pulse envelope, and pulse width.
  • the processor 220 may only use frequency domain technology to convert the pulse wave signal into a frequency domain signal, and then perform feature extraction on the frequency domain signal to obtain at least one frequency domain feature value.
  • the frequency domain feature value includes at least one of a spectrum feature and a power spectrum feature.
  • the processor 220 may also perform feature extraction on the pulse wave signal using only nonlinear dynamics technology to obtain at least one nonlinear dynamics feature value.
  • the nonlinear dynamics characteristic value includes entropy or complexity.
  • the processor 220 obtains the characteristic value representing the fluctuation rhythm of the pulse wave according to the pulse wave signal, and further includes: the processor 220 performs characteristic extraction on the pulse wave signal for a period of time or several cycles to obtain at least Two characteristic values; the analyzing the characteristic values to obtain regularity evaluation information includes: analyzing the at least two characteristic values by a statistical analysis method and/or a machine learning method to obtain the regularity evaluation information .
  • the processor 220 analyzes the at least two characteristic values through a statistical analysis method to obtain statistical analysis data, and obtains the regularity evaluation information according to the statistical analysis data; and/or through machine learning In the method, the at least two characteristic values are used as input to obtain the output of the regularity evaluation information.
  • the processor 220 adopts at least one analysis technology of time domain technology, frequency domain technology and nonlinear dynamics technology to perform feature extraction on the pulse wave signal to obtain the corresponding at least one feature value, and may further include:
  • the processor 220 uses at least one analysis technology of time domain technology, frequency domain technology, and nonlinear dynamics technology to perform feature extraction on the pulse wave signal to obtain at least two types of feature values. According to the two types of feature values and each The weight of the class eigenvalues yields at least one final eigenvalue.
  • the at least two different characteristic values include at least two characteristic values analyzed by different analysis techniques and/or at least two different characteristic values analyzed by the same analysis technique.
  • the processor 220 is also used to convert the extracted characteristic value into an intermediate characteristic value after acquiring the characteristic value representing the fluctuation rhythm of the pulse wave according to the pulse wave signal.
  • the processor 220 analyzing the characteristic value to obtain regularity evaluation information includes: the processor 220 performs analysis based on the intermediate characteristic value to obtain the regularity evaluation information.
  • the intermediate feature value includes a pulse rate value
  • the processor 220 converting the extracted feature value into an intermediate feature value includes: the processor 220 converts the extracted feature value into a pulse rate value.
  • the processor 220 is further configured to perform analysis based on the pulse rate value to obtain regularity evaluation information.
  • the intermediate characteristic value may also include a pulse sound characteristic value
  • the processor 220 is specifically configured to convert the extracted characteristic value into a pulse sound characteristic value, and analyze based on the pulse sound characteristic value to obtain a regularity evaluation information.
  • the processor 220 converting the extracted characteristic value into a pulse sound characteristic value includes: the processor 220 determines the arrival time of the peak or trough of the pulse according to the extracted characteristic value, and proceeding at the arrival time of the peak or trough Wave crest or trough mark; generate pulse sound characteristic value based on wave crest or trough mark.
  • the processor 220 analyzes based on the pulse sound characteristic value to obtain regularity evaluation information, which may further include: the processor 220 marks the peaks or troughs of the pulse wave signal within a period of time or several cycles Obtain at least two wave peaks or trough marks, and obtain at least two pulse sound feature values generated by at least two wave crests or at least two trough marks; and compare the at least two pulse sound features by means of statistical analysis and/or machine learning. Value is analyzed to obtain the regularity evaluation information.
  • the monitoring device 200 further includes a memory 230, a display screen 240, an indicator light 250, a speaker 260, and a vibrator 270.
  • the processor 220 is further configured to output prompt information according to the regularity evaluation information. Specifically, the processor 220 controls to output prompt information on the display screen 240 according to the regularity evaluation information.
  • the content of the prompt information output according to the regularity evaluation information is the same as the content of the same part of the monitoring device in the embodiment shown in FIG. 16. For details, refer to the related description of FIG. 16.
  • the prompt information includes at least one of pulse wave related information, executable function related information, and the regularity evaluation information;
  • the type of regularity evaluation information includes an evaluation result used to indicate regular or irregular pulse beats and/or heart rhythms
  • the pulse wave-related information includes pulse wave waveforms and/or rhythm quantification parameter values
  • the executable function is a function that can be executed in the next step when the regularity evaluation information meets the preset condition.
  • the rhythm quantification parameter value includes at least one characteristic value including pulse interval, pulse amplitude, pulse area, pulse slope, pulse envelope, and pulse width, and/or at least includes the highest value statistically analyzed according to at least one characteristic value, Statistical analysis data including one of ratio, sum, integral, difference, mean, standard deviation, maximum interval, minimum interval, pulse variability, number of variations, maximum pulse rate, and minimum pulse rate, and/ Or at least one threshold including the threshold of the degree of variability and the threshold of the number of mutations.
  • the regularity evaluation information is displayed in at least one of the following forms: text, pattern, and light.
  • the type of the regularity evaluation information includes a pulse and/or heart rhythm used to indicate regular or irregular, and the processor 220 controls to output alarm information when the regularity evaluation information is irregular.
  • the content of the output alarm information is also the same as the related content in the related embodiment of the monitoring device 200 shown in FIG. 16. For details, reference may be made to the related description of the monitoring device 200 shown in FIG. 16.
  • the presentation form of the alarm information includes at least one of text, pattern, light, sound, and vibration.
  • the processor 220 may control the display screen 240 to display the text and/or pattern.
  • the processor 220 may control the display screen 240 to display the text and/or pattern.
  • the processor 220 The display screen or the indicator light 250 can be controlled to display corresponding light, for example, the entire screen or a specific area of the display screen can be controlled to display colors such as red, or the indicator light 250 can be controlled to emit red light.
  • the indicator light 250 may specifically be an indicator light including a red LED light, a green LED light, and a blue LED light.
  • the processor 220 may generate or mix colors by controlling the lighting of different colors and/or numbers of LED lights. The corresponding color light.
  • the processor 220 may control the speaker 260 to output sound.
  • the processor 220 may control the vibrator 270 to generate vibration.
  • the processor 220 when the regularity evaluation information is irregular, the processor 220 also determines the alarm gear according to the acquired characteristic value, and controls the output of the alarm information of the corresponding alarm gear, wherein the alarm The gears include at least two gears.
  • the processor 220 compares the acquired characteristic value with multiple reference values, determines the characteristic value interval in which the characteristic value is located, and according to the determined characteristic value interval and the corresponding relationship between the characteristic value interval and the alarm gear, Determine the corresponding alarm gear.
  • the processor 220 determines that the corresponding alarm gear is the first alarm gear when the slope is greater than or equal to the first slope and less than the second slope, And control to emit a green light or an audible alarm message with a smaller decibel; when the slope is greater than or equal to the second slope and less than the third slope, the processor 220 determines that the corresponding alarm gear is the second alarm gear, and controls to emit orange Light or medium-decibel sound alarm information; when the slope is greater than or equal to the third slope, the processor 220 determines that the corresponding alarm gear is the third alarm gear, and controls to emit a red light or the highest-decibel sound alarm information.
  • the first slope is smaller than the second slope, and the second slope is smaller than the third slope.
  • the first alarm gear is smaller than the second alarm gear
  • the second alarm gear is smaller than the third alarm gear
  • the number of the alarm gears can be any suitable value such as 2, 3, 4, etc.
  • the correspondence relationship between the characteristic value interval and the alarm gear position may be a correspondence relationship table, a correspondence relationship curve, etc., pre-stored in the memory 230.
  • the monitoring device 200 further includes a communication unit 280, which is used to establish communication with a monitoring management device 300 such as department-level workstation equipment and/or hospital-level data center/hospital-level emergency center management equipment. connection.
  • a monitoring management device 300 such as department-level workstation equipment and/or hospital-level data center/hospital-level emergency center management equipment. connection.
  • the communication unit 280 can also be used to communicate with the bedside monitoring device 202 and department-level workstation equipment and/or hospital-level data center/hospital-level emergency center management equipment and other monitoring management equipment 300 Establish a communication connection.
  • the communication unit 280 includes at least one of a Bluetooth module, a WMTS communication module, an NFC communication module, a WIFI communication module, and a mobile communication network module such as 2G/3G/4G/5G.
  • the processor 220 is further configured to send the prompt information to the department-level workstation equipment and/or the hospital-level data center/hospital-level emergency center management equipment and other monitoring and management equipment 300 through the communication unit 280, through the department-level workstation equipment And/or the hospital-level data center/hospital-level emergency center management equipment outputs the prompt information.
  • the processor 220 is further configured to send the periodic physiological signals to department-level workstation equipment and/or hospital-level data center/hospital-level emergency center management equipment through the communication unit 280, through the department-level workstation
  • the equipment and/or hospital-level data center/hospital-level emergency center management equipment performs “extracting the pulse wave signal related to the measurement object from the periodic physiological signal”, “obtaining the characteristic pulse wave signal from the pulse wave signal”
  • the regularity evaluation information is obtained by processing operations such as "the characteristic value of the fluctuation rhythm" and "analyzing the characteristic value to obtain the regularity evaluation information”.
  • the processor 220 is further configured to receive regularity evaluation information from department-level workstation equipment and/or hospital-level data center/hospital-level emergency center management equipment through the communication unit 280, and according to the received The regularity evaluation information outputs prompt information.
  • the processor 220 may send the periodic physiological signals to the bedside monitoring device 202, department-level workstation equipment and/or hospital-level data center/hospital. Level emergency center management equipment, etc., through the bedside monitoring equipment 202, department-level workstation equipment and/or hospital-level data center/hospital-level emergency center management equipment, etc., to obtain regular evaluation information; and the processor 220 also Regularity evaluation information can be received from the bedside monitoring equipment 202, department-level workstation equipment, and/or hospital-level data center/hospital-level emergency center management equipment, and output prompt information according to the received regularity evaluation information.
  • the prompt information may also be determined by department-level workstation equipment and/or hospital-level data center/hospital-level emergency center management equipment, and then sent to the monitoring device 200 for display output.
  • the processor 220 may directly receive prompt information from department-level workstation equipment and/or hospital-level data center/hospital-level emergency center management equipment through the communication unit 280.
  • the memory 230 also prestores the ratio interval or the correspondence relationship between the difference interval and the filter, and the ratio is the aforementioned rhythm quantization parameter value and the For the ratio of other physiological sign parameter values, three filters are used as an example.
  • the processor 220 is also specifically used to determine the value of the rhythm quantization parameter and other physiological sign parameter values in terms of filter selection.
  • the ratio or difference of is less than the first preset ratio or difference; if it is less than the first preset ratio or difference, select the first filter for filtering, if it is greater than or equal to the first preset ratio or difference, continue Determine whether the ratio or difference is less than a second preset ratio or difference, where the second preset ratio or difference is greater than the first preset ratio or difference; if the ratio or difference is less than For the second preset ratio or difference, the second filter is selected for filtering, and if it is greater than or equal to the second preset ratio or difference, the third filter is selected for filtering.
  • the filter 290 including the first filter, the second filter, and the third filter when the ratio or difference between the rhythm quantization parameter value and the other physiological parameter value is smaller than the first
  • the first filter is selected for filtering.
  • the ratio or difference between the rhythm quantization parameter value and other physiological parameter values is greater than or equal to the first preset ratio or difference and less than the second preset ratio or
  • the second filter is selected for filtering, and when the ratio or difference between the rhythm quantization parameter value and the other physiological parameter values is greater than the second preset ratio or difference, the third filter is selected for filtering.
  • the filter parameter may be determined according to the ratio interval or the difference interval at the same time as the filter, that is, after the processor 220 determines the filter according to the ratio interval or the difference interval, it may also be determined according to the ratio interval or the difference interval. Determine the corresponding filter parameters, that is, different ratio intervals or difference intervals can also correspond to different filter parameters.
  • the processor 220 obtains regularity evaluation information according to the pulse wave signal and the other physiological sign signals, specifically including: the processor 220 extracts physiological sign parameters from the other physiological sign signals Value, according to the pulse wave signal to obtain a characteristic value that characterizes the rhythm of the pulse wave, analyze the characteristic value to obtain first regularity evaluation information, and analyze the physiological sign parameter value to obtain second regularity evaluation information, and The first regularity evaluation information and the second regularity evaluation information are described to obtain the final regularity evaluation information.
  • the at least one second sensor 212 may be an ECG sensor, the other physiological sign signal is an ECG signal, the physiological sign parameter value is an ECG parameter value, and the processor 220 is based on the first
  • the final regularity evaluation information is obtained from the regularity evaluation information and the second regularity evaluation information, including: the processor 220 selects any one of them when the first regularity evaluation information and the second regularity evaluation information are consistent. One is the final regularity evaluation information; and when the first regularity evaluation information is inconsistent with the second regularity evaluation information, the second regularity evaluation information is selected as the final regularity evaluation information.
  • the processor 220 is further configured to use the characteristic value obtained according to the analysis of the first regularity evaluation information as the input of the machine learning model and use the final regularity evaluation information as the machine learning model.
  • the output of the model is bound to each other to further improve the machine learning model.
  • the at least one second sensor 212 includes an ECG sensor, which can directly detect ECG signals and obtain regularity evaluation information, while the first sensor 211 is detected by non-ECG sensors.
  • the regularity evaluation information obtained by the analysis of the pulse wave signal is verified, and the regularity evaluation information obtained based on the ECG signal is used as the final regularity evaluation information, so as to train and improve the machine learning model, and improve the The accuracy of the regularity evaluation information obtained from the pulse wave signal detected by the electrical sensor.
  • the ECG sensor and the non-ECG sensor can be used for detection at the same time in the first several times, and in the subsequent period, the non-ECG sensor can be used for periodic physiology. Signal detection and regular evaluation information based only on signals obtained by non-ECG sensors can still ensure the accuracy of the evaluation.
  • the memory 230 also stores program instructions, and the program instructions are used by the processor 220 to execute the steps in the analysis methods in FIGS. 12, 13, and 14.
  • monitoring device 200 for a more specific structure and functions performed by the monitoring device 200, reference may be made to the related description of the monitoring device 200 in FIG. 16, and may also refer to the related descriptions of FIGS. 2, 11, and 12-14, which will not be repeated here.
  • the multi-parameter monitor or module assembly at least includes a parameter measurement circuit 112.
  • the parameter measurement circuit 112 includes at least one parameter measurement circuit corresponding to a physiological parameter.
  • the parameter measurement circuit includes at least an ECG signal parameter measurement circuit, a respiratory parameter measurement circuit, a body temperature parameter measurement circuit, a blood oxygen parameter measurement circuit, a noninvasive blood pressure parameter measurement circuit, and a At least one parameter measurement circuit in the blood pressure parameter measurement circuit, etc., each parameter measurement circuit is respectively connected to the externally inserted sensor accessory 111 through a corresponding sensor interface.
  • the sensor accessory 111 includes detection accessories corresponding to the detection of physiological parameters such as blood oxygen, blood pressure, and body temperature.
  • the parameter measurement circuit 112 is mainly used to connect the sensor attachment 111 to obtain the collected physiological parameter signals, and may include at least two or more physiological parameter measurement circuits.
  • the parameter measurement circuit may be, but is not limited to, a physiological parameter measurement circuit (module).
  • Physiological parameter measurement circuit (module) or sensor collects human physiological parameters, etc.
  • the parameter measurement circuit obtains the external physiological parameter sensor attachment to obtain the physiological sampling signal of the patient through the extended interface, and obtains the physiological data after processing for alarm and display.
  • the extended interface can also be used to output the control signal on how to collect the physiological parameters output by the main control circuit to the external physiological parameter monitoring accessory through the corresponding interface to realize the monitoring and control of the patient's physiological parameters.
  • the parameter measurement circuit 112 may be a circuit for processing sensor signals; the sensor accessories 111 are sensor accessories including the aforementioned sensor 210, the first sensor 211, and at least one second sensor 212.
  • the sensor accessory 111 is an external sensor accessory that can be inserted through a sensor interface.
  • the multi-parameter monitor or module component may also include a main control circuit 113.
  • the main control circuit 113 needs to include at least one processor 1131 and at least one memory 1132.
  • the main control circuit may also include a power management module 1133, a power IP module, and an interface. At least one of the conversion circuit, etc.
  • the processor 1131 may be the aforementioned processor 220, and the memory 1132 may be the aforementioned processor 270.
  • the power management module 1133 is used to control the power on and off of the whole machine, the power-on sequence of each power domain inside the board, and battery charging and discharging.
  • the power IP module refers to associating the schematic diagram of the power circuit unit that is frequently called repeatedly with the PCB layout, and solidifying it into a separate power module, that is, converting an input voltage into an output voltage through a predetermined circuit, where the input voltage and The output voltage is different. For example, the voltage of 15V is converted to 1.8V, 3.3V or 3.8V. It is understandable that the power IP module can be single-channel or multi-channel. When the power IP module is a single channel, the power IP module can convert an input voltage into an output voltage.
  • the power IP module can convert one input voltage into multiple output voltages, and the voltage values of the multiple output voltages can be the same or different, so as to meet the differences of multiple electronic components at the same time Voltage demand, and the module has few external interfaces, it works in the system as a black box decoupling from the external hardware system, which improves the reliability of the entire power supply system.
  • the interface conversion circuit is used to convert the signal output by the main control minimum system module (that is, at least one processor and at least one memory in the main control circuit) into an input standard signal required by the actual external device, for example, to support an external VGA display
  • the function is to convert the RGB digital signal output by the main control CPU into a VGA analog signal, support the external network function, and convert the RMII signal into a standard network differential signal.
  • the multi-parameter monitor or module assembly may also include one or more of the local display 114, the alarm circuit 116, the input interface circuit 117, and the external communication and power interface 115.
  • the main control circuit is used to coordinate and control the boards, circuits and devices in the multi-parameter monitor or module assembly.
  • the main control circuit is used to control the data interaction between the parameter measurement circuit 112 and the communication interface circuit, as well as the transmission of control signals, and transmit the physiological data to the display 114 for display, or it can receive data from the touch screen or
  • the user control instructions input by physical input interface circuits such as keyboards and keys can also output control signals on how to collect physiological parameters.
  • the alarm circuit 116 may be an acousto-optic alarm circuit and a vibration alarm circuit, and may include the aforementioned indicator light 250, speaker 250, and vibrator 270.
  • the main control circuit completes the calculation of physiological parameters, and can send the calculation results and waveforms of the parameters to the host (such as a host with a display, PC, central station, etc.) through the external communication and power interface 115, and the external communication and power interface 115 It can be one or a combination of Ethernet, Token Ring, Token Bus, and the fiber distribution data interface (FDDI) of the backbone network of these three networks.
  • FDDI fiber distribution data interface
  • the host can be any computer equipment such as the host of the monitor, an electrocardiograph, an ultrasonic diagnostic apparatus, a computer, etc., and a monitoring device can be formed by installing matching software.
  • the host can also be a communication device, such as a mobile phone, a multi-parameter monitor, or a module component that sends data to a mobile phone that supports Bluetooth communication through a Bluetooth interface to realize remote data transmission.
  • the local display 114 is the display 240
  • the input interface circuit 117 can be a touch panel integrated with the display 240 to form a touch display.
  • the external communication and power interface 115 can be the aforementioned Communication unit 280.
  • the local display 114 is the display screen 240
  • the input interface circuit 117 can be a touch panel integrated with the display screen 240
  • the external communication and power interface 115 can be the aforementioned communication unit 280.
  • the multi-parameter monitoring module component can be set outside the monitor shell, as an independent external plug-in parameter module, which can be inserted into the host (including the main control board) of the monitor to form a plug-in monitor as a part of the monitor, or also It can be connected to the monitor's host (including the main control board) through a cable, and the external parameter module is used as an external accessory of the monitor.
  • the parameter processing can also be built in the shell, integrated with the main control module, or physically separated and set in the shell to form an integrated monitor.
  • the memory 230 may include a high-speed random access memory, and may also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), and a secure digital (Secure Digital, SD) card, flash card, multiple disk storage devices, flash memory devices, or other volatile solid-state storage devices.
  • a non-volatile memory such as a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), and a secure digital (Secure Digital, SD) card, flash card, multiple disk storage devices, flash memory devices, or other volatile solid-state storage devices.
  • the processor 220 is a central processing unit (Central Processing Unit, CPU), and may also be other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), on-site Field-Programmable Gate Array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc.
  • the general-purpose processor may be a microprocessor or the processor may also be any conventional processor or the like.
  • the principles herein can be reflected in a computer program product on a computer-readable storage medium, which is pre-installed with computer-readable program code.
  • a computer-readable storage medium Any tangible, non-transitory computer-readable storage medium can be used, including magnetic storage devices (hard disks, floppy disks, etc.), optical storage devices (CD-ROM, DVD, Blu Ray disks, etc.), flash memory and/or the like .
  • These computer program instructions can be loaded on a general-purpose computer, a special-purpose computer, or other programmable data processing equipment to form a machine, so that these instructions executed on the computer or other programmable data processing device can generate a device that realizes the specified function.
  • Computer program instructions can also be stored in a computer-readable memory, which can instruct a computer or other programmable data processing equipment to operate in a specific manner, so that the instructions stored in the computer-readable memory can form a piece of Manufactured products, including realization devices that realize specified functions.
  • Computer program instructions can also be loaded on a computer or other programmable data processing equipment, thereby executing a series of operation steps on the computer or other programmable equipment to produce a computer-implemented process, so that the execution on the computer or other programmable equipment Instructions can provide steps for implementing specified functions.
  • Coupled refers to physical connection, electrical connection, magnetic connection, optical connection, communication connection, functional connection and/or any other connection.

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  • Cardiology (AREA)
  • Physics & Mathematics (AREA)
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  • Measuring Pulse, Heart Rate, Blood Pressure Or Blood Flow (AREA)

Abstract

La présente invention concerne un procédé d'analyse d'informations d'évaluation de régularité. Le procédé consiste à : acquérir, au moyen d'un capteur, un signal physiologique périodique d'un objet de mesure, le capteur étant un capteur non cardiographique ; extraire, à partir du signal physiologique périodique, un signal à onde pulsée associé à l'objet de mesure ; acquérir, en fonction du signal à onde pulsée, une valeur caractéristique représentant le rythme de fluctuation de l'onde pulsée ; et analyser la valeur caractéristique pour obtenir des informations d'évaluation de régularité. La présente invention concerne en outre un dispositif de surveillance et un système de surveillance. Dans la présente invention, un dispositif de surveillance peut être utilisé pour déterminer avec précision la régularité du rythme cardiaque au moyen d'une technologie non ECG.
PCT/CN2019/098456 2019-07-30 2019-07-30 Procédé d'analyse d'informations d'évaluation de régularité, dispositif de surveillance et système de surveillance WO2021016892A1 (fr)

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CN201980098034.XA CN114040705A (zh) 2019-07-30 2019-07-30 规则性评价信息的分析方法、监护设备及监护系统
PCT/CN2019/098456 WO2021016892A1 (fr) 2019-07-30 2019-07-30 Procédé d'analyse d'informations d'évaluation de régularité, dispositif de surveillance et système de surveillance

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