CN112294281A - Prompting method of regularity evaluation information, monitoring equipment and monitoring system - Google Patents
Prompting method of regularity evaluation information, monitoring equipment and monitoring system Download PDFInfo
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Abstract
The application provides a method for prompting regularity evaluation information, which comprises the following steps: radiating light of different wavelengths into a tissue region of a measurement object, detecting an optical signal transmitted through the tissue region, and extracting a photoplethysmographic signal generated by light absorption of the tissue region from the optical signal; processing the photoplethysmography signals to extract a pulse wave waveform; acquiring a characteristic value representing the fluctuation rhythm of the pulse wave according to the pulse wave waveform; identifying the fluctuation rhythm of the pulse wave according to the characteristic value to obtain regularity evaluation information; and outputting prompt information according to the regularity evaluation information. The application also provides a monitoring device and a monitoring system. The method and the device can still accurately judge the regularity of the heart rhythm when the monitoring device is not provided with the ECG technology.
Description
Technical Field
The application relates to the field of medical instruments, in particular to a prompting method of regularity evaluation information, a monitoring device and a monitoring system.
Background
Cardiac rhythmicity is monitored by an ECG (electrocardiogram) technique to identify irregular rhythms of the heart. However, the ECG technique requires more ECG electrode pads and needs to be attached to a specific part of a human body, the process is complicated, and the current ward-round monitoring device or the monitoring device of department is not equipped with the ECG technique, so that the medical staff can only judge whether the heart rhythm of the patient is regular by the traditional pulse-taking mode. However, the process depends on the pulse taking position and time controlled by personal technical ability and the screening result is obtained, and the accuracy is difficult to guarantee.
Disclosure of Invention
In view of this, the present application provides a method for prompting regularity evaluation information, a monitoring device and a monitoring system, which can accurately determine the regularity of a cardiac rhythm when the monitoring device is not equipped with an ECG technique.
The embodiment of the application discloses a method for prompting regularity evaluation information, which comprises the following steps: radiating light of different wavelengths into a tissue region of a measurement object, detecting an optical signal transmitted through the tissue region, and extracting a photoplethysmographic signal generated by light absorption of the tissue region from the optical signal; processing the photoplethysmography signals to extract a pulse wave waveform; acquiring a characteristic value representing the fluctuation rhythm of the pulse wave according to the pulse wave waveform; identifying the fluctuation rhythm of the pulse wave according to the characteristic value to obtain regularity evaluation information; and outputting prompt information according to the regularity evaluation information.
The embodiment of the application also discloses a method for prompting the regularity evaluation information, which comprises the following steps: acquiring a sensor signal through a sensor connected with a measuring object, wherein the sensor is a non-electrocardio sensor; extracting a pulse wave signal of the measurement object from the sensor signal; processing the pulse wave signal to extract a pulse wave waveform; acquiring a characteristic value representing the fluctuation rhythm of the pulse wave according to the pulse wave waveform; identifying the fluctuation rhythm of the pulse wave according to the characteristic value to obtain regularity evaluation information; and outputting prompt information according to the regularity evaluation information.
The embodiment of the application also discloses a monitoring device, which comprises a blood oxygen sensor and a processor. The blood oxygen sensor is used for radiating light with different wavelengths into a tissue area of a measuring object and detecting a light signal transmitted through the tissue area; the processor is connected with the blood oxygen sensor and used for extracting photoplethysmography signals generated by light absorption of the tissue area from the light signals, processing the photoplethysmography signals to extract pulse wave waveforms, acquiring characteristic values representing pulse wave fluctuation rhythms according to the pulse wave waveforms, identifying the pulse wave fluctuation rhythms according to the characteristic values to acquire regularity evaluation information, and controlling and outputting prompt information according to the regularity evaluation information.
The embodiment of the application also discloses monitoring equipment, which comprises a sensor and a processor. The sensor is connected with a measuring object to obtain a sensor signal, wherein the sensor is a non-electrocardio sensor. The processor is used for extracting the pulse wave signal of the measuring object from the sensor signal; processing the pulse wave signal to extract a pulse wave waveform; acquiring a characteristic value representing the fluctuation rhythm of the pulse wave according to the pulse wave waveform; identifying the fluctuation rhythm of the pulse wave according to the characteristic value to obtain regularity evaluation information; and outputting prompt information according to the regularity evaluation information.
A monitoring system includes a monitoring device including a blood oxygen sensor and a processor. The blood oxygen sensor is used for radiating light with different wavelengths into a tissue area of a measuring object and detecting a light signal transmitted through the tissue area; the processor is connected with the blood oxygen sensor and used for extracting photoplethysmography signals generated by light absorption of the tissue area from the light signals, processing the photoplethysmography signals to extract pulse wave waveforms, acquiring characteristic values representing pulse wave fluctuation rhythms according to the pulse wave waveforms, identifying the pulse wave fluctuation rhythms according to the characteristic values to acquire regularity evaluation information, and controlling and outputting prompt information according to the regularity evaluation information. Alternatively, the monitoring device comprises a sensor and a processor. The sensor is connected with a measuring object to obtain a sensor signal, wherein the sensor is a non-electrocardio sensor. The processor is used for extracting the pulse wave signal of the measuring object from the sensor signal; processing the pulse wave signal to extract a pulse wave waveform; acquiring a characteristic value representing the fluctuation rhythm of the pulse wave according to the pulse wave waveform; identifying the fluctuation rhythm of the pulse wave according to the characteristic value to obtain regularity evaluation information; and outputting prompt information according to the regularity evaluation information.
A computer-readable storage medium having stored therein program instructions for executing a method for prompting a rule evaluation information after being called by a computer. The prompting method comprises the following steps: radiating light of different wavelengths into a tissue region of a measurement object, detecting an optical signal transmitted through the tissue region, and extracting a photoplethysmographic signal generated by light absorption of the tissue region from the optical signal; processing the photoplethysmography signals to extract a pulse wave waveform; acquiring a characteristic value representing the fluctuation rhythm of the pulse wave according to the pulse wave waveform; identifying the fluctuation rhythm of the pulse wave according to the characteristic value to obtain regularity evaluation information; and outputting prompt information according to the regularity evaluation information. Or, the prompting method includes: acquiring a sensor signal through a sensor connected with a measuring object, wherein the sensor is a non-electrocardio sensor; extracting a pulse wave signal of the measurement object from the sensor signal; processing the pulse wave signal to extract a pulse wave waveform; acquiring a characteristic value representing the fluctuation rhythm of the pulse wave according to the pulse wave waveform; identifying the fluctuation rhythm of the pulse wave according to the characteristic value to obtain regularity evaluation information; and outputting prompt information according to the regularity evaluation information.
In the application, the pulse wave signals are acquired through the blood oxygen sensor and the like, the information which is the fluctuation rhythm of the pulse waves and is related to the heart beat rhythm is identified based on the pulse wave signals, the regularity evaluation information is obtained and prompted, and when the monitoring equipment is not provided with an ECG (electrocardiogram) technology, the regularity evaluation information can still be accurately obtained and prompted.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a schematic diagram of a monitoring system for use in a hospital according to an embodiment of the present application.
Fig. 2 is a flowchart of a method for prompting regularity evaluation information in an embodiment of the present application.
Fig. 3 is a schematic diagram illustrating display of a prompt message according to an embodiment of the present application.
Fig. 4 is a schematic diagram illustrating display of a prompt message in another embodiment of the present application.
Fig. 5 is a schematic diagram illustrating a display of a prompt message according to still another embodiment of the present application.
Fig. 6 is a schematic diagram illustrating display of prompt information in another embodiment of the present application.
Fig. 7 is a schematic diagram illustrating display of prompt information in another embodiment of the present application.
Fig. 8 is a schematic diagram illustrating display of prompt information in another embodiment of the present application.
Fig. 9 is a schematic view of an interface displaying prompt information in an embodiment of the present application.
Fig. 10 is a schematic view of an interface displaying prompt information in another embodiment of the present application.
Fig. 11 is a flowchart of a method for prompting regularity evaluation information in another embodiment of the present application.
Fig. 12 is a block diagram of a monitoring device according to an embodiment of the present application.
Fig. 13 is a block diagram of a monitoring device according to another embodiment of the present application.
FIG. 14 is a system block diagram of a multi-parameter monitor or module assembly.
Detailed Description
Reference is made herein to various exemplary embodiments. However, those skilled in the art will recognize that changes and modifications may be made to the exemplary embodiments without departing from the scope hereof. For example, the various operational steps, as well as the components used to perform the operational steps, may be implemented in differing ways depending upon the particular application or consideration of any number of cost functions associated with operation of the system (e.g., one or more steps may be deleted, modified or incorporated into other steps).
The terms "first," "second," and the like in the description and claims of the present invention and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, or apparatus.
Referring to fig. 1, a schematic diagram of a monitoring system 100 used in a hospital is shown, in which the monitoring system 100 is utilized to store data monitored by a wearable monitor or a bedside monitor as a whole, and centrally manage patient information and nursing information, and the patient information and the nursing information are stored in association with each other, so as to facilitate storage of historical data and associated alarm. In the monitoring system 100 shown in fig. 1, the monitoring system 100 comprises at least one monitoring device 200 and at least one monitoring management device 300. The at least one monitoring device 200 may comprise one of a mobile monitoring device and a bedside monitoring device for directly monitoring a measurement subject, such as a patient. The at least one monitoring management device 300 includes at least one of a department-level workstation device and a hospital-level data center/hospital-level emergency center management device.
As shown in fig. 1, the at least one monitoring device 200 may comprise a mobile monitoring device 201 and a bedside monitor 202. The portable monitoring device 200 is a wearable monitoring apparatus.
Wherein one bedside monitor 202 may be provided for each patient bed, the bedside monitor 202 may be a multi-parameter monitor or a plug-in monitor. In addition, each bedside monitor 202 can also be paired with one mobile monitoring device 201 for transmission, the mobile monitoring device 201 provides a simple and portable multi-parameter monitor or module assembly, the portable multi-parameter monitor or module assembly can be worn on the body of a patient to perform mobile monitoring corresponding to the patient, and after the mobile monitoring device 201 and the bedside monitors 202 are in wired or wireless communication, patient state data generated by the mobile monitoring can be transmitted to the bedside monitors 202 for display. As shown in fig. 1, the monitoring management device 300 may include a department-level workstation device 301 and an institution-level data center/first aid center management device 302, and the patient status data generated by the mobile monitoring device 201 is transmitted to the department-level workstation device 301 for a doctor or a nurse to view, or transmitted to the institution-level data center/first aid center management device 302 for storage and/or display through the bedside monitor 202.
In addition, the mobile monitoring device 201 can also directly transmit the patient state data generated by mobile monitoring to the department-level workstation device 301 through the wireless network node N1 arranged in the hospital for storage and display, or transmit the patient state data generated by mobile monitoring to the hospital-level data center/hospital-level emergency center management device 302 through the wireless network node N1 arranged in the hospital for storage. The data corresponding to the patient status parameter displayed on the bedside monitor 202 may originate from a sensor accessory directly connected to the bedside monitor 202, or originate from the mobile monitoring device 201, or originate from the department-level workstation device 301, the institution-level data center, or the institution-level emergency center management device 302.
Each mobile monitoring device 201 may also store patient status data collected by itself, the bedside monitor 202 may also store patient status data collected by sensor accessories connected to the bedside monitor, and patient status data received from the mobile monitoring device 201, the department-level workstation device 301, the hospital-level data center/hospital-level emergency center management device 302, and the like. The department-level workstation 301 and the hospital-level data center/hospital-level emergency center management 302 may store patient status data sent by any of the mobile monitoring devices 201.
Please refer to fig. 2, which is a flowchart illustrating a method for prompting regularity evaluation information according to an embodiment of the present application. The prompting method of the present application can be applied to the monitoring system 100 or the monitoring device 200, for example, as described above. Wherein, in the present embodiment, the monitoring device 200 is equipped with a blood oxygen sensor. As shown in fig. 2, the method for prompting the regularity evaluation information includes the following steps:
light of different wavelengths is radiated into a tissue region of a measurement object, an optical signal transmitted through the tissue region is detected, and a photoplethysmographic signal generated by light absorption of the tissue region is extracted from the optical signal (S21).
Specifically, in step S21, light with different wavelengths is radiated to the tissue region of the measurement subject by the blood oxygen sensor, and the optical signal transmitted/reflected by the tissue region is detected, and then the processor of the monitoring device 200 extracts the photoplethysmography signal generated by the light absorption of the tissue region from the optical signal.
Processing the photoplethysmographic pulse wave signal to extract a pulse wave waveform (S22).
In some embodiments, the step S22 includes: and carrying out filtering processing, amplification processing and A/D conversion (digital-to-analog conversion) processing on the photoplethysmography signals to extract pulse wave waveforms. The pulse wave waveforms include at least one single pulse wave waveform.
And acquiring a characteristic value representing the fluctuation rhythm of the pulse wave according to the pulse wave waveform (S23).
The fluctuation rhythm of the pulse wave is identified from the feature values to obtain regularity evaluation information (S24).
And outputting prompt information according to the regularity evaluation information (S25).
It should be understood that outputting the prompt message includes displaying the prompt message, or outputting the prompt message by sound, voice, light, etc., as long as it outputs the prompt message for prompting, and is not limited herein.
Therefore, in the present application, the blood oxygen sensor acquires the pulse wave signal, and identifies the information related to the heart beat rhythm, i.e., the fluctuation rhythm of the pulse wave based on the pulse wave signal, to obtain the regularity evaluation information and prompt the regularity evaluation information, so that the regularity evaluation information can be accurately obtained and prompted when the monitoring device 200 is not equipped with the ECG technology.
Wherein, the monitoring device 200 further includes a display screen, and the prompt information at least includes one of the following:
the regularity evaluation information displayed in a first display area of the display screen;
displaying pulse wave related information in a second display area of the display screen;
and displaying related information of executable functions in a third display area of the display screen, wherein the executable functions are functions which can be executed in the next step when the regularity evaluation information meets preset conditions.
Wherein the regularity evaluation information may include regular or irregular evaluation results.
The step S25 "outputting prompt information according to the regularity evaluation information" may include: and displaying corresponding prompt information according to whether the regularity evaluation information is regular or irregular.
Referring to fig. 3, a schematic diagram of a prompt message in an embodiment is shown in fig. 3, where the prompt message may only include regularity evaluation information P1 of "suspected irregular pulse", and at this time, 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 function interface or a system interface of the monitoring device 200. When the first display area is a certain area of the current interface, the prompt message can be displayed on the current interface in a pop-up window mode. When the first display area a1 is the entire display area of the display screen, the prompt message may be displayed in a prompt interface after switching from the current interface to the prompt interface. It should be understood that the display manner of the regularity evaluation information P1 may further include other words such as "irregular pulse", "irregularity", "pulse abnormality", "irregular pulse interval", and the like, as long as it can prompt that the measurement object has irregular pulse or may have irregular pulse, and the expression form of the words is not limited.
Obviously, when the regularity evaluation information is a rule, the prompt information may be "regular pulse", "rule", "normal", and the like, which can prompt that the current pulse of the measurement object is normal.
When the prompt information comprises the regularity evaluation information, the user can directly see the result of the intelligent analysis of the equipment, the operation is convenient and visual, and the user can conveniently execute follow-up examination, such as appointment electrocardiographic examination, ultrasonic examination and the like.
Referring to fig. 4, a schematic diagram of displaying a prompt message in another embodiment is shown, as shown in fig. 4, the prompt message may only include the pulse wave related information P2 displayed in the second display area a 2. Similarly, the second display area a2 may be the entire display area of the display screen or a certain area in the current interface displayed by the display screen. When the second display area a2 is a certain area of the current interface, the prompt message can be displayed on the current interface in a pop-up window manner. When the second display area a2 is the entire display area of the display screen, the prompt message may be displayed in a prompt interface after switching from the current interface to the prompt interface.
When the prompt information includes the pulse wave related information P2, a waveform reference may be provided to the user for the user to confirm the regularity evaluation information.
Referring to fig. 5, a schematic diagram of displaying a prompt message in a further embodiment is shown in fig. 5, where the prompt message may further 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 and the second display area a2 where the pulse wave-related information P2 is located are adjacently disposed. It is to be understood that the first display area a1 and the second display area a2 may not be adjacent to each other, and may be disposed arbitrarily. In the embodiment, the adjacent arrangement of the first display area a1 and the second display area a2 can facilitate the user to visually check the regularity evaluation information and judge the specific reason of the occurrence regularity evaluation information of the measurement object according to the pulse wave related information in combination with the pulse wave related information.
Referring to fig. 6, a schematic diagram of displaying prompt information in another embodiment is shown, as shown in fig. 6, 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 function-executable related information P3 displayed in the third display area A3. The display of the related information P3 of executable function can play a role of prompting and guiding the related operation to be executed next, so as to facilitate the user to learn and execute the operation to be executed next.
Specifically, as shown in fig. 6, when the regularity evaluation information P1 indicates irregular pulse evaluation and/or irregular cardiac rhythm evaluation results such as "irregular pulse", "irregular", "pulse abnormality", "abnormal", "irregular pulse interval", "irregular pulse rate", "suspected irregularity", "suspected atrial fibrillation", "suspected cardiac rhythm irregularity", and the like, the function-executable related information P3 includes: at least one of "print" (e.g., print pulse wave waveform), "reserve ECG", "reserve ultrasound", and may also include other functions, such as user-defined common functions.
Wherein the first display region a1, the second display region a2, and the third display region A3 are sequentially disposed adjacent to A3. Obviously, in other embodiments, the first display region a1, the third display region A3, and the second display region a2 may be arranged adjacent to each other in sequence, and the sequence may be arbitrarily adjusted as long as it is ensured that a plurality of regions are arranged adjacent to each other. As described above, the first display region a1, the second display region a2, and the third display region A3 may not be adjacent to each other, and may be a plurality of non-adjacent regions.
Thus, in the present application, when there are at least two display areas, the at least two display areas are adjacently located on the display screen. It is to be understood that the at least two display areas are adjacently disposed on the display screen for the convenience of the user to view the regularity evaluation information, the pulse wave-related information, and the information related to the executable function. In other embodiments of the present invention, the display regions may not be adjacently disposed.
The pulse wave-related information includes a pulse wave waveform and/or a rhythm quantization parameter value.
It should be understood that, in the present application, the pulse wave waveform may include at least a pulse wave waveform when the regularity evaluation information indicates an irregular evaluation result, a pulse wave waveform when the regularity evaluation information indicates a regular evaluation result, and a pulse wave waveform form obtained in real time during the acquisition of the periodic physiological signal of the measurement object by the sensor. Furthermore, the pulse wave shape may include a waveform shape within a period of time, or may be a continuously generated pulse wave shape, for example, when the pulse wave shape is a continuously generated pulse wave shape, it may include an irregular pulse wave shape within a period of time at least on a certain segment of the pulse wave shape.
In some embodiments, after or before the step of "acquiring a characteristic value characterizing a wave rhythm of a pulse wave from the pulse wave signal", the method further includes: evaluating the quality of the pulse wave signal to obtain a quality factor; and determining whether to adopt or discard the currently obtained pulse wave signal according to the quality factor. It is understood that the quality factor may be a characteristic obtained during the analysis processing of the periodic physiological signal or the pulse wave signal according to the steps S22 or S23.
In addition, the quality factor is obtained by evaluating the quality of the pulse wave signal, for example, in a step including "described above; and determining whether to adopt or discard the currently obtained pulse wave signal according to the quality factor, the pulse wave waveform may include at least a pulse wave waveform corresponding to a time when the pulse wave signal quality is good, or a pulse wave waveform corresponding to a time when the pulse wave signal quality is not good. That is, whether the quality factor finally determines to discard the currently obtained pulse wave signal or not, the corresponding pulse wave waveform may be output or not output and displayed. Specifically, when the pulse wave signal quality is good, the corresponding pulse wave waveform may include a segment of an irregular pulse wave waveform, and may also include a segment of a regular pulse wave waveform. In one embodiment, when the pulse wave signal quality is good, the corresponding pulse wave waveform may include an irregular pulse wave waveform over a period of time.
The rhythm quantization parameter value may include at least one of a characteristic value, statistical analysis data of the characteristic value, and a preset threshold value. Wherein the characteristic value may include at least one of a frequency domain characteristic, a nonlinear dynamics characteristic, a pulse frequency related quantity, and a waveform morphology characteristic value; the statistical analysis data of the eigenvalues may include at least one of frequency domain statistical analysis data, nonlinear dynamics characteristic statistics, pulse frequency related quantity statistics, waveform morphology eigenvalue statistics, and variation related quantity; the preset threshold comprises a threshold corresponding to the characteristic value and/or the statistical analysis data of the characteristic value.
The frequency domain features include at least one of spectral features and power spectral features, and the frequency domain statistical analysis data includes at least one of spectral feature statistics and power spectral feature statistics. The spectrum characteristics may include: one of the characteristic information of a spectrum peak, a spectrum interval, a spectrum amplitude, a spectrum area, a spectrum slope, a spectrum envelope and the like, wherein the spectrum peak comprises the spectrum peak amplitude and refers to the height of the spectrum peak; the spectrum peak comprises a spectrum peak position, which refers to a frequency position corresponding to the spectrum peak; the spectral peaks may also include a number of spectral peaks, which refers to the number of spectral peaks within a band in the 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 a frequency band, the spectrum slope refers to the slope of any ascending segment or descending segment in the spectrum, and the spectrum envelope refers to the envelope formed by the connection between the spectrum peaks. The frequency spectrum feature statistics comprise one of single-frequency spectrum feature statistics, multi-frequency spectrum feature statistics and the like, wherein the single-frequency spectrum feature statistics comprise: within a single spectrum, the most value, mean value, ratio, difference, sum, integral, standard deviation, distribution statistics, etc. of these features such as different spectral peak amplitudes, spectral peak positions, spectral intervals, spectral amplitudes, spectral areas, spectral slopes, etc., and the statistical analysis values of the spectral feature statistics, such as the mean of the spectral interval differences, the standard deviation of the spectral interval differences, etc. The multi-spectral feature statistics include: the maximum value, the mean value, the ratio, the difference value, the summation, the integral, the standard deviation, the distribution statistics and the like of the characteristics such as the spectral peak amplitude, the spectral peak number, the spectral peak position, the spectral interval, the spectral amplitude, the spectral area, the spectral slope and the like of the spectra correspond to different periods in a period of time, and the statistical analysis value of the spectral characteristic statistics, such as the standard deviation of the maximum spectral peak position difference value between the spectra, the number of the maximum spectral peak position difference value between the spectra exceeding a preset value and the like. The power spectrum features may include: one of characteristic information of a power spectrum peak, a power spectrum interval, a power spectrum amplitude, a power spectrum area, a power spectrum slope, a power spectrum envelope and the like, wherein the power spectrum peak comprises the power spectrum peak amplitude which refers to the height of the power spectrum peak; the power spectrum peak comprises a power spectrum peak position which refers to a frequency position corresponding to the power spectrum peak; the power spectrum peaks may also include the number of power spectrum peaks, which refers to the number of power spectrum peaks in a frequency band in the power spectrum. 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 a frequency band, the power spectrum slope refers to the slope of any ascending segment or descending segment in the power spectrum, and the power spectrum envelope refers to the envelope formed by the connection of power spectrum peaks. The power spectrum feature statistics comprise one of single power spectrum feature statistics, multi-power spectrum feature statistics and the like, wherein the single power spectrum feature statistics comprise: within a single power spectrum, the maximum value, the mean value, the ratio, the difference value, the sum, the integral, the standard deviation, the distribution statistics, and the like of the features such as the peak amplitude, the peak position, the power spectrum interval, the power spectrum amplitude, the power spectrum area, the power spectrum slope, and the like of different power spectrums, and the statistical analysis value of the power spectrum feature statistics, such as the mean value, the standard deviation, and the like of the power spectrum interval difference value. The multi-power spectral feature statistics include: the maximum value, the mean value, the ratio, the difference value, the summation, the integral, the standard deviation, the distribution statistics and the like of the characteristics such as the peak amplitude of the power spectrum, the number of the peaks of the power spectrum, the peak position of the power spectrum, the interval of the power spectrum, the amplitude of the power spectrum, the area of the power spectrum, the slope of the power spectrum and the like, and the statistical analysis value of the characteristic statistics of the power spectrum, such as the standard deviation of the peak position difference value of the maximum power spectrum among the power spectrums, the number of the peak position difference value of the maximum power spectrum among the power spectrums exceeding a preset value and the like, are.
The nonlinear dynamics characteristics include at least: entropy value and complexity, the entropy value including but not limited to entropy value characteristics such as information entropy, spectral entropy, approximate entropy, sample entropy, fuzzy entropy, etc. The nonlinear dynamical feature statistics comprise statistical analysis data of nonlinear dynamical feature values.
The pulse frequency related quantity comprises a pulse rate, the pulse frequency related quantity statistic comprises a statistically analyzed quantity of the pulse rate, e.g. the statistically analyzed quantity of the pulse rate comprises a maximum pulse rate value and/or a minimum pulse rate value. Maximum/minimum pulse rate definition: in a signal with N pulse waves, N-1 pulse rates can be calculated according to the interval of adjacent pulse waves in a period of time, wherein the maximum value and the minimum value of the pulse rates are defined as the maximum pulse rate and the minimum pulse rate.
The waveform morphology feature value at least includes one of pulse interval, pulse amplitude, pulse area, pulse slope, pulse envelope, pulse width, etc. The pulse interval refers to a time interval between two single pulses, and may be a time interval between a peak and a peak, a valley and a valley, or a time interval between any corresponding points on the two single pulses. The spaces may or may not be contiguous. The single pulse in this context may be a pulse wave, or a single pulse acquired by applying other forms. The pulse amplitude refers to the difference between the peak and the trough. The pulse slope is the slope at any one of the rising and falling segments of the pulse wave. Pulse area refers to the integral over time of the pulse wave between two adjacent troughs or between the start and the end of a single pulse. The pulse envelope is: the envelope formed by the connection of the peaks and the peaks (or the valleys and the valleys). Pulse width refers to the length of time from the beginning to the end of a single pulse.
The waveform morphology feature value statistical analysis data is a result of analyzing the waveform morphology feature value for a period of time based on a statistical analysis method, and may at least include a pulse interval difference value, a pulse amplitude difference value, a pulse slope difference value, a pulse area difference value, a pulse envelope difference value, a pulse width difference value, a pulse interval mean value, a pulse amplitude mean value, a pulse slope mean value, a pulse area mean value, a pulse envelope mean value, a pulse width mean value, a pulse interval standard deviation, a pulse amplitude standard deviation, a pulse wave slope standard deviation, a pulse area standard deviation, a pulse envelope standard deviation, a pulse interval sum, a pulse amplitude sum, a pulse slope sum, a pulse area sum, a pulse envelope sum, a pulse width sum, and a pulse interval ratio value, The pulse width ratio, the pulse slope ratio, the pulse area ratio, the pulse envelope ratio, the pulse width ratio, the mean of the pulse interval differences, the mean of the pulse width differences, the mean of the pulse slope differences, the mean of the pulse area differences, the mean of the pulse envelope differences, the mean of the pulse width differences, the integral of the pulse interval differences, the integral of the pulse amplitude differences, the integral of the pulse slope differences, the integral of the pulse area differences, the integral of the pulse envelope differences, the integral of the pulse width differences, the maximum pulse rate value, the minimum pulse rate value and the like. The mean value of the pulse intervals refers to the mean value of the pulse intervals in a period of time. The difference in pulse intervals refers to the difference between pulse intervals. The mean of the pulse interval differences refers to the mean of the pulse interval differences over a period of time. The integration of the pulse interval difference is an integration value obtained by integrating the pulse interval difference in a time period. The sum of the pulse intervals refers to the sum of the pulse intervals. The ratio of pulse intervals refers to the ratio of different pulse intervals. The standard deviation of the pulse intervals refers to the standard deviation of the pulse intervals over a period of time. The difference of the pulse widths refers to the difference of the pulse widths. The mean value of the pulse width is the average value of the pulse width over a period of time. The difference in pulse width refers to the difference between pulse widths. The mean value of the pulse width difference values refers to the mean value of the pulse width difference values over a period of time. The integral of the pulse width difference value is an integral value obtained by integrating the pulse width difference value in a time period. The standard deviation of pulse width refers to the standard deviation of pulse width over a period of time. The sum of the pulse widths refers to the sum of the pulse widths. The ratio of pulse widths refers to the ratio between different pulse widths. The difference in pulse amplitude refers to the difference between pulse amplitudes. The mean value of the pulse amplitudes refers to the mean value of the pulse amplitudes over a period of time. The standard deviation of pulse amplitude refers to the standard deviation of pulse amplitude over a period of time. The sum of the pulse amplitudes refers to the sum of the pulse amplitudes added over a period of time. The ratio of the pulse amplitudes refers to the ratio between different pulse amplitudes. The mean value of the pulse amplitude difference values refers to the mean value of the pulse amplitude difference values in a period of time. The integral of the pulse amplitude difference value is an integral value obtained by integrating the pulse amplitude difference value in a time period. The difference in pulse slope refers to the difference between the pulse slopes. The mean value of the pulse slope refers to the mean value of the pulse slope over a period of time. The standard deviation of the pulse slope refers to the standard deviation of the pulse slope over a period of time. The summation of the pulse slopes refers to the summation of the pulse slopes over a period of time. The ratio of the pulse slopes refers to the ratio between different pulse slopes. The mean of the pulse slope differences refers to the mean of the pulse slope differences over a period of time. The integral of the pulse slope difference is an integral value obtained by integrating the pulse slope difference in a time period. The difference value of the pulse areas refers to the difference value between the pulse areas, the mean value of the pulse areas refers to the mean value between the pulse areas in a period of time, and the standard deviation of the pulse areas refers to the standard deviation of the pulse areas in a period of time. The sum of the pulse areas refers to the sum of the pulse areas over a period of time. The ratio of the pulse areas refers to the ratio of different pulse areas. The mean of the pulse area difference values refers to the mean of the pulse area difference values over a period of time. The integral of the pulse area difference value is an integral value obtained by integrating the pulse area difference value in a time period.
The variation-related quantity is a measure reflecting a change of at least one of the waveform morphology feature value, the pulse wave frequency-related quantity, the frequency domain feature, the nonlinear dynamics feature, the frequency domain feature statistic, the nonlinear dynamics feature statistic, the pulse frequency-related quantity statistic, and the waveform morphology feature value statistic, and for example, the variation-related quantity includes at least one of a variation degree and a variation frequency.
The variation degree is used for representing the variation degree of the signal characteristic information of the pulse wave relative to the statistical analysis result of the pulse wave signal characteristic information in a period of time, wherein the signal characteristic information at least comprises one of a waveform form characteristic value, a pulse wave frequency related quantity, a frequency domain characteristic, a nonlinear dynamics characteristic, a frequency domain characteristic statistic, a nonlinear dynamics characteristic statistic, a pulse frequency related quantity statistic, a waveform form characteristic value statistic and the like. In one embodiment, the variability may be one of a waveform shape feature value, a pulse wave frequency related quantity, a frequency domain feature, and a nonlinear dynamics feature, and the variability is a difference between the waveform shape feature value analyzed data over a period of time, a statistic of the pulse wave frequency related quantity over a period of time, a statistic of the frequency domain feature over a period of time, and a statistic of the nonlinear dynamics feature over a period of time. The difference degree can be obtained by difference calculation, quotient calculation, combination operation of difference calculation and quotient calculation, and the like. The statistical analysis method mentioned herein includes one of mathematical statistical methods such as mean calculation, difference calculation, standard deviation calculation, etc. Specifically, in one embodiment, the variance may refer to a variance of a pulse wave with respect to a pulse wave of an arbitrary period of time, and specifically, the variance may refer to a variance of a current pulse wave with respect to a pulse wave of a period of time, such as a variance of a pulse interval. Taking the variation degree of the pulse intervals as an example, if the current pulse wave is the seventh pulse wave, there are six pulse intervals, the difference between at least one of the six pulse intervals and the mean value of any number of the six pulse intervals is calculated, and the ratio of the difference to the mean value is taken as the variation degree of the pulse intervals. It is understood that, in other embodiments, the aforementioned variance refers to a variance of the current pulse wave from the previous pulse wave, for example, if the current pulse wave is the seventh pulse wave, the current pulse wave has six pulse intervals, the difference between the sixth pulse interval and the mean of the previous five pulse intervals is calculated, and the ratio of the difference and the mean of the previous five pulse intervals is taken as the variance of the pulse intervals.
The number of variations may be a number of variations of the pulse wave occurring within a certain period of time, for example, a number of times that a waveform shape feature value, a pulse wave frequency-related quantity, a frequency domain feature, a nonlinear dynamics feature, a frequency domain feature statistic, a nonlinear dynamics feature statistic, a pulse frequency-related quantity statistic, or a waveform shape feature value statistic exceeds a predetermined value within a certain period of time. Specifically, the variation frequency may be a frequency at which the difference between the pulse intervals exceeds a predetermined value, or a frequency at which one of the pulse wave signal characteristic information, such as the pulse interval, the mean of the pulse interval differences, the standard deviation of the pulse intervals, the difference between the pulse amplitudes, the mean of the pulse amplitudes, the standard deviation of the pulse amplitudes, the difference between the pulse slopes, the mean of the pulse slopes, the standard deviation of the pulse slopes, the difference between the pulse areas, the mean of the pulse areas, the standard deviation of the pulse areas, the pulse rate value, the maximum pulse rate value, and the minimum pulse rate value, exceeds a predetermined value within a period of time.
The rhythm quantization parameter value may further include a threshold corresponding to the aforementioned characteristic value and/or statistical analysis data of the aforementioned characteristic value, for example, the rhythm quantization parameter value further includes at least one of a variance threshold and a variance number threshold.
Correspondingly, in some embodiments, the regularity evaluation information P1 may be given based on a comparison between the identified rhythm quantization parameter value and a corresponding preset threshold, for example, the regularity evaluation information P1 may be given based on a comparison between the aforementioned degree of variation and a corresponding threshold, a comparison between the aforementioned number of variations and a corresponding threshold, or a comparison between the aforementioned degree of variation and a corresponding threshold in combination, so as to determine whether the pulse wave is regular or not, or give a suggestion that the pulse wave is regular or not according to the comparison result. In some embodiments, a comparison with a threshold value may be made depending on one of the aforementioned rhythm quantization parameter values identified, thereby giving regularity evaluation information P1; alternatively, it is also possible to perform a plurality of pieces of combination judgment based on comparison between the recognized characteristic information of two or more (including two) of the aforementioned rhythm quantization parameter values with the corresponding threshold values, respectively, thereby giving the regularity evaluation information P1. Next, in some embodiments, at least one of the pieces of characteristic information in the identified rhythm quantization parameter values is compared with a preset threshold value a plurality of times in succession, and when the results of the plurality of comparisons satisfy a criterion of a pulse wave rule or a pulse wave irregularity, an evaluation result regarding the pulse wave rule or the pulse wave irregularity is given, thereby obtaining the regularity evaluation information P1, or a suggestion of whether the aforementioned pulse wave rule or not is given. Next, in some embodiments, at least one feature information of the identified rhythm quantization parameter values is compared with a preset threshold value a plurality of times in succession over a period of time, and when a ratio of the number of times of characterizing the pulse wave regularity in the comparison results satisfies a pulse wave regularity criterion, regularity evaluation information P1 is outputted, and when a ratio of the number of times of characterizing the pulse wave irregularity in the comparison results satisfies a pulse wave irregularity criterion, regularity evaluation information P1 is outputted.
Specifically, in some embodiments, the pulse wave related information includes the pulse wave waveform displayed in the first sub-display area and/or the rhythm quantization parameter value displayed in the second sub-display area.
Referring to fig. 7, fig. 7 is a schematic view illustrating display of 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. Specifically, each vital sign data item region respectively displays that the measurement parameter of the non-invasive blood pressure NIBP is 120/80(mmHg), the measurement parameter of the blood oxygen SPO2 is 98 (%), the measurement parameter of the pulse is 64(BPM), the measurement parameter of the body temperature is 102.5(F), and the measurement parameter of the respiration is 20 BPM. As shown in fig. 7, the first display region P1 and the second display region P2 are not adjacent. In this embodiment, the display screen further includes a touch area T for retracting or expanding the second display area P2 to correspondingly hide or display the pulse wave related information a 2. Referring to fig. 8, in fig. 8, the regularity evaluation information a1 is displayed only in the first display area P1, so that the user can pay attention to the regularity evaluation information a1, and the second display area P2 is closed, so that the pulse wave related information a2 is hidden. The arrangement enables a user to select to view or hide the pulse wave related information according to actual needs, and when the pulse wave related information is hidden, the interface of the display screen is neat and attractive; when the user regularity evaluation information a1 suggests "irregularity" or the user needs to view the pulse wave related information a2 for other reasons, the second display area P2 may be expanded for viewing by clicking the touch area T.
The prompt information including at least one of the regularity evaluation information, the pulse wave related information and the executable function related information prompt information can be displayed on a current interface in a pop-up window mode, or can be displayed in the prompt interface after the current interface is switched to the prompt interface.
Wherein, in some embodiments, the regularity evaluation information is displayed by at least one of the following forms: text, pattern, light.
In some embodiments, when the prompt message is a pop-up window display and includes at least two of the regularity evaluation message, the pulse wave related message, and the related message prompt message of the executable function, at least two of the regularity evaluation message, the pulse wave related message, and the related message prompt message 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 region a1, the second display region a2, and the third display region A3 may be located in the same window or may be located in different windows.
For example, as shown in fig. 3, the regularity evaluation information may include both characters and patterns: suspected irregular pulse
". Obviously, an indicator light may be further provided on the display screen, and the regularity evaluation information may be indicated by light emitted from the indicator light, for example, "irregular" is indicated when red light is emitted, and "regular" is indicated when green light is emitted.
As shown in fig. 4 to 6, the second display area a2 further includes a first sub-display area a21, and the pulse wave-related information includes the pulse wave waveform displayed in the first sub-display area and/or the rhythm quantization parameter value displayed in the second sub-display area a 22. The pulse wave waveform is extracted by processing the photoplethysmographic pulse wave signal in step S22. By displaying the pulse wave waveform, the pulse condition of the pulse can be visually displayed.
As shown in fig. 4 to 6, the second display region a2 includes a second sub display region a22, and the rhythm quantization parameter values displayed in the second sub display region a22 include at least one of: the pulse rate measurement method comprises a characteristic value, statistical analysis data of the characteristic value and a preset threshold, wherein the statistical analysis data comprises at least one of difference, mean, standard deviation, summation, ratio, integral, maximum interval period, minimum interval period, pulse variation degree, variation times, maximum pulse rate value and minimum pulse rate value of the characteristic value. Wherein, the maximum pulse rate value and the minimum pulse rate value refer to the maximum value and the minimum value in N-1 pulse rates calculated according to the interval of adjacent pulse waves in a signal with N pulse waves in a period of time. The characteristic values include: 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 further include a characteristic value representing a fluctuation rhythm of the pulse wave directly obtained from the pulse wave waveform, and/or statistical analysis data obtained by performing statistical analysis on the characteristic values. The preset threshold includes a threshold corresponding to the feature value and/or the statistical analysis data of the feature value, for example, at least one of a variance threshold and a variance number threshold.
As shown in fig. 4 to 6, the first sub-display area a21 and the second sub-display area a22 are adjacently disposed. The specific positional relationship between the first sub-display region a21 and the second sub-display region a22 is not limited, for example, as shown in fig. 4, the second sub-display region a22 is above, or as shown in fig. 5-6, the first sub-display region a21 is above.
In some embodiments, the information related to the executable function includes guide information of the executable function and/or a function icon of the executable function.
The guidance 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, and the guidance information may be a text or a pattern, and is used to guide the user to know the executable function of the monitoring device 200 and how to trigger the executable functions.
As shown in fig. 6, the information related to the executable function may also directly include function icons B1 of executable functions, so that each function icon B1 of executable function is displayed in a more direct manner for a user to operate to trigger the corresponding executable function.
Therefore, the prompting method may further include: and responding to the triggering operation of the function icon B1, and controlling the execution of the function corresponding to the function icon B1.
As shown in fig. 6, the executable function includes at least one of printing a pulse wave waveform, reserving an ECG exam, reserving an ultrasound exam, and may also include other functions such as a user-defined general function. Accordingly, the function icon B1 may include at least one function icon including a print function icon of a pulse wave waveform, a reserved ECG examination function icon, and a reserved ultrasound examination function icon.
In some embodiments, the step S23 "obtaining a feature value characterizing a pulse wave fluctuation rhythm from the pulse wave waveform" includes: and performing feature extraction on the pulse wave signal by adopting at least one analysis technology of a time domain technology, a frequency domain technology and a nonlinear dynamics technology to obtain at least one feature value.
In some embodiments, the step S24 "identifying the fluctuation rhythm of the pulse wave according to the feature value to obtain the regularity evaluation information" includes: and comparing the at least one characteristic value with a corresponding preset threshold value to obtain regular or irregular regularity evaluation information.
As mentioned above, the characteristic value may include at least one of pulse interval, pulse magnitude, pulse area, pulse slope, pulse envelope, and pulse width. For example, the at least one feature value may be one feature value of pulse intervals, the preset threshold may be a preset pulse interval range, and the "comparing the at least one feature value with the corresponding preset threshold to obtain regular or irregular regularity evaluation information" may further include: and comparing the pulse interval with a preset pulse interval range, obtaining irregular regularity evaluation information when the pulse interval is determined to be out of the preset pulse interval range, and obtaining regular regularity evaluation information when the pulse interval is determined to be in the preset pulse interval range.
That is, in some embodiments, regular or irregular regularity evaluation information may be acquired directly from a characteristic value that characterizes the rhythm of fluctuation of a pulse wave acquired from the pulse wave waveform.
In other embodiments, the step S23 "obtaining a feature value representing a pulse wave fluctuation rhythm according to the pulse wave waveform" includes: extracting the characteristics of the pulse wave signals within a period of time or a plurality of periods to obtain at least one characteristic value; analyzing the at least one characteristic value through a machine learning method to obtain the regularity evaluation information; and/or analyzing the at least two characteristic values by a statistical analysis method and/or a machine learning method to obtain the regularity evaluation information.
Wherein, the feature extraction of the pulse wave signals in a period of time or a plurality of periods to obtain at least one feature value may also be: at least one analysis technology of a time domain technology, a frequency domain technology and a nonlinear dynamics technology is adopted to extract the characteristics of the pulse wave signals in a period or a plurality of periods to obtain at least one characteristic value.
Wherein the "analyzing the at least two feature values by 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 by a statistical analysis method to obtain statistical analysis data, and obtaining the regularity evaluation information according to the statistical analysis data; and/or deriving the output of the regularity evaluation information by using the at least two characteristic values as input through a machine learning method.
Wherein the statistical analysis data may be at least one of the difference, mean, standard deviation, sum, ratio, integral, maximum interval period, minimum interval period, pulse variability, variation frequency threshold, maximum pulse rate value, and minimum pulse rate value, and the regularity evaluation information is obtained according to the statistical analysis data, the method may include comparing the statistical analysis data such as the difference, the mean, the standard deviation, the sum, the ratio, the integral, the maximum interval period, the minimum interval period, the pulse variability, the variation frequency, the maximum pulse rate value, and the minimum pulse rate value with preset statistical data such as a preset difference, a preset mean, a preset standard deviation, a preset sum, a preset ratio, an integral, a preset maximum interval period, a preset minimum interval period, a preset variation threshold, a preset variation frequency threshold, a preset maximum pulse rate value, and a preset minimum pulse rate value, to obtain the regular or irregular regularity evaluation information.
In some embodiments, the regularity evaluation information may be given based on a comparison between the identified rhythm quantization parameter value and a corresponding preset threshold, for example, the pulse rhythm regularity evaluation information may be given based on a comparison between the aforementioned degree of variation and a corresponding threshold, a comparison between the aforementioned number of variations and a corresponding threshold, or a comparison between the aforementioned degree of variation and the aforementioned number of variations and a corresponding threshold, respectively, and the pulse wave may be determined to be regular or irregular. In some embodiments, a comparison with a threshold value may be made in accordance with one of the identified aforementioned rhythm quantization parameter values, thereby giving regularity evaluation information; or, it can compare more than two (including two) characteristic values in the identified rhythm quantization parameter values with corresponding threshold values respectively, and make multiple-piece combined judgment, thereby giving evaluation information of pulse rhythm regularity. Secondly, in some embodiments, at least one characteristic value of the identified rhythm quantization parameter values is compared with a preset threshold value a plurality of times in succession, and when the comparison results of the plurality of times all satisfy the criterion of pulse wave rule or pulse wave irregularity, an evaluation result about the pulse wave rule or pulse wave irregularity is given, thereby obtaining regularity evaluation information. In addition, in other embodiments, at least one characteristic value of the identified rhythm quantization parameter values is compared with a preset threshold value a plurality of times in succession over a period of time, when the number of times of representing the pulse wave regularity in the comparison results satisfies the pulse wave regularity criterion, an evaluation result of the pulse wave regularity is output, and when the number of times of representing the pulse wave irregularity in the comparison results satisfies the pulse wave irregularity criterion, an evaluation result of the pulse wave irregularity is output.
Specifically, in some embodiments, the statistical analysis data is pulse variability and/or variability times based on the aforementioned characteristic values. The obtaining of the regularity evaluation information according to the statistical analysis data includes:
and comparing the variation degree and/or the variation times with preset statistical data of preset variation degree and/or variation times to obtain the regularity evaluation information. For example, for the pulse wave signals collected over a period of time, the variability and/or the variability times of the pulse wave signals may be counted continuously for multiple times, and the variability and/or the variability times obtained by each counting are respectively compared with preset statistical data of preset variability and/or variability times, a threshold of the preset continuous statistical times is N times, and if the comparison result is that the variability and/or the variability times of the continuously counted pulse wave signals greater than or equal to N times exceed the preset statistical data of the preset variability and/or variability times, the regularity evaluation information of the pulse wave signals is determined to be pulse irregularity. For another example, in other embodiments, the variability and/or the variability times of the pulse wave signals within any period of time are counted for a plurality of times, and the variability and/or the variability times obtained by each counting are compared with preset statistical data of preset variability and/or variability times, the number of times that the statistical variability and/or the variability times of the pulse wave signals exceed the preset statistical data of the variability and/or the variability times is recorded as N1 times, the result of the N1-time statistics may be determined that the regularity evaluation information of the pulse wave signals is pulse irregularity, a preset percentage X, when the ratio of N1 in the total statistical times is greater than or equal to X, the final determination result is determined as pulse irregularity, otherwise, the final determination result is determined as pulse regularity.
In other embodiments, the regular or irregular regularity evaluation information may be obtained after statistical analysis is performed on the characteristic value representing the pulse wave fluctuation rhythm obtained from the pulse wave waveform to obtain statistical analysis data.
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 one feature value may be used as an input of the machine learning model to automatically derive an output of the regularity evaluation information which is regular or irregular.
The variation degree is used for representing the variation degree of the signal characteristic information of the pulse wave relative to the statistical analysis result of the pulse wave signal characteristic information in a period of time, wherein the signal characteristic information at least comprises one of a waveform form characteristic value, waveform form characteristic value statistical analysis data, a pulse wave frequency related quantity, a frequency domain characteristic, a nonlinear dynamics characteristic and the like. In one embodiment, the variability may be one of a waveform shape feature value, a pulse wave frequency related quantity, a frequency domain feature, and a nonlinear dynamics feature, and the variability is a difference between the analyzed data, a statistic of the pulse wave frequency related quantity over time, a statistic of the frequency domain feature over time, and a statistic of the nonlinear dynamics feature over time. The difference degree can be obtained by difference calculation, quotient calculation, combination operation of difference calculation and quotient calculation, and the like. The statistical analysis method mentioned herein includes one of mathematical statistical methods such as mean calculation, difference calculation, standard deviation calculation, etc. Specifically, in one embodiment, the variance may refer to a variance of a pulse wave with respect to a pulse wave of an arbitrary period of time, and specifically, the variance may refer to a variance of a current pulse wave with respect to a pulse wave of a period of time, such as a variance of a pulse interval. Taking the variation degree of the pulse intervals as an example, if the current pulse wave is the seventh pulse wave, there are six pulse intervals, the difference between at least one of the six pulse intervals and the mean value of any number of the six pulse intervals is calculated, and the ratio of the difference to the mean value is taken as the variation degree of the pulse intervals.
Specifically, the waveform morphology feature value statistical analysis data refers to a result of analyzing the waveform morphology feature value for a period of time based on a statistical analysis method, and may at least include one of a mean value of pulse intervals, a difference value of pulse intervals, a mean value of pulse interval difference values, a standard deviation of pulse intervals, a difference value of pulse amplitudes, a mean value of pulse amplitudes, a standard deviation of pulse amplitudes, a difference value of pulse slope, a mean value of pulse slope, a standard deviation of pulse slope, a difference value of pulse areas of peaks, a mean value of pulse areas of peaks, and a standard deviation of pulse areas of peaks. Specifically, in one embodiment, the pulse variation degree refers to a variation degree of any one pulse wave with respect to a pulse wave of any period of time, such as a variation degree of a pulse interval. Specifically, in one embodiment, the variance refers to a variance of any one pulse wave with respect to a pulse wave in any period of time, for example, a variance of a pulse interval. Specifically, in one embodiment, the variance refers to a variance of the current pulse wave with respect to the pulse wave in a period of time, for example, if the current pulse wave is the seventh pulse wave, there are six pulse intervals, a difference between at least one of the six pulse intervals and a mean value of any number of the six pulse intervals is calculated, and a ratio of the difference to the mean value is used as the variance of the pulse intervals. It is understood that, in other embodiments, the variance refers to a variance of the current pulse wave from the previous pulse wave, for example, if the current pulse wave is the seventh pulse wave, the current pulse wave has six pulse intervals, the difference between the sixth pulse interval and the mean of the previous five pulse intervals is calculated, and the ratio of the difference and the mean of the previous five pulse intervals is used as the variance of the pulse intervals.
Wherein, the mean value of the pulse intervals refers to the mean value of the pulse intervals in a period of time, the difference value of the pulse intervals refers to the difference value of the pulse intervals, the mean value of the pulse interval difference value in a period of time, the standard deviation of the pulse intervals refers to the standard deviation of the pulse intervals in a period of time, the pulse amplitude refers to the difference value between the wave crest and the wave trough, the mean value of the pulse amplitude refers to the mean value of the 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 pulse slope refers to the pulse slope at any position of the rising section and the falling section of the pulse wave, the difference value of the pulse slope refers to the difference value of the pulse slopes, the mean value of the 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, the pulse area of the wave crest refers to the integral of the pulse waves between two adjacent wave troughs in time, the difference value of the pulse areas of the wave crests refers to the difference value of the pulse areas of the wave crests, the mean value of the pulse areas of the wave crests refers to the mean value of the pulse areas of the wave crests in a period of time, and the standard deviation of the pulse areas of the wave crests refers to the standard deviation of the pulse areas of the wave crests in a period of time.
The variation frequency may be a frequency of occurrence of pulse wave variation within a period of time, for example, a frequency of exceeding a predetermined value of a waveform morphology feature value, a statistical analysis data of the waveform morphology feature value, a pulse wave frequency correlation quantity, a frequency domain feature, and a nonlinear dynamics feature within a period of time. Specifically, the variation frequency is a frequency at which the difference between the pulse intervals exceeds a predetermined value, or a frequency at which one of the pulse wave signal characteristic information such as the pulse interval, the mean of the pulse intervals, the mean of the pulse interval differences, the standard deviation of the pulse intervals, the difference between the pulse amplitudes, the mean of the pulse amplitudes, the standard deviation of the pulse amplitudes, the difference between the pulse slope ratios, the mean of the pulse slope ratios, the standard deviation of the pulse slope ratios, the difference between the pulse areas of the peaks, the mean of the pulse areas of the peaks, the standard deviation of the pulse areas of the peaks, the pulse rate value, the maximum pulse rate value, the minimum pulse rate value, and the like exceeds a predetermined value within a certain period of time. In the present application, the feature values obtained by the time domain technique include, but are not limited to, waveform interval, amplitude, pulse area, pulse slope, envelope, and the like.
The frequency domain technology is to convert the pulse waveform of the time domain into a frequency domain signal through algorithms such as Laplace transform, and the like, and the characteristic values obtained through the frequency domain technology include but are not limited to frequency domain characteristic values such as frequency spectrum peak characteristics, power spectrum characteristics and the like.
The characteristic value obtained through the nonlinear dynamics analysis includes but is not limited to a nonlinear dynamics characteristic value within entropy value characteristics or complexity characteristics of information entropy, spectral entropy, approximate entropy, sample entropy and fuzzy entropy of the pulse wave waveform.
In some embodiments, the "obtaining at least one feature value by performing feature extraction on the pulse wave signal using at least one of a time domain technique, a frequency domain technique, and a non-linear dynamics technique" or the "obtaining at least two feature values by performing feature extraction on the pulse wave signal over a period of time or over several periods using at least one of a time domain technique, a frequency domain technique, and a non-linear dynamics technique" may include: and extracting the features of the pulse wave signals by adopting at least two analysis technologies of a time domain technology, a frequency domain technology and a nonlinear dynamics technology to obtain at least two types of feature values, and obtaining at least one final feature value or at least two final feature values according to the two types of feature values and the weight value of each type of feature value.
For example, after the time domain technique is adopted to perform feature extraction on the pulse wave signals to obtain the time domain feature value and the frequency domain technique is adopted to perform feature extraction on the same segment of pulse wave signals to obtain the frequency domain feature value, the final feature value can be obtained according to the weighting calculation formula ax + by. The method comprises the steps of obtaining a pulse wave signal, obtaining a time domain characteristic value, a frequency domain characteristic value, a weight value of the time domain characteristic value, and b weight value of the frequency domain characteristic value, wherein x can be a time domain characteristic value, y can be a frequency domain characteristic value, a is a weight value of the time domain characteristic value, and b is a weight value of the frequency domain characteristic value, so that the same segment of pulse wave signal is analyzed through multiple analysis technologies, the final characteristic value can be obtained by combining multiple types of characteristic values obtained through the multiple technologies and the weight value of each.
In some embodiments, the method further comprises: and performing combined analysis on the different characteristic values by using the same or different methods to identify the fluctuation rhythm of the pulse wave so as to obtain regularity evaluation information.
Wherein the different feature values include multiple types of feature values analyzed by different analysis techniques (e.g., time domain feature values, frequency domain feature values, etc.) and/or multiple types of different feature values analyzed by the same analysis technique (e.g., pulse interval, pulse slope, etc.).
Wherein the same or different methods include statistical methods, machine learning methods, and the like.
In some embodiments, after the step of obtaining a characteristic value characterizing a pulse wave fluctuation rhythm from the pulse wave waveform, the method further comprises: converting the obtained characteristic value into an intermediate characteristic value; the identifying the fluctuation rhythm of the pulse wave according to the characteristic value to obtain the regularity evaluation information comprises the following steps: and identifying the fluctuation rhythm of the pulse wave based on the intermediate characteristic value to obtain regularity evaluation information.
Wherein, the intermediate characteristic value includes a pulse sound characteristic value, converting the acquired characteristic value into an intermediate characteristic value, including: and converting the acquired characteristic value into a pulse sound characteristic value. The identifying the fluctuation rhythm of the pulse wave based on the intermediate characteristic value to obtain regularity evaluation information includes: and identifying the fluctuation rhythm of the pulse wave based on the pulse sound characteristic value to obtain regularity evaluation information.
In some embodiments, the identifying a fluctuating rhythm of the pulse wave based on the pulse sound characteristic value, resulting in regularity evaluation information, includes: obtaining pulse sound intervals, and judging that the pulse sound intervals are suspected to be irregular when the difference values of a plurality of continuous adjacent intervals exceed a threshold value, or at least N difference values in N adjacent interval difference values exceed the threshold value, or the number (threshold value) of interval average values exceeds or is smaller than one interval, or the standard deviation of the intervals is divided by the interval average values to exceed the threshold value.
Further, the converting the extracted feature value into a pulse sound feature value includes: determining the arrival time of the peak or the trough of the pulse according to the acquired characteristic value, and marking the peak or the trough at the arrival time of the peak or the trough; and generating a pulse sound characteristic value according to the peak mark or the trough mark.
The converting the extracted feature value into an intermediate feature value includes: and converting the extracted characteristic value into a pulse rate value.
The identifying the fluctuation rhythm of the pulse wave based on the intermediate characteristic value to obtain regularity evaluation information includes: and identifying the fluctuation rhythm of the pulse wave based on the pulse rate value to obtain regularity evaluation information.
In some embodiments, the analyzing based on the pulse rate value to obtain regularity evaluation information includes: obtaining the difference value between the pulse rates, and judging that the pulse rate is suspected to be irregular when the difference value between a plurality of continuous adjacent pulse rates exceeds a threshold value, or at least N exceeding threshold values are met in the difference values between the N adjacent pulse rates, or the number of pulse rates exceeding or smaller than the average value of the pulse rates (threshold value) exists, or the standard deviation of the pulse rates is divided by the average value of the pulse rates to exceed the threshold value.
As previously mentioned, the type of regularity evaluation information includes regular or irregular, and in some embodiments, the method further includes: and when the regularity evaluation information is irregular, outputting alarm information.
Wherein, the display form of the alarm information comprises at least one of characters, patterns, light, sound and vibration.
Wherein the text and the pattern can be output through a display screen of the monitoring device 200, the light can be output through a display screen or an indicator light of the monitoring device 200, the sound can be output through a speaker of the monitoring device 200, and the vibration can be generated through a vibrator of the monitoring device 200.
In some embodiments, when the regularity evaluation information is irregular, outputting alarm information includes: and determining an alarm gear according to the acquired characteristic value, and controlling to output alarm information of the corresponding alarm gear, wherein the alarm gear comprises at least two gears.
In some embodiments, the alert information includes at least a portion of the alert information, where a display area of the alert information is at least partially the same as a display area of the alert information. In some embodiments, when the alarm information alarms through the display screen, the alarm information is prompt information, and at the moment, the display area of the alarm information is the display area of the prompt information.
Specifically, the determining an alarm gear according to the acquired feature value may include: and comparing the acquired characteristic value with a plurality of reference values, determining a characteristic value interval in which the characteristic value is positioned, and determining a corresponding alarm gear according to the determined characteristic value interval and the corresponding relation between the characteristic value interval and the alarm gear.
For example, when the acquired characteristic value is a pulse slope in the time domain characteristic value, and when the pulse slope is greater than or equal to a first pulse slope and smaller than a second pulse slope, determining that the corresponding alarm gear is a first alarm gear, and controlling to send out green light or sound alarm information with smaller decibel; when the pulse slope is greater than or equal to the second pulse slope and smaller than the third pulse slope, determining the corresponding alarm gear as a second alarm gear, and controlling to send out orange light or medium decibel sound alarm information; and when the pulse slope is larger than or equal to a third pulse slope, determining the corresponding alarm gear as a third alarm gear, and controlling to send out red light or sound alarm information with the highest decibel.
Wherein, the first pulse slope is smaller than the second pulse slope, and the second pulse slope is smaller than the third pulse slope. The first alarm gear is smaller than the second alarm gear, and 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 and the like.
The corresponding relation between the characteristic value interval and the alarm gear can be a pre-stored corresponding relation table, a corresponding relation curve and the like.
In some embodiments, the method further comprises the steps of: and responding to the result change operation or confirmation operation input by the user, and changing or confirming the regular or irregular regularity evaluation information.
Please refer to fig. 9, which is a schematic interface diagram showing prompt information in an embodiment. In this embodiment, operation information for the user to determine may be given in the popup. As shown in fig. 9, the prompt information may be displayed in a pop-up manner on an interface, the prompt information includes a detailed information area Z1 and a determination area Z2, the detailed information area Z1 displays detailed information for the user to determine whether the user is regular, the determination area Z2 includes "regular" and "irregular" options for the user to select to obtain the regularity evaluation information, and the regularity evaluation information may be determined to be regular in response to a selection operation of the "regular" option, or may be determined to be irregular in response to a selection operation of the "irregular" option. Wherein the detailed information includes: pulse wave waveform (pleth area in the figure), pulse mark, pulse interval measurement value, maximum interval period, minimum interval period, pulse variation degree, variation frequency, variation threshold, variation frequency threshold, maximum pulse rate value, minimum pulse rate value and other information. In some embodiments of the invention, the content of the detailed information is completely non-overlapping with the content of the toast, the detailed information giving more information than the toast. It will be appreciated that in other embodiments of the invention, the content contained in the detailed information may also be partially or completely identical to the content contained in the reminder information.
The interface can be a monitoring result interface, a system interface and the like.
Please refer to fig. 10, which is a schematic diagram of an interface displaying prompt information in another embodiment. As shown in fig. 10, the prompt message includes a "regular" or "irregular" selection box displayed on an interface of the monitoring device 200. The options of "regular" and "irregular" are used for the user to select to confirm or change the regularity evaluation information.
That is, as shown in fig. 10, the current regularity evaluation information is prompted by the currently selected "rule" selection box S1 and "irregularity" selection box S2, and the regularity evaluation information may be changed in response to the user' S selection of the "rule" selection box S1 or the "irregularity" selection box S2.
In another embodiment, the entire interface may be a prompt information interface.
As shown in fig. 10, the prompt message further includes an interface providing operation interface for the user to call out detailed information to assist the user in determining, where the detailed information includes: pulse wave waveform (pleth area in the figure), pulse identification, pulse interval measurement value, maximum pulse interval, minimum pulse interval, pulse interval variation degree and other information. The interface provides an operation interface which may be the touch area T shown in fig. 7 to 8.
In some embodiments, the monitoring device 200 further comprises at least one other sensor, which is other than an ecg sensor or an oximetry sensor.
While "radiating light of different wavelengths into a tissue region of a measurement object, detecting an optical signal transmitted through the tissue region" in step S21 is performed, the method further includes: and acquiring other physiological sign signals of the human body through at least one other sensor.
The step S22 "processing the photoplethysmographic signal to extract a pulse wave waveform", includes: and extracting a pulse wave waveform according to the photoplethysmography signal and the other physiological sign signals.
Wherein, the extracting of the pulse wave waveform according to the photoplethysmography signal and the other physiological signs comprises: and filtering the influence of other physiological sign signals in the photoplethysmography signals to obtain filtered photoplethysmography signals, and extracting pulse wave waveforms according to the filtered photoplethysmography signals.
Wherein, when considering the influence of other physiological sign signals, the pulse wave waveform in this application can be all according to the pulse wave waveform of extracting out and getting of photoplethysmography signal after filtering.
Wherein, the photoplethysmography signal after obtaining the filtration by filtering the influence of other physiological sign signals in the photoplethysmography signal includes:
obtaining a rhythm quantization parameter value according to the photoplethysmography signals and obtaining other physiological sign parameter values according to the other physiological sign signals; determining a filtering scheme according to the rhythm quantization parameter value and the other physiological sign parameter values; and filtering out the influence of other physiological sign signals in the pulse wave signals according to the filtering scheme to obtain filtered pulse wave signals.
Further, the filtering scheme includes a selected filter and filtering parameters, and the determining the filtering scheme according to the rhythm quantization parameter value and the other physiological sign signals includes: and determining a corresponding target filter and a target filtering parameter according to the ratio or the difference value of the rhythm quantization parameter value and the other physiological sign parameter values. The filtering of the pulse wave signals according to the filtering scheme to remove the influence of other physiological sign signals to obtain filtered pulse wave signals includes: and filtering the pulse wave signal by the target filter according to the target filtering parameter to obtain a filtered pulse wave signal.
The filter is a hardware filter in the monitoring device 200, the monitoring device 200 includes a plurality of filters, and each filter corresponds to a plurality of filter parameters.
Wherein, the determining the corresponding target filter and target filter parameter according to the ratio of the rhythm quantization parameter value to the other physiological sign parameter values comprises: determining a filtering scheme corresponding to the ratio or difference between the rhythm quantization parameter value and the other physiological sign parameter values according to the corresponding relation between the preset ratio or difference and the filtering scheme; and determining the filter and the filter parameter in the filtering scheme as the target filter and the target filter parameter respectively.
The corresponding relationship between the ratio and the filtering scheme may be a pre-stored corresponding relationship table.
In some embodiments, the other sensor comprises a respiration sensor, the other physiological sign signal comprises a respiration signal, the other physiological sign parameter value comprises a parameter for characterizing respiration wave morphology and/or signal frequency, for example, a respiration rate, a respiration wave interval, a respiration wave amplitude, a respiration wave pulse slope, and the like, and may also be a respiration wave form, and the rhythm quantification parameter value comprises a pulse rate.
Because the change of the intrathoracic pressure when venous blood flows back to the heart is caused during respiration, the stretch receptors in the lung feel the change of the pressure, the neural activity can regulate the blood vessel movement center of the brain, the sympathetic nerve is controlled to act on the blood vessel to cause the change of the blood vessel, and the change of the detected pulse wave is further caused. Therefore, the pulse wave changes due to the action of the vagus nerve during respiration, the vagus nerve is inhibited during inspiration, the pulse wave interval is reduced, the vagus nerve inhibition is cancelled during expiration, and the pulse wave interval is enlarged. Therefore, the respiratory factor is filtered when the irregular pulse is identified based on the pulse wave signal, and the more real characteristic value of the pulse wave signal can be obtained, so that the identification accuracy of the irregular pulse is improved.
In some embodiments, the steps S22-S25 may be executed in the monitoring device 200, that is, the processing procedures of "processing the photoplethysmographic pulse wave signal to extract the pulse wave waveform", "obtaining the characteristic value characterizing the pulse wave fluctuation rhythm according to the pulse wave waveform", "identifying the fluctuation rhythm of the pulse wave according to the characteristic value to obtain the regularity evaluation information", "outputting the prompt information according to the regularity evaluation information", and the like may be executed for the monitoring device 200.
In some embodiments, the method further comprises: and sending the prompt information to a monitoring management device 300 such as a department-level workstation device and/or an institution-level data center/an institution-level emergency center management device, and outputting the prompt information through the department-level workstation device and/or the institution-level data center/the institution-level emergency center management device.
Wherein, when the monitoring device 200 is the mobile monitoring device 201, the above steps may also be: the prompt information is sent to the monitoring management device 300 such as the bedside monitor 202, the department-level workstation device and/or the hospital-level data center/hospital-level emergency center management device, and the prompt information is output through the bedside monitor 202, the department-level workstation device and/or the hospital-level data center/hospital-level emergency center management device.
That is, when the monitoring device 200 is the mobile monitoring device 201, the prompt information can also be sent to the bedside monitor 202 for display and output.
The monitoring management device 200, the department workstation device and/or the hospital data center/hospital emergency center management device, and other monitoring management devices 300 may output prompt information, or only one of the monitoring device 200 and the monitoring management device 300 may output prompt information.
In other embodiments, the steps S22-S24 may be performed in the monitoring management device 300, that is, "processing the photoplethysmographic pulse wave signal to extract a pulse wave waveform," "obtaining a feature value characterizing the pulse wave fluctuation rhythm according to the pulse wave waveform," "identifying the fluctuation rhythm of the pulse wave according to the feature value to obtain regularity evaluation information," and the like, and may also be performed in a department-level workstation device and/or a hospital-level data center/hospital-level emergency center management device.
The method further comprises the following steps: and sending the photoplethysmography signals to department-level workstation equipment and/or hospital-level data center/hospital-level emergency center management equipment, and performing processing operations such as processing the photoplethysmography signals to extract pulse wave waveforms, acquiring characteristic values representing pulse wave fluctuation rhythms according to the pulse wave waveforms, and identifying the pulse wave fluctuation rhythms according to the characteristic values to obtain regularity evaluation information through the department-level workstation equipment and/or the hospital-level data center/hospital-level emergency center management equipment to obtain the regularity evaluation information.
In some embodiments, said outputting the prompt information according to the regularity evaluation information further includes: and receiving the regularity evaluation information from the department-level workstation equipment and/or the hospital-level data center/hospital-level emergency center management equipment, and outputting prompt information according to the received regularity evaluation information.
Obviously, when the monitoring device 200 is a mobile monitoring device 201, in order to send the photoplethysmographic signal to a bedside monitor 202, a department-level workstation device and/or an institution-level data center/institution-level emergency center management device, etc., regularity evaluation information can be obtained by processing the bedside monitor 202, the department-level workstation device and/or the institution-level data center/institution-level emergency center management device, etc.; and receiving regularity evaluation information from the bedside monitor 202, the department-level workstation equipment and/or the hospital-level data center/hospital-level emergency center management equipment, and outputting prompt information according to the received regularity evaluation information.
Thus, the method of the present application may be performed in one device, the monitoring device 200, and in a plurality of different devices in the monitoring system 100.
Please refer to fig. 11, which is a flowchart illustrating a method for prompting regularity evaluation information according to another embodiment of the present application. The prompting method can be applied to the monitoring system 100 or the monitoring device 200, for example, as described above. In some embodiments, the monitoring system 100 or the monitoring device 200 is a monitoring system or a monitoring device without a cardiac electrical sensor.
The prompting method of the regularity evaluation information comprises the following steps:
a sensor signal is acquired by a sensor connected to a measurement object, wherein the sensor is a non-electrocardiographic sensor (S91). Furthermore, the sensor is a non-electrocardio sensor and can acquire pulse wave signals or sensor signals reflecting the pulse wave signals.
A pulse wave signal of the measurement subject is extracted from the sensor signal (S92).
The pulse wave signal is processed to extract a pulse wave waveform (S93).
And acquiring a characteristic value representing the fluctuation rhythm of the pulse wave according to the pulse wave waveform (S94).
The fluctuation rhythm of the pulse wave is identified from the feature values to obtain regularity evaluation information (S95).
And outputting prompt information according to the regularity evaluation information (S96).
In the current ECG technology, an electrocardiogram sensor is used for acquiring potential difference changing on the body surface of a human body in real time and is recorded in a lead waveform mode, and the electrical activity of the heart reflected on the electrocardiogram can assist doctors in diagnosing pathological changes at the corresponding position of the heart. The non-electrocardio sensor adopted in the application can be connected to a human body to acquire and transmit physiological signals for assisting heart diagnosis, and the biggest difference of the non-electrocardio sensor and the electrocardio sensor for acquiring the potential difference of the body surface of the human body to diagnose the heart in the traditional technology is that the non-electrocardio sensor does not acquire the potential difference of real-time variation of the body surface of the human body.
Such sensors are therefore referred to as "non-cardiac electrical sensors" in this application. For example, in some embodiments, the non-electrocardiographic sensor may radiate light of different wavelengths into a tissue region of a corresponding site of a subject, detect an optical signal transmitted through the tissue region, extract a photoplethysmographic signal from the optical signal resulting from light absorption by the tissue region, and obtain a pulse wave signal using the photoplethysmographic signal. For another example, in some embodiments, the non-electrocardiographic sensor may obtain the pulse wave signal by placing the cuff at a predetermined portion of the body, controlling the cuff to inflate to a certain pressure, causing the cuff to compress the artery, then gradually deflating, sampling the pressure in the cuff during deflation or inflation, and detecting the pulse wave at that pressure.
Therefore, in the present application, the pulse wave signal is extracted from the periodic physiological signal acquired by the sensor, and the regularity evaluation information is obtained by identifying information related to the heart beat rhythm, which is the fluctuation rhythm of the pulse wave, based on the pulse wave signal, and the regularity evaluation information can be accurately obtained using the "non-electrocardiographic sensor" without using the ECG technique.
In the embodiment of the present application, whether a pulse wave is regularly screened is obtained according to a pulse wave signal acquired from the non-electrocardiographic sensor, and corresponding pulse wave related information and/or regularity evaluation information within a period of time is obtained, where the corresponding pulse wave related information and/or regularity evaluation information within the period of time at least includes pulse wave related information and/or regularity evaluation information corresponding to the occurrence of an irregular pulse wave.
Steps S92 to S96 in this embodiment correspond to and are similar to steps S21 to S25 in fig. 2, and the difference between this embodiment and the prompting method shown in fig. 2 is that the sensor is not a blood oxygen sensor or at least not limited to a blood oxygen sensor, and the difference is only that the pulse wave signal is acquired in a certain manner.
For example, the monitoring device 200 or the monitoring system 100 includes a display screen, and the prompt information includes at least one of: the regularity evaluation information displayed in a first display area of the display screen; displaying pulse wave related information in a second display area of the display screen; and displaying related information of executable functions in a third display area of the display screen, wherein the executable functions are functions which can be executed in the next step when the regularity evaluation information meets preset conditions.
Wherein the regularity evaluation information is displayed in at least one of the following forms: text, pattern, light.
Wherein the second display area includes a first sub-display area, and the pulse wave related information includes a pulse wave waveform displayed in the first sub-display area and/or a rhythm quantization parameter value displayed in the second sub-display area.
Wherein the second display region comprises a second sub-display region, and the rhythm quantization parameter value displayed in the second sub-display region comprises at least one of: the pulse rate measurement method comprises the following steps of (1) a characteristic value, statistical analysis data of the characteristic value and a preset threshold, wherein the statistical analysis data comprise at least one of a difference value, a mean value, a standard deviation, a sum, a ratio, an integral, a maximum interval period, a minimum interval period, a pulse variation degree, a variation frequency, a variation degree threshold, a variation frequency threshold, a maximum pulse rate value and a minimum pulse rate value; the characteristic values include: at least one of pulse interval, pulse amplitude, pulse rate value, pulse area, pulse slope, pulse envelope, and pulse width. The preset threshold includes a threshold corresponding to the feature value and/or the statistical analysis data of the feature value, for example, at least one of a variance threshold and a variance number threshold.
Wherein the first sub-display area and the second sub-display area are adjacent.
Wherein the related information of the executable function comprises guide information of the executable function and/or a function icon of the executable function.
And further. The method further comprises the following steps: and responding to the triggering operation of the function icon, and controlling to execute the function corresponding to the function icon.
Wherein the executable function comprises at least one of printing a pulse wave waveform, ordering an ECG exam, ordering an ultrasound exam.
Wherein, when there are at least two display regions, the at least two display regions are sequentially adjacently disposed.
Wherein, the obtaining of the characteristic value representing the fluctuation rhythm of the pulse wave according to the pulse wave waveform comprises: and performing feature extraction on the pulse wave signals in the period of time or in a plurality of periods by adopting at least one analysis technology of a time domain technology, a frequency domain technology and a nonlinear dynamics technology to obtain at least one feature value.
Furthermore, the corresponding nonlinear dynamics characteristic value calculation result can be compared with the corresponding preset threshold value to obtain pulse wave related information and/or regularity evaluation information. For example, the calculation result of the nonlinear dynamics characteristic value is compared with a corresponding preset threshold value, so as to identify irregular pulse wave signals, extract irregular pulse wave signals within a period of time, and output pulse wave related information and/or regularity evaluation information corresponding to the irregular pulse wave signals based on the irregular pulse wave signals within the period of time.
In some embodiments, when the pulse wave is determined to be irregular by utilizing the nonlinear dynamics eigenvalue analysis, analysis methods such as time domain analysis, frequency domain analysis, machine learning and the like can be utilized to determine the pulse wave waveform related information, such as the pulse interval, and output and display the information. In some embodiments, the user may further determine the regularity evaluation information based on the pulse wave waveform related information that is output for display.
Wherein, the obtaining of the characteristic value representing the fluctuation rhythm of the pulse wave according to the pulse wave waveform comprises: extracting the characteristics of the pulse wave signals within a period of time or a plurality of periods to obtain at least one characteristic value; analyzing the at least one characteristic value through a machine learning method to obtain the regularity evaluation information; and/or analyzing the at least two characteristic values by a statistical analysis method and/or a machine learning method to obtain the regularity evaluation information.
Wherein the analyzing the at least two feature 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 to obtain statistical analysis data, and obtaining the regularity evaluation information according to the statistical analysis data; and/or deriving the output of the regularity evaluation information by using the at least two characteristic values as input through a machine learning method.
The machine learning method may be to build a machine learning model, such as a neural network model, through model training, so that the at least two feature values may be used as inputs of the machine learning model, and the output of the regularity evaluation information representing a rule or an irregularity may be automatically derived.
In some embodiments, analyzing the at least two feature values by a machine learning method to obtain the regularity evaluation information includes:
and inputting the pulse wave signals into the machine learning model after training is completed, and automatically obtaining regularity evaluation information.
Wherein, a machine learning model, such as a neural network model, can be established through model training. In one embodiment, when the machine learning model is trained, the association relationship between the at least two feature values and the regularity evaluation information may be input into the trained machine learning model, so as to obtain the machine learning model after the training is completed. Of course, in some embodiments, the aforementioned pulse wave signals are machine-learned to obtain at least two feature values, including: at least two characteristic values obtained based on the pulse wave signals after time domain analysis, frequency domain analysis or nonlinear dynamics analysis are input into the machine learning model after training is completed, and regularity evaluation information can be automatically obtained.
In some embodiments, after obtaining a feature value characterizing a pulse wave fluctuation rhythm from the pulse wave waveform, the method further comprises: converting the obtained characteristic value into an intermediate characteristic value; the identifying the fluctuation rhythm of the pulse wave according to the characteristic value to obtain the regularity evaluation information comprises the following steps: and identifying the fluctuation rhythm of the pulse wave based on the intermediate characteristic value to obtain regularity evaluation information.
In some embodiments, the intermediate feature value includes a pulse sound feature value, and the converting the acquired feature value into the intermediate feature value includes: and converting the acquired characteristic value into a pulse sound characteristic value.
In some embodiments, the converting the extracted feature value into a pulse sound feature value includes: determining the arrival time of the peak or the trough of the pulse according to the acquired characteristic value, and marking the peak or the trough at the arrival time of the peak; and generating a pulse sound characteristic value according to the peak mark or the trough mark.
In some embodiments, the type of regularity evaluation information includes a rule or an irregularity, the method further comprising: and when the regularity evaluation information is irregular, outputting alarm information.
Wherein, the display form of the alarm information comprises at least one of characters, patterns, light, sound and vibration.
In some embodiments, when the regularity evaluation information is irregular, outputting alarm information includes: and determining an alarm gear according to the acquired characteristic value, and controlling to output alarm information of the corresponding alarm gear, wherein the alarm gear comprises at least two gears.
In some embodiments, the sensor includes at least one of a pressure sensor, an electromagnetic sensor, a sound sensor, and an acceleration sensor.
Wherein, when the sensor is a pressure sensor, the sensor signal in the step of "acquiring a sensor signal by a sensor connected to a measurement object" may be a pressure signal, and the step of "extracting a pulse wave signal of the measurement object from the sensor signal" includes: and obtaining the pulse wave signal of the measuring object according to the change of the pressure in the pressure signal.
The pressure sensor can be a blood pressure sensor and is used for acquiring a pressure signal of pulse wave and blood vessel fluctuation.
When the sensor is an electromagnetic sensor, the electromagnetic sensor can comprise a conducting ring worn on the wrist and sensors such as a Hall sensor arranged in a magnetic field of the conducting ring, the conducting ring on the wrist stretches and contracts along with the pulse of the pulse tube, so that the magnetic field changes, and the Hall sensor can detect the change to generate corresponding electromagnetic induction signals. The step of "acquiring a sensor signal by a sensor connected to a measurement object" may be an electromagnetic induction signal, and the step of "extracting a pulse wave signal of the measurement object from the sensor signal" includes: and obtaining the pulse wave signal of the measuring object according to the change of the induction intensity in the electromagnetic induction signal.
For another example, when the sensor is an acoustic sensor, the acoustic sensor may collect an acoustic signal of the pulse beat, that is, the sensor signal may be an acoustic signal, and then the frequency, volume, tone, and other characteristics of the acoustic signal may be analyzed to obtain a pulse wave signal.
Please refer to the foregoing description related to fig. 2-10 for other more specific or additional steps, which are not repeated herein.
Please refer to fig. 12, which is a block diagram of a monitoring device 200 according to an embodiment of the present application. As shown in fig. 12, a block architecture diagram of the monitoring device 200 is shown. As shown in fig. 2, the monitoring device 200 includes a blood oxygen sensor 210 and a processor 220.
The blood oxygen sensor 210 is used to radiate light of different wavelengths into a tissue region of a subject and detect light signals transmitted through the tissue region.
The processor 220 is connected to the blood oxygen sensor 210, and configured to extract a photoplethysmography signal generated by light absorption of the tissue region from the optical signal, process the photoplethysmography signal to extract a pulse waveform, obtain a feature value representing a pulse wave fluctuation rhythm according to the pulse waveform, identify the pulse wave fluctuation rhythm according to the feature value to obtain regularity evaluation information, and control output of prompt information according to the regularity evaluation information.
The blood oxygen sensor 210 includes a blood oxygen probe, which may be a clip-type structure, for being clipped on a measurement object, such as a finger of a patient. The tissue region may be a finger region of a measurement object.
In some embodiments, the blood oxygen sensor comprises a Light Emitting Device (LED) for emitting light to a tissue region of a subject and a light receiving device (PD) for receiving light signals transmitted/reflected through the tissue region. Wherein, both the LED and the PD can be arranged on the blood oxygen probe.
The monitoring device 200 further includes a display screen 230, the processor 220 controls the display screen 230 to display the prompt information, and the prompt information at least includes one of the following: the regularity evaluation information displayed in the first display area of the display screen 230; pulse wave related information displayed in a second display area of the display screen 230; and displaying related information of an executable function in the third display area 230 of the display screen 230, wherein the executable function is a function which can be executed in the next step when the regularity evaluation information meets a preset condition.
Referring back to fig. 3, as shown in fig. 3, the prompt message may only include the regularity evaluation message P1 of "suspected irregular pulse", and in this case, 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 function interface or a system interface of the monitoring device 200. It is to be understood that the regularity evaluation information P1 may also include other words such as "irregular pulse", "irregularity", "pulse abnormality", "irregular pulse interval", etc., as long as it can prompt the measurement object that the pulse is irregular currently or may be irregular, and the word expression form is not limited.
Obviously, when the regularity evaluation information is a rule, the prompt information may be "regular pulse", "rule", "normal", and the like, which can prompt that the current pulse of the measurement object is normal.
When the prompt information comprises the regularity evaluation information, the user can directly see the result of the intelligent analysis of the equipment, the operation is convenient and visual, and the user can conveniently execute follow-up examination, such as appointment electrocardiographic examination, ultrasonic examination and the like.
Referring back to fig. 4, as shown in fig. 4, the prompt message may only include the pulse wave related information P2 displayed in the second display area a 2. Specifically, the pulse wave related information P2 displayed in the second display area a2 includes — the pulse interval is: 31, 43, 33, 48, 29; the mean pulse interval is 36.8; the pulse interval difference is: 12, 10, 15, 19; the mean 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 by the display screen. When the second display area a2 is a certain area of the current interface, the prompt message can be displayed on the current interface in a pop-up window manner. When the second display area a2 is the entire display area of the display screen, the prompt message may be displayed in a prompt interface after switching from the current interface to the prompt interface.
When the prompt information includes the pulse wave related information P2, a waveform reference may be provided to the user for the user to confirm the regularity evaluation information.
Referring back to fig. 5, as shown in fig. 5, the prompt information may further include both 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 and the second display area a2 where the pulse wave-related information P2 is located are adjacently disposed. It is to be understood that the first display area a1 and the second display area a2 may not be adjacent to each other, and may be disposed arbitrarily. In the embodiment, the adjacent arrangement of the first display area a1 and the second display area a2 can facilitate the user to visually check the regularity evaluation information and judge the specific reason of the occurrence regularity evaluation information of the measurement object according to the pulse wave related information in combination with the pulse wave related information.
Referring back to fig. 6, as shown in fig. 6, the prompt information may include the regularity evaluation information P1 displayed in the first display area a1, the pulse wave related information P2 displayed in the second display area a2, and the executable function related information P3 displayed in the third display area A3. The display of the related information P3 of executable function can play a role of prompting and guiding the related operation to be executed next, so as to facilitate the user to learn and execute the operation to be executed next.
Wherein the first display region a1, the second display region a2, and the third display region A3 are sequentially disposed adjacent to A3. Obviously, in other embodiments, the first display region a1, the third display region A3, and the second display region a2 may be disposed adjacent to each other in sequence, and the sequence may be arbitrarily adjusted as long as a plurality of regions are disposed adjacent to each other.
Thus, in the present application, when there are at least two display regions, the at least two display regions are adjacently located on the display screen 230. It is to be understood that the at least two display areas are adjacently disposed on the display screen for the convenience of the user to view the regularity evaluation information, the pulse wave-related information, and the information related to the executable function. In other embodiments of the present invention, the display regions may not be adjacently disposed.
Referring back to fig. 7 and 8, as shown in fig. 7, the first display region P1 is not adjacent to the second display region P2. In this embodiment, the display screen further includes a touch area T for retracting or expanding the second display area P2 to correspondingly hide or display the pulse wave related information a 2. As shown in fig. 8, the regularity evaluation information a1 is displayed only in the first display area P1, so that the user can focus on the regularity evaluation information a1, and the second display area P2 is closed, so that the pulse wave related information a2 is hidden. The arrangement enables a user to select to view or hide the pulse wave related information according to actual needs, and when the pulse wave related information is hidden, the interface of the display screen is neat and attractive; when the user regularity evaluation information a1 suggests "irregularity" or the user needs to view the pulse wave related information a2 for other reasons, the second display area P2 may be expanded for viewing by clicking the touch area T.
The prompt information including at least one of the regularity evaluation information, the pulse wave related information and the executable function related information prompt information can be displayed on a current interface in a pop-up window mode, or can be displayed in the prompt interface after the current interface is switched to the prompt interface.
Wherein, in some embodiments, the regularity evaluation information is displayed by at least one of the following forms: text, pattern, light.
For example, as shown in fig. 3, the regularity evaluation information may include both characters and patterns: suspected irregular pulse
". Obviously, an indicator light can be arranged on the display screen, and regularity evaluation information can be indicated through light emitted by the indicator light, for example, when red light is emitted, irregularity is indicated, and when green light is emitted, gauge is indicatedThen ".
In some embodiments, when the prompt message is a pop-up window display and includes at least two of the regularity evaluation message, the pulse wave related message, and the related message prompt message of the executable function, at least two of the regularity evaluation message, the pulse wave related message, and the related message prompt message 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 region a1, the second display region a2, and the third display region A3 may be located in the same window or may be located in different windows.
As shown in fig. 4 to 6, the second display area a2 further includes a first sub-display area a21, and the pulse wave-related information includes the pulse wave waveform displayed in the first sub-display area and/or the rhythm quantization parameter value displayed in the second sub-display area a 22. The pulse wave waveform is extracted by processing the photoplethysmographic pulse wave signal in step S22. By displaying the pulse wave waveform, the pulse condition of the pulse can be visually displayed.
As shown in fig. 4 to 6, the second display region a2 includes a second sub display region a22, and the rhythm quantization parameter values displayed in the second sub display region a22 include at least one of: the pulse rate measurement method comprises the following steps of (1) obtaining a characteristic value, statistical analysis data of the characteristic value and a preset threshold, wherein the statistical analysis data comprise at least one of difference, mean, standard deviation, summation, ratio, integral, maximum interval period, minimum interval period, pulse variation degree, variation frequency, variation threshold, variation frequency threshold, maximum pulse rate value and minimum pulse rate value of the characteristic value; the characteristic values include: 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 further include a characteristic value representing a fluctuation rhythm of the pulse wave directly obtained from the pulse wave waveform, and/or statistical analysis data obtained by performing statistical analysis on the characteristic values. The preset threshold includes a threshold corresponding to the feature value and/or the statistical analysis data of the feature value, for example, at least one of a variance threshold and a variance number threshold.
As shown in fig. 4 to 6, the first sub-display area a21 and the second sub-display area a22 are adjacently disposed. The specific positional relationship between the first sub-display region a21 and the second sub-display region a22 is not limited, for example, as shown in fig. 4, the second sub-display region a22 is above, or as shown in fig. 5-6, the first sub-display region a21 is above.
In some embodiments, the information related to the executable function includes guide information of the executable function and/or a function icon of the executable function.
The guidance 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, and the guidance information may be a text or a pattern, and is used to guide the user to know the executable function of the monitoring device 200 and how to trigger the executable functions.
As shown in fig. 6, the information related to the executable function may also directly include function icons B1 of executable functions, so that each function icon B1 of executable function is displayed in a more direct manner for a user to operate to trigger the corresponding executable function.
Therefore, the prompting method may further include: and responding to the triggering operation of the function icon B1, and controlling the execution of the function corresponding to the function icon B1.
As shown in fig. 6, the executable function includes at least one of printing a pulse wave waveform, reserving an ECG exam, reserving an ultrasound exam, and may also include other functions such as a user-defined general function. Accordingly, the function icon B1 may include at least one function icon including a print pulse waveform function icon, a reserved ECG examination function icon, and a reserved ultrasound examination function icon.
In some embodiments, the processor 220 obtains the at least one feature value by performing feature extraction on the pulse wave signal within a period or a plurality of periods by using at least one analysis technique selected from a time domain technique, a frequency domain technique, and a nonlinear dynamics technique.
Wherein the processor 220 identifies the fluctuation rhythm of the pulse wave according to the characteristic value to obtain the regularity evaluation information, which may include: the processor 220 compares at least one characteristic value with a corresponding preset threshold value to obtain regular or irregular regularity evaluation information.
As previously mentioned, the characteristic value may include at least one of pulse interval, pulse magnitude, and pulse rate value. For example, the at least one feature value may be a pulse interval, the preset threshold may be a preset pulse interval range, and the "the processor 220 compares the at least one feature value with the corresponding preset threshold to obtain regular or irregular regularity evaluation information" may further include: the processor 220 compares the pulse interval with a preset pulse interval range, and obtains regular evaluation information that is "irregular" when it is determined that the pulse interval is outside the preset pulse interval range, and obtains regular evaluation information that is "regular" when it is determined that the pulse interval is within the preset pulse interval range.
That is, in some embodiments, regular or irregular regularity evaluation information may be acquired directly from a characteristic value that characterizes the rhythm of fluctuation of a pulse wave acquired from the pulse wave waveform.
In some embodiments, the processor 220 is specifically configured to perform feature extraction on the pulse wave signals within a period of time or several periods to obtain at least one feature value; analyzing the at least one characteristic value through a machine learning method to obtain the regularity evaluation information; and/or 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 may also perform feature extraction on the pulse wave signals within a period of time or several periods to obtain at least two feature values: the processor 220 performs feature extraction on the pulse wave signals within a period or several periods by using at least one analysis technique of a time domain technique, a frequency domain technique and a nonlinear dynamics technique to obtain at least two feature values.
In some embodiments, the step of "acquiring a feature value characterizing a pulse wave fluctuation rhythm from the pulse wave waveform" includes: and (3) performing feature extraction on the pulse wave signals by adopting a nonlinear dynamics technology to obtain at least one nonlinear dynamics characteristic value.
That is, in some embodiments, the pulse wave signal may be feature extracted using only a non-linear dynamics technique to obtain at least one non-linear dynamics feature value.
Furthermore, the corresponding nonlinear dynamics characteristic value calculation result can be compared with the corresponding preset threshold value to obtain the characteristic value representing the pulse wave fluctuation rhythm. For example, the calculation result of the nonlinear dynamics characteristic value is compared with a corresponding preset threshold value, so that irregular pulse wave signals are identified, irregular pulse wave signals within a period of time are extracted, and the characteristic value corresponding to the irregular pulse wave signals and representing the pulse wave fluctuation rhythm is output based on the irregular pulse wave signals within the period of time.
In some embodiments, when the extracted feature value of the nonlinear dynamics count is used for analyzing and confirming that the pulse wave is irregular, the feature value representing the pulse wave fluctuation rhythm, such as the pulse interval, can be determined by methods of time domain analysis, frequency domain analysis, machine learning and the like, and is output and displayed. In some embodiments, the user may further determine the regularity evaluation information based on the output displayed characteristic value that characterizes the pulse wave fluctuation rhythm.
Further, the processor 220 analyzes the at least two feature values by a statistical analysis method to obtain statistical analysis data, and obtains the regularity evaluation information according to the statistical analysis data; and/or the processor derives the output of the regularity evaluation information by a machine learning method using the at least two feature values as inputs.
The statistical analysis data may be at least one of the aforementioned difference, mean, standard deviation, sum, ratio, integral, maximum interval period, minimum interval period, pulse variability, variation frequency, maximum pulse rate value, and minimum pulse rate value, and the obtaining the regularity evaluation information according to the statistical analysis data may include comparing the statistical analysis data such as the difference, mean, standard deviation, maximum interval period, minimum interval period, pulse variability, variation frequency, maximum pulse rate value, and minimum pulse rate value with preset statistical data such as the difference, mean, standard deviation, maximum interval period, minimum interval period, variation threshold, variation frequency threshold, maximum pulse rate value, and minimum pulse rate value, to obtain regular or irregular regularity evaluation information.
Thus, in other embodiments, the processor 220 may perform statistical analysis on the feature value representing the pulse wave fluctuation rhythm obtained according to the pulse wave waveform to obtain statistical analysis data, and then obtain regular or irregular regularity evaluation information according to the statistical analysis data.
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 one feature value may be used as an input of the machine learning model to automatically derive an output of the regularity evaluation information which is regular or irregular.
In the present application, the feature values obtained by the time domain technique include, but are not limited to, waveform interval, amplitude, pulse area, pulse slope, pulse envelope, pulse width, and the like.
The frequency domain technology is to convert the pulse waveform of the time domain into a frequency domain signal through algorithms such as Laplace transform, and the like, and the characteristic values obtained through the frequency domain technology include but are not limited to frequency domain characteristic values such as frequency spectrum peak characteristics, power spectrum characteristics and the like.
The characteristic value obtained through the nonlinear dynamics analysis includes but is not limited to a nonlinear dynamics characteristic value within entropy value characteristics or complexity characteristics of information entropy, spectral entropy, approximate entropy, sample entropy and fuzzy entropy of the pulse wave waveform.
In some embodiments, the processor 220 extracting the features of the pulse wave signals to obtain at least one feature value by using at least one of a time domain technique, a frequency domain technique and a non-linear dynamics technique, or the processor 220 extracting the features of the pulse wave signals in a period of time or in a number of cycles by using at least one of a time domain technique, a frequency domain technique and a non-linear dynamics technique to obtain at least two feature values may include: the processor 220 performs feature extraction on the pulse wave signal by using at least two analysis techniques of a time domain technique, a frequency domain technique, and a nonlinear dynamics technique to obtain at least two types of feature values, and obtains at least one final feature value or at least two final feature values according to the two types of feature values and a weight value of each type of feature value.
For example, after the processor 220 performs feature extraction on the pulse wave signals by using a time domain technique to obtain a time domain feature value and performs feature extraction on the same segment of pulse wave signals by using a frequency domain technique to obtain a frequency domain feature value, the final feature value may be obtained according to a weighted calculation formula ax + by. The method comprises the steps of obtaining a pulse wave signal, obtaining a time domain characteristic value, a frequency domain characteristic value, a weight value of the time domain characteristic value, and b weight value of the frequency domain characteristic value, wherein x can be a time domain characteristic value, y can be a frequency domain characteristic value, a is a weight value of the time domain characteristic value, and b is a weight value of the frequency domain characteristic value, so that the same segment of pulse wave signal is analyzed through multiple analysis technologies, the final characteristic value can be obtained by combining multiple types of characteristic values obtained through the multiple technologies and the weight value of each.
In some embodiments, the processor 220 is further configured to perform a combined analysis on different feature values using the same or different methods to identify a fluctuating rhythm of the pulse wave to obtain regularity evaluation information.
Wherein the different feature values include multiple types of feature values analyzed by different analysis techniques (e.g., time domain feature values, frequency domain feature values, etc.) and/or multiple types of different feature values analyzed by the same analysis technique (e.g., pulse interval, pulse slope, pulse width, etc.).
Wherein the same or different methods include statistical methods, machine learning methods, and the like.
In some embodiments, after the processor 220 obtains the feature value characterizing the pulse wave fluctuation rhythm according to the pulse wave waveform, the processor is further configured to convert the obtained feature value into an intermediate feature value, and identify the fluctuation rhythm of the pulse wave based on the intermediate feature value to obtain the regularity evaluation information.
Wherein the intermediate characteristic value includes a pulse sound characteristic value, and the processor 220 converts the acquired characteristic value into an intermediate characteristic value, including: and converting the acquired characteristic value into a pulse sound characteristic value.
Further, the converting the extracted feature value into the pulse sound feature value by the processor 220 includes: the processor 220 determines the arrival time of the peak or the trough of the pulse according to the acquired feature value, marks the peak or the trough at the arrival time of the peak or the trough, and generates a pulse sound feature value according to the peak or the trough mark.
Further, the type of the regularity evaluation information includes a rule or an irregularity, and the processor 220 is further configured to output an alarm message when the regularity evaluation information is irregular.
The display form of the alarm information comprises at least one of characters, patterns, light, sound and vibration.
As shown in fig. 12, the monitoring device 200 further includes an indicator light 240, a speaker 250, and a vibrator 260.
When the alarm information is the text and/or the pattern, the processor 220 may control the display screen 230 to display the text and/or the pattern, and when the alarm information is light, the processor 220 may control the display screen or the indicator 240 to display corresponding light, for example, control the entire display screen or a specific area of the display screen to display red and other colors, or control the indicator 240 to emit red light.
The indicator lamp 240 may specifically be an indicator lamp including a red LED lamp, a green LED lamp, and a blue LED lamp, and the processor 220 may generate or mix light of corresponding colors by controlling different colors and/or numbers of LED lamps to emit light.
When the alarm information is voice alarm information, the processor 220 may control the speaker 250 to output a voice.
When the alarm information is vibration, the processor 220 may control the vibrator 260 to generate vibration.
In some embodiments, when the regularity evaluation information is irregular, the processor 220 further determines an alarm gear according to the obtained characteristic value, and controls to output alarm information of a corresponding alarm gear, where the alarm gear includes at least two gears.
Specifically, the processor 220 compares the obtained characteristic value with a plurality of reference values, determines a characteristic value interval in which the characteristic value is located, and determines a corresponding alarm gear according to the determined characteristic value interval and a corresponding relationship between the characteristic value interval and the alarm gear.
For example, when the obtained feature value is a pulse slope in the time domain feature value, the processor 220 determines that the corresponding alarm gear is the first alarm gear when the pulse slope is greater than or equal to a first pulse slope and smaller than a second pulse slope, and controls to send out green light or sound alarm information with a smaller decibel; when the pulse slope is greater than or equal to the second pulse slope and smaller than the third pulse slope, the processor 220 determines that the corresponding alarm gear is the second alarm gear, and controls to send out orange light or medium decibel sound alarm information; and when the pulse slope is greater than or equal to the third pulse slope, the processor 220 determines that the corresponding alarm gear is the third alarm gear, and controls to send out red light or highest decibel sound alarm information.
Wherein, the first pulse slope is smaller than the second pulse slope, and the second pulse slope is smaller than the third pulse slope. The first alarm gear is smaller than the second alarm gear, and 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 and the like.
As shown in fig. 12, the monitoring device 200 further includes a memory 270, wherein the correspondence between the characteristic value interval and the alarm gear position may be a correspondence table, a correspondence curve, or the like pre-stored in the memory 270.
In some embodiments, the processor 220 is further configured to modify or confirm the regular or irregular regularity evaluation information in response to a result modification operation or a confirmation operation input by a user.
Referring back to fig. 9, as shown in fig. 9, the prompt message may be displayed on an interface in a pop-up manner, the prompt message includes a detailed message area Z1 and a determination area Z2, the detailed message area Z1 displays detailed messages for the user to determine whether the detailed messages are regular, the determination area Z2 includes "regular" and "irregular" options, and the "regular" and "irregular" options are used for the user to select to obtain the regularity rating information. Wherein the detailed information includes: pulse wave waveform (pleth area in the figure), pulse mark, pulse interval measurement value, maximum interval period, minimum interval period, pulse variation degree and other information. In some embodiments of the invention, the content of the detailed information is completely non-overlapping with the content of the toast, the detailed information giving more information than the toast. It will be appreciated that in other embodiments of the invention, the content contained in the detailed information may also be partially or completely identical to the content contained in the reminder information.
For example, the processor 220 determines that the regularity evaluation information is regular in response to the selection operation for the "regular" option, or confirms that the regularity evaluation information is irregular in response to the selection operation for the "irregular" option.
Referring back to fig. 10, as shown in fig. 10, the prompt message includes a "regular" or "irregular" selection box displayed on an interface of the monitoring device 200. The options of "regular" and "irregular" are used for the user to select to confirm or change the regularity evaluation information.
That is, as shown in fig. 10, the current regularity evaluation information is prompted by the currently selected "rule" selection box S1 and "irregularity" selection box S2, and the regularity evaluation information may be changed in response to the user' S selection of the "rule" selection box S1 or the "irregularity" selection box S2.
In another embodiment, the entire interface may be a prompt information interface.
As shown in fig. 10, the prompt message further includes an interface providing operation interface for the user to call out detailed information to assist the user in determining, where the detailed information includes: pulse wave waveform (pleth area in the figure), pulse identification, pulse interval measurement value, maximum pulse interval, minimum pulse interval, pulse interval variation degree and other information. The interface providing the operation interface may be a touch area T known in fig. 7 to 8.
In some embodiments, the monitoring device 200 further comprises at least one other sensor 280, wherein the at least one other sensor 280 is other than the ecg sensor or the oximetry sensor 210.
Wherein the at least one other sensor 280 is used for acquiring other physiological sign signals of the human body.
Wherein the at least one other sensor 280 acquires other physiological signals of the human body and the blood oxygen sensor 210 is used for radiating light with different wavelengths into the tissue area of the measurement object, and the detection of the light signals transmitted through the tissue area can be performed simultaneously.
The processor 220 extracts a pulse waveform according to the photoplethysmography signal and the other physiological sign signals.
Wherein, the processor 220 extracts the pulse wave waveform according to the photoplethysmography signal and the other physiological signs, including: the processor 220 filters out the influence of other physiological sign signals in the photoplethysmographic signal to obtain a filtered photoplethysmographic signal, and extracts a pulse wave waveform according to the filtered photoplethysmographic signal.
Wherein, when considering the influence of other physiological sign signals, the pulse wave waveform in this application can be all according to the pulse wave waveform of extracting out and getting of photoplethysmography signal after filtering.
Wherein, the processor 220 filters out the influence of other physiological sign signals in the photoplethysmographic signal to obtain a filtered photoplethysmographic signal, which includes: the processor 220 obtains a rhythm quantization parameter value according to the photoplethysmogram signal and obtains other physiological sign parameter values according to the other physiological sign signals; determining a filtering scheme according to the rhythm quantization parameter value and the other physiological sign parameter values; and filtering out the influence of other physiological sign signals in the pulse wave signals according to the filtering scheme to obtain filtered pulse wave signals.
As shown in fig. 12, the monitoring device 200 further includes a plurality of filters 290, for example, the plurality of filters 290 includes a filter 1, a filter 2, a filter N, and the like, where N is a positive integer, and the number of N is set as required. The plurality of 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, so that the filtering parameters may be adjusted by adjusting resistors, capacitors, inductors, or the like, or by digital adjustment.
Further, the filtering scheme includes the selected filter 290 and the filtering parameter, and the determining, by the processor 220, the filtering scheme according to the rhythm quantization parameter value and the other physiological sign signals includes: the processor 220 determines the corresponding target filter 290 and target filter parameters according to the ratio or difference between the rhythm quantization parameter value and the other physiological sign parameter values. The processor 220 obtains the filtered pulse wave signal by filtering out the influence of other physiological sign signals in the pulse wave signal according to the filtering scheme, including: the processor 220 filters the pulse wave signal with the target filter parameter through the target filter 290 to obtain a filtered pulse wave signal.
Wherein, each filter corresponds to various filter parameters.
Wherein, the processor 220 determines the corresponding target filter and target filtering parameter according to the ratio of the rhythm quantization parameter value to the other physiological sign parameter values, including: the processor 220 determines a filtering scheme corresponding to the ratio or difference between the rhythm quantization parameter value and the other physiological sign parameter values according to a preset corresponding relationship between the ratio or difference and the filtering scheme; the filter 290 and the filter parameter in the filtering scheme are determined to be the target filter 290 and the target filter parameter, respectively.
The corresponding relationship between the ratio and the filtering scheme may be a table of corresponding relationships pre-stored in the memory 270.
In some embodiments, the other sensor 290 comprises a respiration sensor, the other physiological sign signal comprises a respiration signal, the other physiological sign parameter value comprises a respiration rate, and the rhythm quantification parameter value comprises a pulse rate.
Because the change of the intrathoracic pressure when venous blood flows back to the heart is caused during respiration, the stretch receptors in the lung feel the change of the pressure, the neural activity can regulate the blood vessel movement center of the brain, the sympathetic nerve is controlled to act on the blood vessel to cause the change of the blood vessel, and the change of the detected pulse wave is further caused. Therefore, the pulse wave changes due to the action of the vagus nerve during respiration, the vagus nerve is inhibited during inspiration, the pulse wave interval is reduced, the vagus nerve inhibition is cancelled during expiration, and the pulse wave interval is enlarged. Therefore, the respiratory factor is filtered when the irregular pulse is identified based on the pulse wave signal, and the more real characteristic value of the pulse wave signal can be obtained, so that the identification accuracy of the irregular pulse is improved.
In some embodiments, the monitoring device 200 further comprises a communication unit 291, wherein the communication unit 291 is configured to establish a communication connection with a monitoring management device 300, such as a department-level workstation device and/or an institution-level data center/institution-level emergency center management device. When the monitoring device 200 is a mobile monitoring device, the communication unit 291 may be further configured to establish a communication connection with the bedside monitor 202 and the monitoring management device 300, such as a department-level workstation device and/or an institution-level data center/institution-level emergency center management device.
Wherein, communication unit 291 includes at least one of mobile communication network modules such as bluetooth module, WMTS communication module, NFC communication module, WIFI communication module and 2G/3G/4G/5G.
The processor 220 is further configured to send the prompt information to the monitoring management device 300, such as a department-level workstation device and/or an institution-level data center/institution-level emergency center management device, through the communication unit 291, and output the prompt information through the department-level workstation device and/or the institution-level data center/institution-level emergency center management device.
When the monitoring device 200 is a mobile monitoring device 201, the processor 220 may send the prompt information to a monitoring management device 300 such as a bedside monitor 202, a department-level workstation device, and/or an institution-level data center/institution-level emergency center management device, and output the prompt information through the bedside monitor 202, the department-level workstation device, and/or the institution-level data center/institution-level emergency center management device.
That is, when the monitoring device 200 is the mobile monitoring device 201, the prompt information can also be sent to the bedside monitor 202 for display and output.
In some embodiments, the processor 220 is further configured to send the photoplethysmographic pulse wave signal to a department-level workstation device and/or a hospital-level data center/hospital-level emergency center management device through the communication unit 291, and perform processing operations such as "processing the photoplethysmographic pulse wave signal to extract a pulse wave waveform", "obtaining a feature value representing a pulse wave rhythm from the pulse wave waveform", "identifying a pulse wave rhythm from the feature value to obtain regularity evaluation information" and the like through the department-level workstation device and/or the hospital-level data center/hospital-level emergency center management device to obtain the regularity evaluation information.
In some embodiments, 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 291, and output prompt information according to the received regularity evaluation information.
Obviously, when the monitoring device 200 is a mobile monitoring device 201, the processor 220 may obtain the regularity evaluation information by performing processing operations on the bedside monitor 202, the department-level workstation device, and/or the hospital-level data center/hospital-level emergency center management device for sending the photoplethysmographic pulse wave signal to the bedside monitor 202, the department-level workstation device, and/or the hospital-level data center/hospital-level emergency center management device; and the processor 220 may also receive regularity evaluation information from the bedside monitor 202, the department-level workstation equipment, and/or the hospital-level data center/hospital-level emergency center management equipment, and output prompt information according to the received regularity evaluation information.
The memory 270 also stores program instructions for the processor 220 to call to execute the method steps in fig. 2. The aforementioned method of fig. 2 and the functionality of the monitoring device 200 of fig. 12 are referenced to each other.
Referring to fig. 13, a block diagram of a monitoring device 200 according to another embodiment is shown. In another embodiment, the monitoring device 200 includes a sensor 211 and a processor 220.
The sensor 211 is configured to acquire a sensor signal, where the sensor is a non-electrocardiographic sensor. Furthermore, the sensor is a non-electrocardio sensor and can acquire pulse wave signals or sensor signals reflecting the pulse wave signals.
The processor 220 is connected to the sensor 211, and is configured to acquire the sensor signal and extract a pulse wave signal of the measurement object from the sensor signal; processing the pulse wave signal to extract a pulse wave waveform; acquiring a characteristic value representing the fluctuation rhythm of the pulse wave according to the pulse wave waveform; identifying the fluctuation rhythm of the pulse wave according to the characteristic value to obtain regularity evaluation information; and outputting prompt information according to the regularity evaluation information.
The monitoring device 200 shown in fig. 13 differs from the monitoring device 200 shown in fig. 12 in that the sensor 211 is not, or at least not limited to, a blood oxygen sensor, but only differs in the manner of acquiring the pulse wave signal.
As shown in fig. 13, the monitoring device 200 further comprises a display screen 230, an indicator light 240, a speaker 250, a vibrator 260, a memory 270, at least one other sensor 280, a filter 290 and a communication unit 291.
In some embodiments, the at least one other sensor 280 is a non-electrocardiographic sensor, and also a sensor other than the blood oxygen sensor that is different from the sensor 211.
For example, the sensor 211 includes at least one of a pressure sensor, an electromagnetic sensor, a sound sensor, and an acceleration sensor. The at least one other sensor 280 may be a respiration sensor.
When the sensor 211 is a pressure sensor, the sensor signal may be a pressure signal, and the processor 220 extracting the pulse wave signal of the measurement object from the sensor signal includes: the processor 220 obtains a pulse wave signal of the measurement object according to the change of the pressure magnitude in the pressure signal.
When the sensor 211 is an electromagnetic sensor, the electromagnetic sensor may include a conductive ring worn on the wrist and a hall sensor disposed in a magnetic field of the conductive ring, and the conductive ring on the wrist stretches and contracts along with the pulsation of the pulse tube, resulting in a change in the magnetic field, so that the hall sensor may detect the change to generate a corresponding electromagnetic induction signal. The sensor signal may be an electromagnetic induction signal, and the processor 220 extracting the pulse wave signal of the measurement object from the sensor signal includes: the processor 220 obtains the pulse wave signal of the measurement object according to the change of the induction intensity in the electromagnetic induction signal.
For another example, when the sensor 211 is an audio sensor, the audio sensor can collect an audio signal of pulse, that is, the sensor signal can be an audio signal, and the processor 220 can analyze the characteristics of the audio such as frequency, volume, and tone to obtain a pulse wave signal.
The memory 270 stores therein program instructions, which are used for the processor 220 to execute the steps in the prompting method in fig. 11 after being called.
Specifically, the structure and the executed functions of the monitoring device 200 may refer to the related description of the monitoring device 200 in fig. 12, and may also refer to the related descriptions of fig. 2 and fig. 11, which are not repeated herein.
Referring to FIG. 14, a system block diagram of a multi-parameter monitor or module assembly is shown. The multi-parameter monitor or module assembly includes at least a parameter measurement circuit 112. The parameter measuring circuit 112 at least comprises a parameter measuring circuit corresponding to a physiological parameter, the parameter measuring circuit at least comprises at least one parameter measuring circuit of an electrocardiosignal parameter measuring circuit, a respiration parameter measuring circuit, a body temperature parameter measuring circuit, a blood oxygen parameter measuring circuit, a non-invasive blood pressure parameter measuring circuit, an invasive blood pressure parameter measuring circuit and the like, and each parameter measuring circuit is respectively connected with an externally inserted sensor accessory 111 through a corresponding sensor interface. The sensor accessory 111 includes a detection accessory corresponding to the detection of physiological parameters such as blood oxygen, blood pressure, body temperature, etc. The parameter measurement circuit 112 is mainly used for connecting the sensor accessory 111 to obtain the acquired physiological parameter signal, and may include at least two measurement circuits of physiological parameters, where the parameter measurement circuit may be, but is not limited to, a physiological parameter measurement circuit (module), a human physiological parameter measurement circuit (module) or a sensor to acquire a human physiological parameter, and the like. Specifically, the parameter measuring circuit obtains physiological sampling signals of related patients from external physiological parameter sensor accessories through the expansion interface, and physiological data is obtained after processing for alarming and displaying. The expansion interface can also be used for outputting a control signal which is output by the main control circuit and is about how to acquire the physiological parameters to an external physiological parameter monitoring accessory through a corresponding interface, so that the monitoring control of the physiological parameters of the patient is realized.
For the monitoring device 200, the parameter measurement circuit 112 can be a circuit that processes the sensing signal; the sensor accessories 111 are sensor accessories including the aforementioned blood oxygen sensor 210, sensor 211, and other sensors 280. In particular, for the bedside monitor 202, the sensor accessory 111 is an external sensor accessory that can be plugged in through the sensor interface.
The multi-parameter monitor or module assembly may further include a main control circuit 113, where the main control circuit 113 needs to include at least one processor 1131 and at least one memory 1132, and of course, the main control circuit may further include at least one of a power management module 1133, a power IP module, an interface conversion circuit, and the like. 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/off of the whole device, the power-on timing sequence of each power domain inside the board card, the charging and discharging of the battery, and the like. The power supply IP block refers to a power supply module that associates a schematic diagram of a power supply circuit unit frequently called repeatedly with a PCB layout and solidifies the schematic diagram into individual power supply modules, that is, converts an input voltage into an output voltage through a predetermined circuit, wherein the input voltage and the output voltage are different. For example, a voltage of 15V is converted into 1.8V, 3.3V, 3.8V, or the like. It is understood that the power supply IP block may be single-pass or multi-pass. When the power supply IP block is single-pass, the power supply IP block may convert an input voltage into an output voltage. When the power IP module is the multichannel, the power IP module can be a plurality of output voltage with an input voltage conversion, and a plurality of output voltage's magnitude of voltage can be the same, also can not be the same to can satisfy a plurality of electronic component's different voltage demands simultaneously, and the module is few to the external interface, and the work is black box and external hardware system decoupling zero in the system, has improved whole electrical power generating system's reliability. The interface conversion circuit is used for converting signals output by the minimum system main control module (i.e. at least one processor and at least one memory in the main control circuit) into input standard signals required to be received by actual external equipment, for example, supporting an external VGA display function, converting RGB digital signals output by the main control CPU into VGA analog signals, supporting an external network function, and converting RMII signals into standard network differential signals.
In addition, the multi-parameter monitor or module assembly may further include one or more of a local display 114, an alarm circuit 116, an input interface circuit 117, an external communication and power interface 115. The main control circuit is used for coordinating and controlling each board card, each circuit and each device in the multi-parameter monitor or the module assembly. In this embodiment, the main control circuit is used for controlling data interaction between the parameter measuring circuit 112 and the communication interface circuit and transmission of control signals, and transmitting physiological data to the display 114 for display, and may also receive user control instructions input from a touch screen or a physical input interface circuit such as a keyboard and a key, and of course, may also output control signals on how to acquire physiological parameters. The alarm circuit 116 may be an audible and visual alarm circuit and a vibratory alarm circuit, and may include the previously described indicator light 240, speaker 250, and vibrator 260. The main control circuit completes the calculation of the physiological parameters, and the calculation result and waveform of the parameters can be sent to a host (such as a host with a display, a PC, a central station, etc.) through the external communication and power interface 115, the external communication and power interface 115 may be one or a combination of a local area network interface composed of Ethernet (Ethernet), a Token Ring (Token Ring), a Token Bus (Token Bus), and a backbone Fiber Distributed Data Interface (FDDI) as these three networks, one or a combination of wireless interfaces such as infrared, bluetooth, wifi, WMTS communication, etc., or may also be one or a combination of wired data connection interfaces such as RS232, USB, etc. The external communication and power interface 115 may also be one or a combination of a wireless data transmission interface and a wired data transmission interface. The host can be any computer equipment of a host computer of a monitor, an electrocardiograph, an ultrasonic diagnostic apparatus, a computer and the like, and matched software is installed to form the monitor equipment. The host can also be communication equipment, such as a mobile phone, and the multi-parameter monitor or the module component sends data to the mobile phone supporting Bluetooth communication through the Bluetooth interface to realize remote transmission of the data.
For the monitoring device 200, the local display 114 is the display screen 230, the input interface circuit 117 may be a touch pad integrated with the display screen 230 to form a touch display screen, and the external communication and power interface 115 may be the aforementioned communication unit 291. For the monitoring device 200, the local display 114 is the display screen 230, the input interface circuit 117 can be a touch pad integrated with the display screen 230, and the external communication and power interface 115 can be the communication unit 291 described above.
The multi-parameter monitoring module component can be arranged outside the monitor shell and used as an independent external parameter monitoring module, a plug-in monitor can be formed by a host (comprising a main control board) inserted into the monitor and used as a part of the monitor, or the multi-parameter monitoring module component can be connected with the host (comprising the main control board) of the monitor through a cable, and the external parameter monitoring module is used as an external accessory of the monitor. Of course, the parameter processing can also be arranged in the shell and integrated with the main control module, or physically separated and arranged in the shell to form the integrated monitor.
The memory 270 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), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), a plurality of magnetic disk storage devices, a Flash memory device, or other volatile solid state storage devices.
The Processor 220 is a Central Processing Unit (CPU), and may also be other general purpose processors, Digital Signal Processors (DSP), Application Specific Integrated Circuits (ASIC), Field Programmable Gate Arrays (FPGA) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, and the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
Reference is made herein to various exemplary embodiments. However, those skilled in the art will recognize that changes and modifications may be made to the exemplary embodiments without departing from the scope hereof. For example, the various operational steps, as well as the components used to perform the operational steps, may be implemented in differing ways depending upon the particular application or consideration of any number of cost functions associated with operation of the system (e.g., one or more steps may be deleted, modified or incorporated into other steps).
Additionally, as will be appreciated by one skilled in the art, the principles herein may be reflected in a computer program product on a computer readable storage medium, which is pre-loaded with computer readable program code. Any tangible, non-transitory computer-readable storage medium may be used, including magnetic storage devices (hard disks, floppy disks, etc.), optical storage devices (CD-ROMs, DVDs, Blu Ray disks, etc.), flash memory, and/or the like. These computer program instructions may be loaded onto a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions which execute on the computer or other programmable data processing apparatus create means for implementing the functions specified. These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including means for implementing the function specified. The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified.
While the principles herein have been illustrated in various embodiments, many modifications of structure, arrangement, proportions, elements, materials, and components particularly adapted to specific environments and operative requirements may be employed without departing from the principles and scope of the present disclosure. The above modifications and other changes or modifications are intended to be included within the scope of this document.
The foregoing detailed description has been described with reference to various embodiments. However, one skilled in the art will recognize that various modifications and changes may be made without departing from the scope of the present disclosure. Accordingly, the disclosure is to be considered in an illustrative and not a restrictive sense, and all such modifications are intended to be included within the scope thereof. Also, advantages, other advantages, and solutions to problems have been described above with regard to various embodiments. However, the benefits, advantages, solutions to problems, and any element(s) that may cause any element(s) to occur or become more pronounced are not to be construed as a critical, required, or essential feature or element of any or all the claims. As used herein, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, system, article, or apparatus. Furthermore, the term "coupled," and any other variation thereof, as used herein, refers to a physical connection, an electrical connection, a magnetic connection, an optical connection, a communicative connection, a functional connection, and/or any other connection.
The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and embodiments of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (41)
1. A method for prompting regularity evaluation information, the method comprising:
radiating light of different wavelengths into a tissue region of a measurement object, detecting an optical signal transmitted through the tissue region, and extracting a photoplethysmographic signal generated by light absorption of the tissue region from the optical signal;
processing the photoplethysmography signals to extract a pulse wave waveform;
acquiring a characteristic value representing the fluctuation rhythm of the pulse wave according to the pulse wave waveform;
identifying the fluctuation rhythm of the pulse wave according to the characteristic value to obtain regularity evaluation information;
and outputting prompt information according to the regularity evaluation information.
2. A prompting method as defined in claim 1, wherein the device or system includes a display screen, the prompting message including at least one of:
the regularity evaluation information displayed in a first display area of the display screen;
displaying pulse wave related information in a second display area of the display screen;
and displaying related information of executable functions in a third display area of the display screen, wherein the executable functions are functions which can be executed in the next step when the regularity evaluation information meets preset conditions.
3. A prompting method as defined in claim 2, wherein the second display region includes at least one of:
a first sub-display area in which the pulse wave-related information includes the pulse wave waveform displayed;
and a second sub-display area for displaying the rhythm quantization parameter value.
4. A prompting method according to claim 3, wherein the rhythm quantization parameter value displayed in the second sub-display region includes at least one of: the pulse rate measurement method comprises the following steps of (1) obtaining a characteristic value, statistical analysis data of the characteristic value and a preset threshold, wherein the statistical analysis data comprise at least one of a difference value, a mean value, a standard deviation, a sum, a ratio, an integral, a maximum interval period, a minimum interval period, a pulse variation degree, a variation frequency, a maximum pulse rate value and a minimum pulse rate value; the characteristic values include: at least one of pulse interval, pulse amplitude, pulse area, pulse slope, pulse envelope, and pulse width; the preset threshold comprises a threshold corresponding to the characteristic value and/or the statistical analysis data of the characteristic value.
5. The presentation method as claimed in claim 4, wherein the first sub-display area and the second sub-display area are adjacent.
6. The presentation method according to claim 2, wherein the information related to the executable function includes guide information of the executable function and/or a function icon of the executable function.
7. A presentation method as claimed in claim 2, characterized in that, when there are at least two display areas, the at least two display areas are arranged next to each other in sequence.
8. The prompting method according to claim 1, wherein the obtaining of the characteristic value characterizing the rhythm of the pulse wave fluctuation from the pulse wave waveform comprises:
and performing feature extraction on the pulse wave signal by adopting at least one analysis technology of a time domain technology, a frequency domain technology and a nonlinear dynamics technology to obtain at least one feature value.
9. The prompting method according to claim 1, wherein the obtaining of the characteristic value characterizing the rhythm of the pulse wave fluctuation from the pulse wave waveform comprises:
extracting the characteristics of the pulse wave signals within a period of time or a plurality of periods to obtain at least one characteristic value;
analyzing the at least one characteristic value through a machine learning method to obtain the regularity evaluation information; and/or analyzing at least two characteristic values by a statistical analysis method and/or a machine learning method to obtain the regularity evaluation information.
10. The prompting method according to any one of claims 1-9, wherein after obtaining a feature value that characterizes a pulse wave fluctuation rhythm from the pulse wave waveform, the method further includes:
converting the obtained characteristic value into an intermediate characteristic value;
the identifying the fluctuation rhythm of the pulse wave according to the characteristic value to obtain the regularity evaluation information comprises the following steps:
and identifying the fluctuation rhythm of the pulse wave based on the intermediate characteristic value to obtain regularity evaluation information.
11. The prompting method of claim 10, wherein the intermediate feature value comprises a pulse sound feature value, and the converting the obtained feature value into the intermediate feature value comprises:
and converting the acquired characteristic value into a pulse sound characteristic value.
12. The prompting method of claim 11, wherein the converting the obtained feature value into a pulse sound feature value comprises:
determining the arrival time of the peak or the trough of the pulse according to the acquired characteristic value, and marking the peak or the trough at the arrival time of the peak or the trough;
and generating a pulse sound characteristic value according to the peak mark or the trough mark.
13. The prompting method of claim 1, wherein the type of regularity evaluation information includes a rule or an irregularity, the method further comprising:
and when the regularity evaluation information is irregular, outputting alarm information.
14. A prompting method as defined in claim 13, wherein the warning information includes at least part of the prompting information.
15. The prompting method according to claim 13, wherein the outputting alarm information when the regularity evaluation information is irregular includes:
and determining an alarm gear according to the acquired characteristic value, and controlling to output alarm information of the corresponding alarm gear, wherein the alarm gear comprises at least two gears.
16. A method for prompting regularity evaluation information is characterized by comprising the following steps:
acquiring a sensor signal through a sensor connected with a measuring object, wherein the sensor is a non-electrocardio sensor;
extracting a pulse wave signal of the measurement object from the sensor signal;
processing the pulse wave signal to extract a pulse wave waveform;
acquiring a characteristic value representing the fluctuation rhythm of the pulse wave according to the pulse wave waveform;
identifying the fluctuation rhythm of the pulse wave according to the characteristic value to obtain regularity evaluation information;
and outputting prompt information according to the regularity evaluation information.
17. A prompting method according to claim 16, wherein the device or system includes a display screen, and the prompting information includes at least one of:
the regularity evaluation information displayed in a first display area of the display screen;
displaying pulse wave related information in a second display area of the display screen;
and displaying related information of executable functions in a third display area of the display screen, wherein the executable functions are functions which can be executed in the next step when the regularity evaluation information meets preset conditions.
18. A prompting method according to claim 17, wherein the second display region includes one of:
a first sub-display area in which the pulse wave-related information includes the pulse wave waveform displayed;
and a second sub-display area for displaying the rhythm quantization parameter value.
19. The prompting method of claim 18, wherein the rhythm quantization parameter value displayed in the second sub-display region includes at least one of: the pulse rate measurement method comprises the following steps of (1) obtaining a characteristic value, statistical analysis data of the characteristic value and a preset threshold, wherein the statistical analysis data comprise at least one of a difference value, a mean value, a standard deviation, a sum, a ratio, an integral, a maximum interval period, a minimum interval period, a pulse variation degree, a variation frequency, a maximum pulse rate value and a minimum pulse rate value; the characteristic values include: at least one of pulse interval, pulse amplitude, pulse area, pulse slope, pulse envelope, and pulse width; the preset threshold comprises a threshold corresponding to the characteristic value and/or the statistical analysis data of the characteristic value.
20. A prompting method according to any one of claims 16-19, further comprising, after acquiring a characteristic value that characterizes a pulse wave fluctuation rhythm from the pulse wave waveform:
converting the obtained characteristic value into an intermediate characteristic value;
the identifying the fluctuation rhythm of the pulse wave according to the characteristic value to obtain the regularity evaluation information comprises the following steps:
and identifying the fluctuation rhythm of the pulse wave based on the intermediate characteristic value to obtain regularity evaluation information.
21. The prompting method of claim 20, wherein the intermediate feature value comprises a pulse sound feature value, and the converting the obtained feature value into the intermediate feature value comprises:
and converting the acquired characteristic value into a pulse sound characteristic value.
22. The prompting method of claim 21, wherein converting the obtained feature value into a pulse sound feature value comprises:
determining the arrival time of the peak or the trough of the pulse according to the acquired characteristic value, and marking the peak or the trough at the arrival time of the peak or the trough;
and generating a pulse sound characteristic value according to the peak mark or the trough mark.
23. The prompting method of claim 16, wherein the type of regularity evaluation information includes a rule or an irregularity, the method further comprising:
and when the regularity evaluation information is irregular, outputting alarm information.
24. A prompting method as defined in claim 23, wherein the warning information includes at least part of the prompting information.
25. A prompting method according to claim 23, wherein when the regularity evaluation information is irregular, outputting alarm information includes:
and determining an alarm gear according to the acquired characteristic value, and controlling to output alarm information of the corresponding alarm gear, wherein the alarm gear comprises at least two gears.
26. The prompting method of claim 16, wherein the sensor comprises at least one of a pressure sensor, an electromagnetic sensor, a sound sensor, and an acceleration sensor.
27. A monitoring device, characterized in that the monitoring device comprises:
a blood oxygen sensor for radiating light of different wavelengths into a tissue region of a subject and detecting a light signal transmitted through the tissue region;
and the processor is connected with the blood oxygen sensor and used for extracting photoplethysmography signals generated by light absorption of the tissue area from the light signals, processing the photoplethysmography signals to extract pulse wave waveforms, acquiring characteristic values representing pulse wave fluctuation rhythms according to the pulse wave waveforms, identifying the pulse wave fluctuation rhythms according to the characteristic values to obtain regularity evaluation information, and controlling and outputting prompt information according to the regularity evaluation information.
28. The monitoring device of claim 27, further comprising a display screen, wherein the processor controls the display screen to display the prompting information, and wherein the prompting information includes at least one of:
the regularity evaluation information displayed in a first display area of the display screen;
displaying pulse wave related information in a second display area of the display screen;
and displaying related information of executable functions in a third display area of the display screen, wherein the executable functions are functions which can be executed in the next step when the regularity evaluation information meets preset conditions.
29. The monitoring device of claim 28, wherein the second display area comprises a first sub-display area, and the pulse wave related information comprises the pulse wave waveform displayed in the first sub-display area and/or a rhythm quantization parameter value displayed in the second sub-display area.
30. The monitoring device of claim 29, wherein the second display region comprises a second sub-display region, and wherein the rhythm quantification parameter value displayed in the second sub-display region comprises at least one of: the pulse rate measurement method comprises the following steps of (1) obtaining a characteristic value, statistical analysis data of the characteristic value and a preset threshold, wherein the statistical analysis data comprise at least one of a difference value, a mean value, a standard deviation, a sum, a ratio, an integral, a maximum interval period, a minimum interval period, a pulse variation degree, a variation frequency, a maximum pulse rate value and a minimum pulse rate value; the characteristic values include: at least one of pulse interval, pulse amplitude, pulse area, pulse slope, envelope, and pulse width; the preset threshold comprises a threshold corresponding to the characteristic value and/or the statistical analysis data of the characteristic value.
31. The monitoring device of any one of claims 27-30, wherein the processor, after obtaining the feature value characterizing the pulse wave fluctuation rhythm according to the pulse wave waveform, is further configured to convert the obtained feature value into an intermediate feature value and identify the pulse wave fluctuation rhythm based on the intermediate feature value to obtain the regularity evaluation information.
32. The monitoring device of claim 21, wherein the intermediate characteristic value comprises a pulse sound characteristic value, and wherein the processor converts the acquired characteristic value into the intermediate characteristic value, comprising:
the processor determines the arrival time of the peak or the trough of the pulse according to the acquired characteristic value, marks the peak or the trough at the arrival time of the peak or the trough, and generates a pulse sound characteristic value according to the peak or the trough mark.
33. The monitoring device of claim 27, wherein the type of regularity evaluation information includes a rule or an irregularity, the processor further configured to output an alarm message when the regularity evaluation information is irregular.
34. The monitoring device of claim 33, wherein the alarm information includes at least a portion of a prompt message.
35. The monitoring device of claim 33, wherein the processor further determines an alarm gear according to the obtained characteristic value when the regularity evaluation information is irregular, and controls to output an alarm message corresponding to the alarm gear, wherein the alarm gear includes at least two gears.
36. The monitoring device of claim 27, wherein the monitoring device is a bedside monitoring device or a mobile monitoring device, the monitoring device further comprising a communication unit, and wherein the processor is further configured to send the prompting information to a department-level workstation device and/or an institution-level data center/institution-level emergency center management device via the communication unit, and output the prompting information via the department-level workstation device and/or the institution-level data center/institution-level emergency center management device.
37. The monitoring device of claim 27, wherein the monitoring device is a bedside monitoring device or a mobile monitoring device, the monitoring device further comprises a communication unit and an output unit, the processor is further configured to send one of the optical signal and the photoplethysmographic signal to a department-level workstation device and/or an institution-level data center/institution-level emergency center management device through the communication unit, the department-level workstation device and/or the institution-level data center/institution-level emergency center management device performs analysis to obtain the prompt information, and the monitoring device is further configured to receive the prompt information sent by the bedside monitoring device, the department-level workstation device, and/or the institution-level data center/institution-level emergency center management device and output the prompt information through the output unit.
38. A monitoring device, characterized in that the monitoring device comprises:
the sensor is connected with a measuring object to obtain a sensor signal, wherein the sensor is a non-electrocardio sensor;
a memory storing program instructions;
a processor for invoking the program instructions to perform the method of any of claims 16-26.
39. The monitoring device of claim 38, wherein the sensor comprises at least one of a pressure sensor, an electromagnetic sensor, a sound sensor, and an acceleration sensor.
40. A monitoring system, characterized in that the monitoring system comprises a monitoring device as claimed in any of the claims 27-37 or a monitoring device as claimed in any of the claims 38-39.
41. A computer readable storage medium having stored therein program instructions for execution by a computer upon invocation of the method according to any of claims 1-15 or the method according to any of claims 16-26.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113040771A (en) * | 2021-03-01 | 2021-06-29 | 青岛歌尔智能传感器有限公司 | Emotion recognition method and system, wearable device and storage medium |
| CN115040121A (en) * | 2022-06-23 | 2022-09-13 | 天津大学 | Dynamic spectrum data processing method using pulse wave rising edge optimization extraction |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113040771A (en) * | 2021-03-01 | 2021-06-29 | 青岛歌尔智能传感器有限公司 | Emotion recognition method and system, wearable device and storage medium |
| CN115040121A (en) * | 2022-06-23 | 2022-09-13 | 天津大学 | Dynamic spectrum data processing method using pulse wave rising edge optimization extraction |
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