CN112294269A

CN112294269A - Rhythm regularity prompting method, rhythm regularity displaying method, monitoring equipment and monitoring system

Info

Publication number: CN112294269A
Application number: CN201910697351.5A
Authority: CN
Inventors: 卿磊
Original assignee: Shenzhen Mindray Bio Medical Electronics Co Ltd
Current assignee: Shenzhen Mindray Bio Medical Electronics Co Ltd
Priority date: 2019-07-30
Filing date: 2019-07-30
Publication date: 2021-02-02

Abstract

The embodiment of the application discloses a rhythm regularity prompting method, a display method, a monitoring device, a monitoring system and a computer readable storage medium. The rhythm regularity prompting method comprises the following steps: acquiring pulse wave signals within a period of time; analyzing the pulse wave signals to obtain an analysis result; displaying an analysis result display area for a user to perform input operation; receiving an input operation of a user, and determining a judgment result confirmed by the user based on the input operation. The embodiment of the application can reduce the defect of low judgment accuracy when medical staff judge whether the pulse rule is regular or not by manually touching the pulse of the patient.

Description

Rhythm regularity prompting method, rhythm regularity displaying method, monitoring equipment and monitoring system

Technical Field

The present application relates to the field of medical technology, and in particular, to a rhythm regularity prompting method, a rhythm regularity displaying method, a monitoring device, a monitoring system, and a computer-readable storage medium.

Background

In emergency triage, clinic patient preliminary examination, etc., the patient vital signs are often measured, wherein the pulse is one of the important patient vital signs. When the vital sign measurement is carried out, medical personnel not only need to measure the parameters of the pulse of a patient, but also need to judge whether the pulse of the patient is regular or not so as to preliminarily screen whether the patient has the problems related to the heart or not. However, the current vital sign measuring device does not measure and judge whether the pulse of the patient is regular or not, so that medical staff needs to touch the pulse of the patient manually to judge whether the pulse of the patient is regular or not, and the medical staff is required to have abundant clinical experience to accurately judge, and some medical staff with low annual capital can not accurately judge, which affects the accuracy of diagnosis.

Disclosure of Invention

The embodiment of the application provides a rhythm regularity prompting method, a display method, a monitoring device, a monitoring system and a computer readable storage medium, which can improve the accuracy of judging whether the pulse is regular or not.

In a first aspect, an embodiment of the present application provides a rhythm regularity prompting method based on a pulse wave, where the method includes:

acquiring pulse wave signals within a period of time;

analyzing the pulse wave signals to obtain an analysis result, wherein the analysis result comprises waveform related information and regularity evaluation information, and the types of the regularity evaluation information comprise pulse regularity and pulse irregularity;

displaying an analysis result display area for a user to perform input operation, wherein the content displayed by the analysis result display area comprises the waveform related information, the regularity evaluation information and a determining sub-area supporting the user to perform input operation on the regularity evaluation information;

receiving an input operation of a user, and determining a judgment result confirmed by the user based on the input operation.

In some embodiments, the method further comprises: and outputting and displaying the judgment result confirmed by the user.

In some embodiments, the determining the sub-region comprises an identification that supports user confirmation or modification of the regularity evaluation information.

In some embodiments, the displaying an analysis result display area for a user to perform an input operation includes one of the following steps:

displaying the analysis result display area on a vital sign display interface; or

And displaying the analysis result display area on a new window popped up on the vital sign display interface.

In some embodiments, said displaying said analysis result display area on a vital signs display interface comprises:

hiding part of the content of the analysis result display area in a pull-down menu, a pull-up menu, a side pull menu or a suspension menu of the vital sign display interface, wherein an interface switching button for hiding and/or unfolding the pull-down menu, the pull-up menu, the side pull menu or the suspension menu is displayed in the analysis result display area;

and when receiving a call detail operation input by a user through clicking the interface switching button, expanding and displaying the hidden part of content.

In some embodiments, the method further comprises:

and if the judgment result confirmed by the user is irregular pulse, outputting and displaying a prompt interface for the user to select a subsequent work function.

In some embodiments, the follow-up work function prompt interface includes an identification of selection of one or more of the following: printing a pulse wave waveform, ordering an ECG exam, and/or ordering an ultrasound exam.

In some embodiments, the regularity evaluation information is displayed in the analysis result display area in a form of a text prompt, a graphic prompt, or a combination of text and graphic prompts.

In some embodiments, the method further comprises: after determining the judgment result confirmed by the user, storing the judgment result confirmed by the user; alternatively, the first and second electrodes may be,

displaying an icon for a user to click on to trigger a save operation, an

Responding to the click of the user, and saving the judgment result confirmed by the user.

In some embodiments, the waveform related information includes pulse wave waveforms and/or rhythm quantization parameters corresponding to the pulse wave signals in the period of time, wherein the rhythm quantization parameters include pulse interval, pulse amplitude, pulse width, pulse slope, pulse area, difference of pulse interval, difference of pulse amplitude, difference of pulse slope, difference of pulse area, mean of pulse interval, mean of difference of pulse interval, mean of pulse amplitude, mean of pulse slope, mean of pulse area, standard deviation of pulse interval, standard deviation of pulse amplitude, standard deviation of pulse wave slope, standard deviation of pulse area, fastest waveform segment, slowest waveform segment, waveform identifier, waveform interval measurement value, maximum waveform interval, minimum waveform interval, maximum pulse rate value, minimum pulse rate value, waveform variation degree, pulse width, standard deviation of pulse amplitude, pulse width, average of pulse interval, maximum pulse width, information of one or more of a waveform variation count, a waveform variation count threshold, and a waveform variation degree threshold.

In some embodiments, the analyzing the pulse wave signal to obtain an analysis result includes:

performing feature extraction on the pulse wave signals to obtain one or more feature quantities corresponding to the pulse wave signals;

and analyzing the characteristic quantity to obtain an analysis result.

In some embodiments, the content displayed by the analysis result display area further includes the one or more feature quantities.

In some embodiments, the feature quantity includes one or more of a frequency, a phase, an entropy value, and a complexity of a pulse wave corresponding to the pulse wave signal.

In some embodiments, the feature extracting the pulse wave signal includes:

and performing one or more of time domain feature extraction, frequency domain feature extraction and nonlinear dynamics feature extraction on the pulse wave signals.

In some embodiments, the time-domain feature extraction includes extracting one or more feature quantities of a pulse interval, a pulse amplitude, a pulse area, a pulse slope, or a pulse envelope of a pulse wave corresponding to the pulse wave signal.

In some embodiments, the frequency domain feature extraction includes converting the pulse wave signal to a frequency domain for analysis to extract frequency domain features of the pulse wave signal.

In some embodiments, the analyzing the feature quantity includes:

and performing one or more of new feature extraction, statistical analysis, feature combination analysis and machine learning analysis on the feature quantity.

In some embodiments, the performing new feature extraction on the feature quantity includes:

integrating the plurality of characteristic quantities to obtain new characteristic quantities; and

and analyzing the new characteristic quantity.

In some embodiments, the new characteristic quantity includes one or more of a pulse rate, a pulse sound, and a pulse magnitude of the pulse wave signal.

In some embodiments, the analyzing the feature quantity to obtain an analysis result includes:

judging whether the pulse rate or the pulse amplitude corresponding to the pulse wave signal in the period of time meets the characteristics of a preset rule or not:

when the pulse rate or the pulse amplitude corresponding to the pulse wave signal in the period of time meets the characteristics of the preset rule, determining that the regularity evaluation information is a pulse rule; alternatively, the first and second electrodes may be,

when the pulse rate or the pulse amplitude corresponding to the pulse wave signal in the period of time does not meet the characteristics of the preset rule, determining that the regularity evaluation information is pulse irregularity; and

obtaining an analysis result, wherein the analysis result at least comprises corresponding regularity evaluation information of the testee.

In some embodiments, the characteristic quantity is pulse interval information of a pulse wave corresponding to the pulse wave signal, wherein the pulse interval information includes a plurality of pulse intervals; the analyzing the characteristic quantity to obtain the analysis result comprises:

performing statistical analysis on the pulse interval information to obtain statistical quantity corresponding to the pulse interval information;

determining regularity evaluation information of the testee based on the statistic; and

and obtaining an analysis result, wherein the analysis result at least comprises the obtained regularity evaluation information.

In some embodiments, the characteristic quantity is pulse interval information of a pulse wave corresponding to the pulse wave signal, wherein the pulse interval information includes a plurality of pulse intervals;

the extracting the features of the pulse wave signals to obtain one or more feature quantities corresponding to the pulse wave signals includes:

extracting time domain characteristics of the pulse wave signals to obtain pulse interval information corresponding to the pulse wave signals;

the analyzing the characteristic quantity to obtain an analysis result comprises the following steps:

obtaining the difference value of continuous adjacent pulse intervals;

determining regularity evaluation information of the testee based on the difference value of the continuous adjacent pulse intervals; and

In some embodiments, the characteristic quantity is pulse wave interval information of a pulse wave of the pulse wave signal; the analyzing the characteristic quantity to obtain an analysis result comprises the following steps:

performing statistical analysis on the pulse sound interval information to obtain statistics corresponding to the pulse sound interval information;

In some embodiments, performing a statistical analysis on the characteristic quantities to obtain an analysis result includes:

analyzing the characteristic quantity to obtain statistic corresponding to the characteristic quantity;

judging whether the statistic meets a preset condition:

determining a pulse rule of the subject when the statistic satisfies the preset condition, or

When the statistic does not meet the preset condition, determining that the pulse of the testee is irregular;

and obtaining an analysis result, wherein the analysis result at least comprises corresponding regularity evaluation information of the testee.

In some embodiments, the statistics include one or more of a mean, a standard deviation, a variance, a maximum, a minimum, a difference of the maximum and the minimum, different types of proportion statistics, continuous feature statistics.

In some embodiments, the preset conditions include: one or more of a fixed condition, a sliding window condition, a dynamic condition, a fuzzy range condition, an adaptive condition.

In some embodiments, the feature binding analysis comprises:

combining different types of characteristic quantities in the plurality of characteristic quantities to obtain new characteristic quantities; and

the resulting new characteristic quantities are analyzed by combining different types of analysis methods.

A second aspect of the embodiments of the present application provides a method for displaying a display interface of a monitoring device, where the monitoring device includes a display screen for receiving an operation input by a user, and the display screen is used to display one or more display interfaces, and the method includes:

displaying a plurality of vital sign data item areas at least comprising an analysis result display area for a user to perform input operation in a vital sign display interface state, wherein the content displayed in the analysis result display area comprises waveform related information and regularity evaluation information of a pulse wave signal;

and displaying a determined sub-area supporting the input operation of the user aiming at the regularity evaluation information, wherein the type of the regularity evaluation information comprises pulse rules and pulse irregularities.

In some embodiments, the method further comprises:

and outputting and displaying a judgment result confirmed by the user based on the input operation of the user.

In some embodiments, the displaying a certain sub-region supporting a user to perform an input operation on the regularity evaluation information includes: displaying an identifier supporting a user to confirm or change the regularity evaluation information.

In some embodiments, said displaying, in the vital signs display interface state, a plurality of vital signs data item regions including at least an analysis result display region regarding the pulse wave signal includes one of:

displaying the analysis result display area on the vital sign display interface; or

In some embodiments, said displaying said analysis result display area on said vital signs display interface comprises:

In some embodiments, the method further comprises: and if the judgment result confirmed by the user is irregular pulse, outputting and displaying a prompt interface for the user to select a subsequent work function.

In some embodiments, the follow-up work function prompt interface includes an identification of selection of one or more of the following:

printing a pulse wave waveform, ordering an ECG exam, and/or ordering an ultrasound exam.

In some embodiments, the waveform related information includes pulse wave waveforms and/or rhythm quantization parameters corresponding to the pulse wave signals acquired within the period of time, where the rhythm quantization parameters include pulse interval, pulse amplitude, pulse width, pulse slope, pulse area, difference of pulse interval, difference of pulse amplitude, difference of pulse slope, difference of pulse area, mean of pulse interval, mean of pulse amplitude, mean of pulse slope, mean of pulse area, standard deviation of pulse interval, standard deviation of pulse amplitude, standard deviation of pulse wave slope, standard deviation of pulse area, fastest waveform segment, slowest waveform segment, waveform identifier, waveform interval measurement value, maximum waveform interval, minimum waveform interval, maximum pulse rate value, minimum pulse rate value, pulse rate value, Information of one or more of a waveform variation degree, a waveform variation frequency threshold value, and a waveform variation degree threshold value.

In some embodiments, the method further includes displaying one or more feature quantities of the pulse wave signal, which are obtained by feature extraction of the pulse wave signal, in the analysis result display area.

A third method according to an embodiment of the present application provides a monitoring device, including:

the device comprises at least one parameter measuring circuit, at least one sensor interface and at least one parameter measuring circuit, wherein the at least one parameter measuring circuit is connected with an externally inserted sensor accessory through the sensor interface so as to acquire physiological signals of a testee, and the physiological signals at least comprise pulse wave signals;

a display screen for serving as a display and input device;

a processor which, when executing the computer program, implements the following:

acquiring pulse wave signals acquired by the parameter measurement circuit within a period of time;

controlling the display screen to display an analysis result display area for a user to perform input operation, wherein the content displayed in the analysis result display area comprises waveform information, regularity evaluation information and a determined sub-area supporting the user to perform input operation on the regularity evaluation information, and controlling the display to display prompt information representing irregular pulse in the analysis result display area at least when the regularity evaluation information is irregular pulse;

and receiving input operation input by a user through the display, and determining a judgment result confirmed by the user based on the input operation.

In some embodiments, the processor further controls the display screen to display the user-confirmed determination result.

In some embodiments, the displaying of the certain sub-region supporting the user's input operation for the regularity evaluation information includes displaying an identifier supporting the user's confirmation or modification of the regularity evaluation information.

In some embodiments, the processor performs the controlling the display screen to display the analysis result display area by one of:

controlling the display screen to display the analysis result display area on a vital sign display interface; or

And controlling the display screen to display the analysis result display area in a new window popped up on the vital sign display interface.

In some embodiments, the processor performs the controlling of the display screen to display the analysis result display area on the vital signs display interface by:

controlling the display screen to hide part of the content of the analysis result display area in a pull-down menu, a pull-up menu, a side pull menu or a suspension menu of the vital sign display interface, wherein an interface switching button which hides and/or unfolds the pull-down menu, the pull-up menu, the side pull menu or the suspension menu is displayed in the analysis result display area;

and when the display screen receives a calling detail operation input by clicking the interface switching button by a user, controlling the analysis result display area to display the hidden part of content in an expanding way.

In some embodiments, if the determined result is irregular pulse, the processor further controls the display screen to output and display a prompt interface for the user to select a subsequent work function.

In some embodiments, the processor is further configured to:

after determining the judgment result confirmed by the user, storing the judgment result confirmed by the user; alternatively, the first and second electrodes may be,

controlling the display screen to display an icon for a user to click to trigger a save operation, and,

and responding to the click of the user, and saving the judgment result confirmed by the user.

In some embodiments, the waveform related information includes pulse wave waveforms and/or rhythm quantization parameters corresponding to the pulse wave signals in the period of time, wherein the rhythm quantization parameters include the characteristic quantity, pulse intervals, pulse amplitudes, pulse widths, pulse slopes, pulse areas, pulse interval differences, pulse amplitude differences, pulse slope differences, pulse area differences, pulse interval mean values, pulse interval difference mean values, pulse amplitude mean values, pulse slope mean values, pulse area mean values, pulse interval standard deviations, pulse amplitude standard deviations, pulse wave slope standard deviations, pulse area standard deviations, fastest waveform segments, slowest waveform segments, waveform identifiers, waveform interval measurement values, maximum waveform intervals, minimum waveform intervals, maximum pulse rate values, minimum pulse rate values, pulse wave slope standard deviations, pulse area standard deviations, fastest waveform segments, waveform identifiers, waveform interval measurement values, maximum waveform intervals, minimum pulse rate values, pulse rate values, Information of one or more of a waveform variation degree, a waveform variation frequency threshold value, and a waveform variation degree threshold value.

In some embodiments, the processor performs the analyzing of the pulse wave signal to obtain an analysis result by:

and analyzing the characteristic quantity to obtain an analysis result.

In some embodiments, the processor further controls the analysis result display area to display the one or more feature quantities.

In some embodiments, the processor performs the feature extraction of the pulse wave signals by one or more of: and performing time domain feature extraction, frequency domain feature extraction and nonlinear dynamics feature extraction on the pulse wave signals.

In some embodiments, the processor performs the time domain feature extraction on the pulse wave signal by:

and extracting one or more characteristic quantities in waveform interval, amplitude, area, slope or envelope of the pulse wave corresponding to the pulse wave signal.

In some embodiments, the processor performs the frequency domain feature extraction by: and converting the pulse wave signal into a frequency domain for analysis so as to extract the frequency domain characteristics of the pulse wave signal.

In some embodiments, the processor performs the analyzing the feature quantity by one or more of: and carrying out new feature extraction, statistical analysis, feature combination analysis and machine learning analysis on the feature quantity.

In some embodiments, the processor performs new feature extraction on the feature quantity by:

and analyzing the new characteristic quantity.

In some embodiments, the processor performs the analyzing of the feature quantity to obtain an analysis result by:

when the pulse rate or the pulse amplitude corresponding to the pulse wave signal in the period of time meets the characteristics of the preset rule, determining the pulse rule of the testee; alternatively, the first and second electrodes may be,

when the pulse rate or the pulse amplitude corresponding to the pulse wave signal in the period of time does not meet the characteristics of the preset rule, determining that the pulse of the testee is irregular; and

In some embodiments, the characteristic quantity is pulse interval information of a pulse wave corresponding to the pulse wave signal, wherein the pulse interval information includes a plurality of pulse intervals; the processor analyzes the characteristic quantity in the following way to obtain an analysis result:

the processor performs the feature extraction on the pulse wave signals to obtain one or more feature quantities corresponding to the pulse wave signals by:

the processor analyzes the characteristic quantity in the following way to obtain an analysis result:

performing statistical analysis on the pulse interval information to obtain a difference value of continuous adjacent pulse intervals;

determining regularity evaluation information of the testee based on the difference value of the continuous adjacent pulse intervals;

In some embodiments, the characteristic quantity is pulse wave interval information of a pulse wave of the pulse wave signal; the processor analyzes the characteristic quantity in the following way to obtain an analysis result:

In some embodiments, the processor performs the statistical analysis of the feature quantity to obtain an analysis result by:

judging whether the statistic meets a preset condition:

when the statistic satisfies the preset condition, determining the pulse rule of the testee; alternatively, the first and second electrodes may be,

In some embodiments, the processor performs the feature-binding analysis of the feature quantities by:

A fourth aspect of the embodiments of the present application provides a monitoring system, including a monitoring device and a central station, where the monitoring device includes a display screen used as a display and input device, where:

the monitoring equipment is used for acquiring pulse wave signals within a period of time and transmitting the pulse wave signals to the central station;

the central station is used for analyzing the pulse wave signals to obtain an analysis result and transmitting the analysis result to the monitoring equipment, wherein the analysis result comprises waveform related information and regularity evaluation information, and the type of the regularity evaluation information comprises pulse regularity and pulse irregularity;

the monitoring device is further configured to:

controlling the display screen to display an analysis result display area for a user to perform input operation, wherein the content displayed by the analysis result display area comprises waveform related information, regularity evaluation information and a determining sub-area supporting the user to perform input operation on the regularity evaluation information;

and receiving input operation input by a user through the display screen, and determining a judgment result confirmed by the user based on the input operation.

A fifth aspect of embodiments of the present application provides a computer-readable storage medium for storing a computer program for electronic data exchange, wherein the computer program causes a computer to perform some or all of the steps as described in any of the methods of the first or second aspects of embodiments of the present application.

The rhythm regularity prompting method, the rhythm regularity displaying method, the rhythm monitoring device, the rhythm monitoring system and the computer readable storage medium analyze the obtained pulse wave signals within a period of time to obtain the type of regularity evaluation information corresponding to the pulse wave signals, so that the defect of low judgment accuracy when medical staff judge whether the pulse is regular or not by manually touching the pulse of a patient can be reduced, and the accuracy of judging whether the pulse is regular or not can be improved.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

FIG. 1 is a block diagram of the hardware of a multi-parameter monitor according to an embodiment of the present application.

Fig. 2 is a flowchart illustrating steps of a method for prompting regularity in a rhythm in accordance with an embodiment of the present application.

FIG. 3 is a schematic diagram illustrating a waveform of one pulse in a pulse wave signal according to an embodiment of the present application.

Fig. 4 is a schematic diagram showing an analysis result in an embodiment of the present application.

Fig. 5 is a schematic diagram showing an analysis result in a further embodiment of the present application.

Fig. 6 is a schematic diagram of an analysis result of a hidden portion in an embodiment of the present application.

Fig. 7 is a schematic diagram illustrating an analysis result of a hidden portion in an embodiment of the present application.

Fig. 8 is a schematic diagram showing an analysis result in an embodiment of the present application.

Fig. 9 is a hardware block diagram of a monitoring system according to an embodiment of the present application.

Detailed Description

In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

The terms "first," "second," and the like in the description and claims of the present application 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, article, or apparatus.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.

The following describes embodiments of the present application in detail.

The medical staff judges whether the pulse is regular or not by manually touching the pulse of the patient and determines the irregular information of the patient according to the regular pulse, and the accuracy of the judgment may depend on the proficiency of the medical staff. In the embodiment of the present application, the monitoring device or central station 211 (shown in fig. 9) can determine whether the pulse of the patient is regular or not based on the acquired pulse wave signal to improve the accuracy of the regularity evaluation information for confirming the patient, wherein the monitoring device includes, but is not limited to, a multi-parameter monitor 10 (shown in fig. 1), a bedside monitor 212 (shown in fig. 9), a portable monitoring device 213 (shown in fig. 9) and other devices having a vital sign measurement function.

Referring to fig. 1, a hardware block diagram of a multi-parameter monitor according to an embodiment of the present application is shown. The multi-parameter monitor 10 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 112 at least comprises at least one parameter measuring circuit of an electrocardiosignal parameter measuring circuit, a body temperature parameter measuring circuit, a blood oxygen parameter measuring circuit, a noninvasive 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 detection of physiological parameters such as electrocardio, blood oxygen, blood pressure, body temperature and the like. The parameter measurement circuit 112 obtains the acquired physiological parameter signal by connecting the sensor accessory 111. The parameter measurement circuit 112 may include one or more physiological parameter measurement circuits, and the parameter measurement circuit 112 may be, but is not limited to, a physiological parameter measurement circuit (module), a human physiological parameter measurement circuit (module) or a sensor for acquiring a human physiological parameter, and the like. The parameter measurement circuit 112 obtains the physiological sampling signal related to the testee obtained by the external physiological parameter sensor accessory through the expansion interface, and obtains the physiological data 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 113 and is about how to acquire the physiological parameter to an external physiological parameter monitoring accessory through a corresponding interface, so as to realize monitoring control on the physiological parameter of the testee.

The multi-parameter monitor 10 includes one or more of a display screen 114, an alarm circuit 116, an input interface circuit 117, an external communication and power interface 115. The main control circuit 113 is used for coordinating and controlling the boards, circuits and devices in the multi-parameter monitor 10. The master control circuitry 113 may include at least one processor 101 and at least one memory 103. Of course, the main control circuit 113 may further include at least one of the power management module 105, the power IP module, the interface conversion circuit, and the like. The power management module 105 is used to control the power on/off of the whole device, the power-on timing sequence of each power domain inside the board, 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 that is frequently called repeatedly with a PCB diagram and is solidified into a single power supply module, that is, an input voltage is converted 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. The power supply IP module can be single-path or multi-path. 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 this embodiment, the main control circuit 113 is used to control data interaction between the parameter measuring circuit 112 and the communication interface circuit and transmission of control signals, and transmit physiological data to the display screen 114 for display, or receive user control instructions input from the display screen or physical input interface circuits such as a keyboard and a key, and also output control signals on how to acquire physiological parameters. The alarm circuit 116 may be an audible and visual alarm circuit. The main control circuit completes the calculation of the physiological parameters and can send the calculation results and the waveforms of the parameters to a host (such as a host with a display screen, a PC, a central station and the like) through the external communication and power interface 115. The external communication and power interface 115 may be one or a combination of an Ethernet (Ethernet), a Token Ring (Token Ring), a Token Bus (Token Bus), and a local area network interface (lan interface) formed by a backbone Fiber Distribution Data Interface (FDDI) as the three networks, one or a combination of wireless interfaces such as infrared, bluetooth, wifi, WMTS communication, or one or a combination of wired data connection interfaces such as RS232 and USB. 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 machine can also be communication equipment, such as a mobile phone, and the multi-parameter monitor 10 transmits data to the mobile phone supporting bluetooth communication through the bluetooth interface, so as to realize remote transmission of the data; or receive data transmitted by a mobile phone supporting Bluetooth communication.

In one embodiment, the multi-parameter monitor 10 can be disposed outside the monitor housing as an independent external parameter-inserting module, and can be a plug-in monitor formed by a host (including a main control board) inserted into the monitor as a part of the monitor, or can be connected to the host (including the main control board) of the monitor through a cable, and the external parameter-inserting module is 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.

Referring to fig. 2, a flowchart of steps of a method for prompting regularity of a program in an implementation of the present application is shown. The rhythm regularity prompting method comprises the following steps:

step 100, acquiring a pulse wave signal within a period of time.

In this embodiment, the parameter measurement circuit 112 may obtain the sensing signal related to the pulse of the user through the sensor accessory 111, and perform signal amplification, a/D conversion, filtering, and the like on the sensing signal to obtain the pulse wave signal. The sensor attachment 111 may include piezoresistive, photoelectric, piezoelectric pulse sensors. The solid piezoresistive sensor adopts a rigid probe, reflects pulse change according to piezoresistive effect, and further generates a pulse wave signal. The photoelectric sensor is designed based on the principle that the transmittance of light in tissue is greater than that in blood, and receives light of a pulsating change transmitted through tissue and converts the light into electrical information to obtain a pulse wave signal related to a tissue photoplethysmogram and the like. The piezoelectric sensor adopts an electromechanical film or a piezoelectric film as a sensing element, and indirectly measures the deformation of the skin surface in the pulse beating process according to the piezoelectric effect so as to obtain a corresponding pulse wave signal. In other embodiments, the pulse wave signal may also be generated by a device having a function of measuring pulse, such as a watch bracelet.

For example, in the case of a light sensor, the light sensor can emit LED light to the skin, receive light reflected back through skin tissue, convert the light into an electrical signal, and convert the electrical signal into a digital signal through a/D. When light shines through skin tissues and then is reflected to the photosensitive sensor, because the light absorption of muscles, bones, veins and other connecting tissues is basically unchanged, the light absorption of blood in an artery is changed under the flowing condition, the light absorption of the artery is changed, the light absorption of other tissues is basically unchanged, further obtained signals can comprise Direct Current (DC) signals and Alternating Current (AC) signals, the blood oxygen saturation (SpO2) reflecting the flowing characteristics of the blood can be obtained by extracting the AC signals in the signals, and a pulse wave signal is obtained based on the flowing characteristics of the blood.

In this embodiment, since the pulse of the pulse wave has periodicity, when the parameter measuring circuit 112 continuously measures the pulse wave of the subject, the parameter measuring circuit 112 can obtain a pulse wave signal containing a plurality of pulse periods.

And 102, analyzing the pulse wave signals to obtain an analysis result.

In this embodiment, the processor 101 may analyze the pulse wave signal to obtain a corresponding analysis result, where the analysis result includes waveform-related information and regularity evaluation information. In analyzing the measured pulse wave signals, the processor 101 may analyze the entire pulse wave signals during the measurement or select a time period for the pulse wave signals to analyze.

In this embodiment, the processor 101 may perform feature extraction on the pulse wave signal to obtain one or more feature quantities corresponding to the pulse wave signal.

The waveform related information includes a pulse wave waveform and/or a rhythm quantization parameter corresponding to the pulse wave signal within a period of time.

The pulse wave form may include at least a pulse wave form when the regularity evaluation information is that the pulse is irregular, a pulse wave form when the regularity evaluation information is that the pulse is regular, and a pulse wave form obtained in real time in a process of acquiring 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.

Fig. 3 is a schematic diagram showing a waveform of one pulse in the pulse wave signal according to an embodiment of the present application. Each pulse may include a plurality of feature points: the characteristic point B represents the aortic valve opening point, the characteristic point C is the systolic highest pressure point, the characteristic point D is the aortic dilation pressure reduction point, the characteristic point E is the left ventricular diastolic starting point, the characteristic point F is the start point of the dicrotic wave, and the characteristic point G is the dicrotic wave highest pressure point. The characteristic point E is the minimum slope point between the characteristic point D and the characteristic point F, the characteristic point C is the main peak of a pulse, the characteristic point G is the secondary peak of a pulse, and the characteristic point B is the trough of a pulse.

In some embodiments, the rhythm quantification parameter includes information of one or more of a pulse interval, a pulse magnitude, a pulse width, a pulse slope, a pulse area, a difference in pulse interval, a difference in pulse magnitude, a difference in pulse slope, a difference in pulse area, a mean in pulse interval, a mean in pulse magnitude, a mean in pulse slope, a mean in pulse area, a standard deviation in pulse interval, a standard deviation in pulse magnitude, a standard deviation in pulse wave slope, a standard deviation in pulse area, a fastest waveform segment, a slowest waveform segment, a waveform identification, a waveform interval measurement, a maximum waveform interval, a minimum waveform interval, a maximum pulse value, a minimum pulse value, a waveform variation, a number of waveform variations threshold, a waveform variation threshold.

Wherein maximum pulse rate/minimum pulse rate is defined: 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 pulse interval refers to a time interval between two single pulses, and may be a time interval between a peak and a peak (e.g., a feature point C on one pulse and a feature point C on another pulse), a valley and a valley (e.g., a feature point B on one pulse and a feature point B on another pulse), or a time interval between any corresponding points on two single pulses. The spaces may or may not be contiguous. The single pulse in this context may be a pulse wave, or may be a single pulse acquired by applying other forms. The pulse amplitude refers to the difference between the wave crest and the wave trough, the pulse slope refers to the slope at any position of the rising section and the falling section of the pulse wave, the pulse area refers to the integral of the pulse wave between two adjacent wave troughs or between the start and the end of a single pulse in time, the pulse width refers to the time length from the start to the end of the single pulse, and the pulse envelope refers to: the envelope formed by the connection of the peaks and the peaks (or the valleys and the valleys). The waveform morphology feature statistic is an analysis result of the waveform morphology feature quantity 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 sum of pulse intervals, a ratio of pulse intervals, a difference value of pulse intervals, a mean value of pulse interval differences, a standard deviation of pulse intervals, a mean value of pulse widths, a sum of pulse widths, a ratio of pulse widths, a difference value of pulse widths, a standard deviation of pulse widths, a difference value of pulse amplitudes, a mean value of pulse amplitudes, a standard deviation of pulse amplitudes, a difference value of pulse slopes, a mean value of pulse slopes, a standard deviation of pulse slopes, a difference value of pulse areas, a mean value of pulse areas, a standard deviation of pulse areas, 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 value of the pulse intervals refers to the difference value of the pulse intervals, the mean value of the pulse interval difference value refers to 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 mean value of the pulse amplitudes refers to the mean value of the pulse amplitudes in a period of time, the standard deviation of the pulse amplitudes refers to the standard deviation of the pulse amplitudes in a period of time, the difference value of the pulse areas refers to the difference value of the pulse areas, the mean value of the pulse areas refers to the mean value of 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 mean value of the pulse widths refers to the mean value of the pulse width difference values in a period of time, the sum of the pulse widths refers to the sum of the pulse widths, the ratio of the pulse widths refers to the ratio of different pulse widths, the difference value of the pulse widths refers to the difference value of the pulse widths, and the standard deviation of the pulse widths refers to the standard deviation of the pulse widths in a period of time.

The variation-related quantity is a measure reflecting changes of the waveform morphological feature quantity, the waveform morphological feature statistic, the pulse wave frequency-related quantity, the frequency domain feature and the nonlinear dynamics feature over a period of time, 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 waveform form characteristic quantity, the statistic of the waveform form characteristic quantity, pulse wave frequency related quantity, frequency domain characteristic, nonlinear dynamics characteristic and the like. In one embodiment, the degree of variation may be one of a waveform morphology feature quantity, a pulse wave frequency related quantity, a frequency domain feature and a nonlinear dynamics feature, and a difference between a statistic of the waveform morphology feature quantity, 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.

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 quantity, a statistic of the waveform shape feature quantity, a pulse wave frequency correlation quantity, a frequency domain feature, and a nonlinear dynamics feature exceed 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 may further include at least one of a frequency domain feature, a nonlinear dynamics feature, a pulse frequency related quantity, a waveform morphology feature quantity, a statistic of the waveform morphology feature quantity, and a variation related quantity. The frequency domain features include at least one of spectral features, spectral feature statistics, power spectral features, power spectral feature statistics, and the like. The frequency domain features include at least one of spectral features, spectral feature statistics, power spectral features, power spectral feature statistics, and the like. The spectrum characteristics may include: one of 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 single-frequency spectrum feature statistics, multi-frequency spectrum feature statistics and other feature information, wherein the single-frequency spectrum feature statistics comprise: within a single spectrum, the most value, mean value, ratio, difference, sum, 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 value, standard deviation, etc. of the spectral interval differences. The multi-spectral feature statistics include: the maximum value, the mean value, the ratio, the difference value, the sum, 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 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 sum, the standard deviation, the distribution statistics and the like of the characteristics such as the power spectrum peak amplitude, the power spectrum peak number, the power spectrum peak position, the power spectrum interval, the power spectrum amplitude, the power spectrum area, the power spectrum slope and the like corresponding to the power spectrums in different time periods within a period of time, and the statistical analysis value of the power spectrum characteristic statistics, such as the standard deviation of the maximum power spectrum peak position difference value among the power spectrums, the number of the maximum power spectrum peak position difference value among the power spectrums exceeding a preset value and the like.

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 pulse-frequency related quantity comprises the pulse rate and a statistically analyzed quantity of the pulse rate, for example the statistically analyzed quantity of the pulse rate comprises a maximum pulse rate value and/or a minimum pulse rate value. The waveform morphological feature at least comprises one of pulse interval, pulse amplitude, pulse width, pulse area, pulse slope, pulse envelope, etc.

In some embodiments, the regularity evaluation information may be given based on a comparison between the identified rhythm quantization parameter and a corresponding preset threshold, for example, the pulse rhythm regularity evaluation information may be given based on a comparison between the aforementioned variability degree and a corresponding threshold, a comparison between the aforementioned variability number and a corresponding threshold, or a comparison between the aforementioned variability degree and the aforementioned variability number and a corresponding threshold, respectively, and the pulse wave may be determined to be regular or irregular. In some embodiments, comparison with a threshold value may be made in accordance with one of the identified characteristic quantities of the aforementioned rhythm quantization parameters, thereby giving regularity evaluation information; alternatively, it is also possible to perform a plurality of pieces of combined judgment based on comparison between two or more (including two) feature quantities of the identified rhythm quantization parameters and corresponding threshold values, respectively, thereby giving evaluation information of the pulse rhythm regularity. Secondly, in some embodiments, at least one feature quantity in the identified rhythm quantization parameter is compared with a preset threshold value for 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 feature quantity in the identified rhythm quantization parameter is compared with a preset threshold value multiple times in succession in a period of time, when the number of times of representing the pulse wave regularity in the multiple comparison results satisfies the pulse wave regularity standard, an evaluation result of the pulse wave regularity is output, and when the number of times of representing the pulse wave irregularity in the multiple comparison results satisfies the pulse wave irregularity standard, 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 quantities. Obtaining the regularity evaluation information according to the statistical analysis data, including:

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 set to be M times, and if the comparison result shows that the variability and/or the variability times of the continuously counted pulse wave signals greater than or equal to M 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 M1 times, the result of the M1-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 M1 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 this embodiment, the processor 101 is configured to perform feature extraction manners, such as time domain feature extraction, frequency domain feature extraction, and nonlinear dynamics feature extraction, on the pulse wave signal to obtain the one or more feature quantities. Wherein, the feature quantity obtained by extracting the pulse wave signal from the time domain feature includes but is not limited to the pulse interval, the pulse amplitude, the pulse area, the pulse slope, the pulse width or the pulse envelope of the pulse wave corresponding to the pulse wave signal; the frequency domain feature extraction includes converting the pulse wave signal into the frequency domain for analysis (such as fourier transform), so as to extract the feature quantity including but not limited to the frequency domain feature of the pulse wave signal; the nonlinear dynamical feature extraction includes extracting feature quantities including, but not limited to, entropy and complexity corresponding to the pulse wave signal.

Furthermore, the corresponding nonlinear dynamics characteristic calculation result can be compared with the corresponding preset threshold value to obtain the pulse wave related information and/or the regularity evaluation information. For example, the calculation result of the nonlinear dynamics characteristic quantity 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 characteristic quantity analysis, the pulse wave waveform related information, such as the pulse interval, can be determined by utilizing methods of time domain analysis, frequency domain analysis, machine learning and the like, and then output and displayed. 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.

The processor 101 is further configured to analyze the extracted feature quantity to obtain regularity evaluation information (or determine whether the pulse wave is regular or not) of the pulse wave signal, where the type of the regularity evaluation information includes pulse regularity and pulse irregularity.

In this embodiment, the processor 101 may perform one or more of new feature extraction, statistical analysis, feature combination analysis, and machine learning analysis on the feature quantity.

When performing new feature extraction on the feature quantity, the processor 101 may integrate a plurality of feature quantities to obtain one or more new feature quantities of pulse rate, pulse sound, and pulse amplitude of the pulse wave signal. The processor 101 may determine regularity evaluation information of the pulse wave signal based on the acquired new feature quantity.

In one embodiment, the processor 101 performs new feature extraction on the feature quantity of the pulse wave signal, including but not limited to obtaining a pulse rate according to the pulse period extraction of the pulse wave signal. For example, the processor 101 may determine the number N of Pulse periods of the Pulse wave contained in t seconds, at which time the processor 101 may determine that the Pulse Rate (PR) of the Pulse wave signal is N × 60/t (in units of times per minute), i.e., representing the number of Pulse beats in 1 minute.

In this embodiment, the processor 101 may determine the regularity evaluation information of the pulse wave signal based on a fixed condition or a dynamic condition.

Under a fixed condition, the processor 101 may sample the pulse wave signal based on a fixed time interval (e.g. 5 seconds), and obtain a pulse rate Pt corresponding to each sampling point. At this time, the pulse rate corresponding to the pulse wave signal can be represented as (P1, P2, P3, … Pt). The processor 101 determines whether the pulse rate corresponding to the pulse wave signal satisfies a characteristic of a first predetermined rule. When the pulse rate corresponding to the pulse wave signal does not satisfy the characteristics of the first preset rule, the processor 101 determines that the pulse of the user (or the subject) is irregular; when the pulse rate corresponding to the pulse wave signal satisfies the characteristic of the first preset rule, the processor 101 determines the pulse rule of the user (or the subject). For example, the processor 101 may determine whether the pulse rate Pt corresponding to each sampling point is within a first predetermined range, and when the pulse rate Pt corresponding to each sampling point is within the first predetermined range, the processor 101 determines the pulse rule of the subject; when the pulse rate Pt corresponding to at least one or a first preset number of sampling points is not within a first preset range, the processor 101 determines that the pulse of the subject is irregular.

Under dynamic conditions, the processor 101 may sample the pulse wave signal based on a variable time interval (e.g. 5, 10, 15, 5, 10 seconds, etc.), and obtain a pulse rate Pt corresponding to each sampling point. The processor 101 may also determine the regularity evaluation information of the pulse rate corresponding to the pulse wave signal within a period of time according to the characteristics of the preset rule. Specifically, the regularity evaluation information for determining the pulse rate corresponding to the pulse wave signal under a fixed condition may be referred to. In an embodiment, the processor 101 may further determine whether the pulse rate corresponding to the pulse wave signal satisfies a predetermined rule based on a sliding window condition, a fuzzy range condition, an adaptive condition, and the like.

In one embodiment, the processor 101 can obtain the pulse magnitude Cn corresponding to each pulse period in the pulse wave corresponding to the pulse wave signal. At this time, the pulse amplitude corresponding to the pulse wave signal can be represented as (C1, C2, C3, … Cn). The processor 101 determines whether the pulse amplitude corresponding to the pulse wave signal satisfies a characteristic of a second predetermined rule. When the pulse amplitude corresponding to the pulse wave signal does not meet the characteristics of a second preset rule, the processor 101 determines that the pulse of the person to be tested is irregular; when the pulse amplitude corresponding to the pulse wave signal satisfies the feature of the second preset rule, the processor 101 determines the pulse rule of the subject. For example, the processor 101 may determine whether the pulse amplitudes Cn corresponding to each pulse period are all within a second preset range, and when the pulse amplitudes Cn corresponding to each pulse period are all within the second preset range, the processor 101 determines the pulse rule of the subject; when the pulse amplitude Cn corresponding to at least one or a second preset number of pulse periods is not within a second preset range, the processor 101 determines that the pulse of the subject is irregular.

In one embodiment, the processor 101 may perform statistical analysis on the feature quantities (such as pulse interval, pulse amplitude, pulse area, pulse slope, pulse width, pulse envelope, frequency domain features, entropy, and complexity) to determine the regularity evaluation information of the pulse wave signal.

The processor 101 analyzes the feature quantity to obtain a statistic corresponding to the feature quantity. The processor 101 determines whether the statistic satisfies a preset condition. When the statistic satisfies the preset condition, the processor 101 determines the pulse rule of the testee; when the statistic does not satisfy the preset condition, the processor 101 determines that the subject's pulse is irregular. Thus, in some embodiments, the regularity evaluation information may be determined after statistical analysis is performed on the feature quantities acquired from the pulse wave signals to obtain statistical quantities. In some embodiments, the statistical quantity may be one or more of a difference value, a mean value, a standard deviation, a sum, a ratio, an integral, a variance, a difference value between a maximum value and a minimum value, a maximum interval period, a minimum interval period, a pulse variability, a variability threshold, a maximum pulse rate value, a minimum pulse rate value, and different types of proportion statistics and continuous feature statistics, which are derived based on the aforementioned feature quantities, and the aforementioned description is specifically combined.

Specifically, the statistic obtained by performing statistical analysis on the feature quantity obtained from the pulse wave signal refers to an analysis result of waveform morphology feature quantity 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 slopes, a mean value of pulse slopes, a standard deviation of pulse slopes, a difference value of pulse areas, a mean value of pulse areas, a standard deviation of pulse areas, and the like. For example, the processor 101 may obtain a waveform interval or a pulse interval Hn of any two adjacent pulse periods in the pulse wave signal to obtain pulse interval information of the corresponding pulse wave, where the pulse interval information may be represented as (H1, H2, H3, …, Hn). Wherein the average value can be expressed as: mean (H1, H2, H3, …, Hn) ═ (H1+ H2+ H3+ … + Hn)/n; the standard deviation and the variance can be obtained based on the mathematical operation related to the average value; max ═ Maximum Max (H1, H2, H3, …, Hn); minimum Min ═ Minimum (H1, H2, H3, …, Hn); the difference between the maximum and minimum values is: Max-Min. The processor 101 may classify the pulse interval information based on the size of the waveform interval, and obtain the number of pulse intervals included in each type, for example, the pulse intervals in the first range are of the first type, and the pulse intervals in the second range are of the second type. The processor 101 can determine the ratio of the number of the pulse intervals contained in each type to the total number of the pulse intervals, and accordingly determine the regularity evaluation information of the pulse of the testee; alternatively, the processor 101 may determine whether the number of pulse intervals included in the target category reaches a threshold value, and thereby determine the regularity evaluation information of the subject's pulse. The processor 101 may perform statistical analysis on other characteristic quantities, and the specific analysis is similar to the above statistical analysis of waveform intervals, and therefore, the detailed description thereof is omitted here.

In one embodiment, the processor 101 may obtain the difference value of the consecutive adjacent pulse intervals, and obtain the regularity evaluation information of the pulse of the subject based on the difference value of the consecutive adjacent pulse intervals. For example, the difference between consecutive adjacent pulse intervals can be expressed as (K1, K2, K3, …, Kn), where Kn ═ Hn-1-Hn. When the difference between consecutive adjacent pulse intervals is not within the target range, the processor 101 may determine that the subject's pulse is irregular; when the difference between consecutive adjacent pulse intervals is within the target range, the processor 101 may determine the pulse rule of the subject. In one embodiment, the processor 101 may use the number of times that the difference between the finger pulse intervals (K1, K2, K3, …, Kn) exceeds a predetermined value as the variation number of the pulse wave signal.

In one embodiment, the processor 101 may further determine a variance of the pulse wave signal. The variance can be expressed as a variance of a pulse wave of a current pulse period relative to a pulse wave of a previous pulse period, such as a variance of a pulse interval. For example, the pulse period of the current pulse wave is the seventh pulse period, and has six pulse intervals, which are denoted by (H1, H2, H3, H4, H5, H6). The ratio of the difference between the sixth pulse interval and the Mean of the five preceding pulse intervals to the Mean of the five preceding pulse intervals is expressed as (H6-Mean (H1, H2, H3, H4, H5))/Mean (H1, H2, H3, H4, H5) as the variability of the pulse intervals.

In other embodiments, the variance is a variance of one pulse wave with respect to a period of time, for example, if the current pulse wave is the seventh pulse wave, there are six pulse intervals, and a ratio of a difference between the sixth pulse interval and the fifth pulse interval to the fifth pulse interval is used as the variance of the pulse interval, which can be expressed as (H6-Mean (H1, H2, H3, H4, H5))/H5. Alternatively, the degree of variation in pulse interval may be determined by taking the difference between any one of the first to sixth pulse intervals and the mean value of any number (in this example, six pulse intervals at the maximum) of pulse intervals and then determining the ratio of the difference to the mean value. When the processor 101 determines that the variance corresponding to the pulse wave signal exceeds a preset variance threshold, the processor 101 may determine that the category of the regularity evaluation information of the pulse wave signal is pulse irregularity; when the processor 101 determines that the variance corresponding to the pulse wave signal does not exceed the preset variance threshold, the processor 101 may determine that the category of the regularity evaluation information of the pulse wave signal is a pulse rule.

In one embodiment, the processor 101 may perform machine learning analysis on the feature quantity to determine regularity evaluation information of the pulse wave signal. For example, the processor 101 may perform machine learning analysis (e.g., support vector machine) on a number of pulse wave signals with identified pulse rules or pulse irregularities to obtain a corresponding model. In this way, the processor 101 may classify the pulse wave signal into a regular pulse or an irregular pulse through a model obtained by machine learning analysis.

In an embodiment, the processor 101 may combine different types of feature quantities (two or more feature quantities) among the plurality of feature quantities to obtain new feature quantities, and may combine different types of analysis methods to analyze the obtained new feature quantities. For example, the processor 101 may determine the regularity evaluation information of the subject's pulse based on both statistical analysis and machine learning analysis.

In some embodiments, the processor 101 performs machine learning analysis on the feature quantity by a machine learning method to determine regularity evaluation information of the pulse wave signal, including:

inputting the pulse wave signals into a machine learning model after training is completed, and automatically obtaining one or more characteristic quantities and/or regularity evaluation information corresponding to the pulse wave signals.

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 feature quantity of the pulse wave signal 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 machine learning of the aforementioned pulse wave signals to obtain the feature quantities of the pulse wave signals includes: relevant information of the pulse wave signals obtained based on the pulse wave signals after time domain analysis, frequency domain analysis or nonlinear dynamics analysis is input into the machine learning model after training is completed, and regularity evaluation information can be automatically obtained.

In one embodiment, when the monitoring device detects that the pulse of the subject is at the position of the peak (e.g., the main peak) of the pulse wave, the monitoring device can control the alarm circuit 116 to output an alarm sound in the form of sound, i.e., the alarm circuit 116 outputs an alarm sound at the position of the main peak of each pulse period. Therefore, the processor 101 can obtain the peak position of the pulse wave corresponding to the pulse wave signal, and convert the pulse wave signal into the corresponding pulse sound based on the peak position of the pulse wave. The pulse sound obtained after conversion also includes information such as period. The processor 101 may determine pulse sound interval information, wherein the pulse sound interval information is a time distance between peaks of any two adjacent periods of pulse sounds in the pulse sounds. The processor 101 may also perform statistical analysis on the pulse sound interval information to obtain statistics corresponding to the pulse sound interval information, and the processor 101 may obtain regularity evaluation information of the subject based on the statistics of the pulse sound interval information. The processor 101 performs statistical analysis on the pulse sound interval information, including but not limited to one or more of mean, standard deviation, variance, maximum, minimum, difference between maximum and minimum, different types of proportion statistics, and continuous feature statistics. The specific analysis method is similar to the statistical analysis of the pulse interval information of the pulse wave of the processor 101, and therefore, the detailed description thereof is omitted here.

And 106, displaying an analysis result display area for the user to perform input operation, wherein the content displayed by the analysis result display area comprises the waveform related information, the regularity evaluation information and a determined sub-area supporting the user to perform input operation on the regularity evaluation information. In this embodiment, the processor 101 may control the content of the analysis result display area displayed on the display screen 114 to include the waveform-related information and the regularity evaluation information, and the determination sub-area supporting the user to perform an input operation on the regularity evaluation information. Wherein, the processor 101 can control a specific area of the vital sign display interface 500 (shown in fig. 4) of the display screen 114 to display the analysis result display area 520 (shown in fig. 4); alternatively, the processor 101 may control the display screen 114 to display the analysis results display area 520 on a new window that pops up on the vital signs display interface 500.

Please refer to fig. 4, which is a schematic diagram illustrating an analysis result according to an embodiment of the present application.

As shown in fig. 4, different vital sign measurement parameters are displayed in a plurality of vital sign data entry areas of a vital sign display interface 500 of the multi-parameter monitor 10, including but not limited to a blood pressure display area 510, an analysis result display area 520, and a body temperature and respiration display area 530. The blood pressure display area 510 can display the information of the diastolic blood pressure and the systolic blood pressure of the subject obtained by the non-invasive blood pressure or invasive blood pressure measurement mode of the sensor attachment 111; the body temperature/respiration display area 530 is used for displaying the body temperature, the respiration rate, and other relevant information of the subject. In addition, a specific area is set on the same vital sign display interface 500 to display the analysis result display area 520. 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.

The analysis result display area 520 includes a pulse rate display section 526, a blood oxygen information display section 523, a waveform display section 522, and a determination sub-area 524 that supports a user's input operation for the regularity evaluation information. The processor 101 controls a particular area of the display screen 114 to simultaneously or non-simultaneously display waveform related information, regularity evaluation information, and an identifier that supports a user to confirm or modify the analysis results.

The pulse rate display section 526 is used for displaying the characteristic quantity, such as the pulse rate, determined by the processor 101 according to the pulse wave signal. The waveform display section 522 is used for displaying a pulse wave waveform 525 (e.g., waveform-related information obtained by the processor 101 based on time domain analysis) corresponding to the pulse wave signal. The determination sub-area 524 is used for displaying an identifier (such as an identifier of "pulse irregularity") that supports the user to confirm or modify the regularity evaluation information, wherein the identifier is used for the display processor 101 to determine the type of the regularity evaluation information of the pulse wave signal based on one or more of new feature extraction, statistical analysis, feature combination analysis, and machine learning analysis. For example, the processor 101 determines that the type of the regularity evaluation information of the pulse of the subject corresponding to the pulse wave signal within a period of time is pulse irregularity, and prompts the type in a text manner through the identification; when the regularity evaluation information of the pulse wave signal is a pulse rule, the processor 101 controls the content of the analysis result display area 520 to further include prompt information representing the pulse rule. In other embodiments, the vital signs display interface 500 can also display other feature quantities.

In this embodiment, the experienced medical staff can determine the regularity evaluation information of the pulse wave signal according to the pulse rate displayed by the pulse rate display section 526 and the pulse wave waveform 525 displayed by the waveform display section 522. For example, when the medical staff determines that the regularity evaluation information of the pulse wave signal is a pulse rule, the monitoring device determines that the regularity evaluation information of the pulse wave signal is a pulse irregularity, that is, the regularity evaluation information determined by the monitoring device is different from the regularity evaluation information determined by the medical staff, and at this time, the medical staff may click the determination sub-area 524 to change the regularity evaluation information of the pulse wave signal.

Please refer to fig. 5, which is a schematic diagram illustrating an analysis result according to another embodiment of the present application. When the clinical experience of the medical staff is low and the regularity evaluation information of the pulse wave signal cannot be determined only according to the pulse rate displayed by the pulse rate display section 526 and the pulse wave waveform 525 displayed by the waveform display section 522, the medical staff can click on the waveform display section 522 to display more waveform related information besides the pulse wave waveform. Processor 101, upon receiving an input operation at waveform display zone 522, processor 101 may display one or more other waveform-related information indicative of a respective location of pulse wave waveform 525, wherein the one or more other waveform-related information indicative of the respective location of pulse wave waveform 525 includes a rhythm quantization parameter. In some embodiments, the rhythm quantification parameter includes, but is not limited to, information of one or more of a characteristic quantity of the pulse wave signal, a fastest waveform segment (e.g., including a number of smaller pulse intervals), a slowest waveform segment (e.g., including a number of larger pulse intervals), a waveform identifier, a waveform interval measurement (e.g., an average of pulse intervals of the pulse wave signal), a maximum waveform interval (e.g., a maximum pulse interval), a minimum waveform interval (e.g., a minimum pulse interval), a waveform variability number, a waveform variability threshold, and a variability number threshold. For example, the processor 101 may mark the maximum waveform interval as 80, the minimum waveform interval as 40, the variance as 34%, and the variance threshold as 20% at the corresponding location of the pulse wave waveform 525. In other embodiments, the healthcare worker may turn off other waveform-related information in the displayed waveform display section 522 in addition to the pulse wave waveform 525.

Please refer to fig. 6, which is a schematic diagram illustrating an analysis result of a hidden portion according to an embodiment of the present application. In this embodiment, the processor 101 hides part of the content of the analysis result display area 522 in a pull-down menu, a pull-up menu, a side-pull menu, or a floating menu of the vital sign display interface 500, wherein an interface switching button 527 that hides and/or expands the pull-down menu, the pull-up menu, the side-pull menu, or the floating menu is displayed in the analysis result display area; when receiving a call detail operation input by the medical staff by clicking the interface switching button 527, the processor 101 expands and displays the hidden part of the content. For example, when the medical professional needs to determine the subject's pulse rate, processor 101 may control the pulse rate displayed by pulse rate display section 526 of analysis results display area 522 and hide pulse wave waveform 525 displayed by waveform display section 522.

Please refer to fig. 7, which is a schematic diagram illustrating an analysis result of a hidden portion according to an embodiment of the present application. When the medical staff needs to check and determine the pulse rate of the subject and the pulse wave waveform 525 of the subject at the same time, the medical staff can click the interface switching button 527 to perform the input operation of calling details, at this time, the processor 101 can display the pulse wave waveform 525 of the waveform display partition 522 which is hidden, and thus, the medical staff determines the regularity evaluation information of the pulse wave signal according to the displayed pulse rate and the pulse wave waveform 525.

And 106, receiving an input operation of the user, and determining a judgment result confirmed by the user based on the input operation.

In this embodiment, the medical staff may determine whether the type of the pulse regularity evaluation information of the subject obtained by the monitoring device 10 is correct according to the waveform related information displayed by the pulse rate display section 526, and further, the medical staff may determine the judgment result corresponding to the pulse regularity evaluation information through an input operation.

Referring back to fig. 5, when the healthcare worker determines that the type of regularity evaluation information obtained by the monitoring device 10 is incorrect, the healthcare worker may click on the determination sub-area 524 to modify the type of regularity evaluation information determined by the monitoring device 10. At this time, the processor 101 receives an input operation by the medical staff, and displays the change display section 529 including the type of regularity evaluation information. Since the types of regularity evaluation information include pulse regularity and pulse irregularity, the processor 101 may control the display screen 114 to display two options of "regular" and "irregular" in the modification display partition 529, which correspond to the two types of pulse regularity and pulse irregularity, respectively.

In this embodiment, since the processor 101 determines that the regularity evaluation information of the pulse of the subject is irregular, the processor 101 may control the option corresponding to "irregular" in the modification display partition 529 to be selected as the default. When the healthcare worker clicks on the option of "rule" in change display partition 529, it indicates that the determination result determined by the healthcare worker is "rule". At this time, the processor 101 saves the judgment result confirmed by the medical staff. If the processor 101 receives the option of selecting "rule" from the medical staff, the processor 101 may change the category of the regularity evaluation information of the pulse of the subject corresponding to the pulse wave signal to the pulse rule. In an embodiment, the processor 101 may further display a saving icon for the medical staff to click to trigger the saving operation, and when the medical staff clicks the saving icon, the processor 101 saves the judgment result confirmed by the medical staff.

In other embodiments, alteration display area 529 may display selection keys that include a "yes" and a "no" designation for manual selection by the healthcare worker to further determine an irregular pulse rate. Specifically, when "yes" is selected, the medical person confirms the regularity evaluation information of the pulse wave signal preliminarily determined by the processor 101, and when "no" is selected, the medical person changes the regularity evaluation information of the pulse wave signal determined by the processor 101. In one embodiment, since the monitoring device 10 determines the regularity evaluation information corresponding to the pulse wave signal, when the medical staff selects "yes", the processor 101 determines that the regularity evaluation information of the pulse wave signal is the same as the regularity evaluation information determined by the monitoring device 10; when the healthcare worker selects "no", the processor 101 determines that the regularity evaluation information of the pulse wave signal is different or opposite to the regularity evaluation information determined by the monitoring device 10. For example, if the monitoring device 10 determines that the regularity evaluation information corresponding to the pulse wave signal is pulse irregularity, when the medical staff selects "yes", the processor 101 determines that the regularity evaluation information of the pulse wave signal is pulse irregularity, which is the same as the regularity evaluation information determined by the monitoring device 10; when the medical staff selects "no", the processor 101 determines that the regularity evaluation information of the pulse wave signal is a pulse rule, contrary to the regularity evaluation information determined by the monitoring device 10.

Please refer to fig. 8, which is a schematic diagram illustrating an analysis result according to another embodiment of the present application.

In this embodiment, the processor 101 controls the display of the analysis result display area 520 in a new window popped up on the vital signs display interface 500. The content displayed in the analysis result display area 520 displayed in the new pop-up window includes a waveform display area 532 and a determination area 534 supporting the user to perform an input operation on the regularity evaluation information, wherein the determination area 534 includes a "regular" key and an "irregular" identification key.

Since the processor 101 determines that the regularity evaluation information of the pulse of the subject is irregular, the processor 101 may control the option corresponding to the "irregular" identification key to be selected as a default. When the medical staff clicks the rule switching, the rule evaluation information determined by the medical staff is indicated as the rule. At this time, the processor 101 saves the judgment result confirmed by the medical staff. If the processor 101 receives that the medical staff selects the "rule" identification key, the processor 101 may change the category of the regularity evaluation information of the pulse of the subject corresponding to the pulse wave signal to the pulse rule.

In this embodiment, in order to enable the medical staff to better determine the regularity evaluation information of the subject according to the waveform-related information, the processor 101 may display one or more other waveform-related information besides the pulse wave waveform marked at the corresponding position of the pulse wave waveform 535 while displaying the pulse wave waveform 535. Wherein the one or more other waveform-related information other than the pulse wave waveform, which is indicated at the corresponding position of the pulse wave waveform, includes a rhythm quantization parameter. In some embodiments, the rhythm quantification parameter includes, but is not limited to, information of one or more of a feature quantity of the pulse wave signal, a fastest waveform segment, a slowest waveform segment, a waveform identification, a waveform interval measurement, a maximum waveform interval, a minimum waveform interval, a waveform variability number, a waveform variability threshold, a variability number threshold. For example, fig. 8 specifically shows that the maximum pulse rate of the pulse wave is 80, the minimum pulse rate is 40, the number of variations is 4, and the threshold of the number of variations is 4.

In one embodiment, the processor 101 displays the regularity evaluation information in the form of a text prompt, a graphical prompt, or a combination of text and graphical prompts on the vital signs display interface 500. In one embodiment, the processor 101 may also control the alarm circuit 116 to output regularity evaluation information, including but not limited to voice.

In an embodiment, the monitoring device 10 is further configured to output and display the determination result confirmed by the user.

In this embodiment, when the medical staff changes the type of the regularity evaluation information, the processor 101 may display the judgment result determined by the medical staff. As in fig. 5, when the medical staff member determines that the type of change regularity evaluation information is "rule", the processor 101 controls the "rule" selection to be in a selected state to prompt the user of the determined judgment result.

In an embodiment, if the processor 101 determines that the regularity evaluation information type of the pulse wave signal is regular and the judgment result confirmed by the medical staff is irregular, the processor 101 outputs and displays a prompt interface for the user to select a subsequent work function, including but not limited to printing a pulse wave waveform, an ECG (electrocardiogram) appointment check, and/or an ultrasound appointment check, so that the medical staff can select a corresponding subsequent step or function.

The rhythm regularity prompting method obtains the type of the regularity evaluation information corresponding to the pulse wave signal after analyzing the obtained pulse wave signal within a period of time, thereby reducing the defect of low judgment accuracy caused by the fact that medical staff manually touches the pulse of a patient to determine the regularity evaluation information. In addition, the type of the regularity evaluation information determined by the monitoring equipment and the waveform related information are displayed through the display screen, so that medical staff can change, store and the like the type of the regularity evaluation information determined by the monitoring equipment, and the user experience is improved.

In one embodiment, the memory 103 is used for storing the computer program and/or module, and the processor 101 implements various functions of the rhythm regularity prompting method by operating or executing the computer program and/or module stored in the memory 103 and calling data stored in the memory 103. The memory 103 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function, and the like. In addition, the memory 103 may include a high speed random access memory device, and may also include a non-volatile memory device 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), at least one piece of magnetic disk storage, a Flash memory device, or other volatile solid state storage device. The processor 101 runs a program corresponding to the executable program code by reading the executable program code stored in the memory 103 for performing the steps of the rhythm regularity prompting method in any of the foregoing embodiments.

Referring to fig. 9, a hardware block diagram of a monitoring system according to an embodiment of the present application is shown. As shown in fig. 9, a monitoring system for use in a hospital is provided, by which data of a monitor or a monitoring device can be integrally stored, patient information and nursing information can be centrally managed, and the patient information and the nursing information can be stored in association with each other, so that storage of historical data and associated alarm can be facilitated. In the system shown in fig. 9, a bedside monitor 212 may be provided for each patient bed, and the bedside monitor 212 may be the multi-parameter monitor or the plug-in monitor described above. In addition, each bedside monitor 212 can also be paired with one portable monitoring device 213 for transmission, the portable monitoring device 213 provides a simple and portable multi-parameter monitor, can be worn on the body of a patient to perform mobile monitoring corresponding to the patient, and can transmit physiological data generated by the mobile monitoring to the bedside monitor 212 for display after the portable monitoring device 213 is in wired or wireless communication with the bedside monitor 212, or transmit the physiological data to the central station 211 for a doctor or a nurse to view through the bedside monitor 212, or transmit the physiological data to the data server 215 for storage through the bedside monitor 212. In addition, the portable monitoring device 213 can also directly transmit the physiological data generated by the mobile monitoring to the central station 211 through the wireless network node 214 arranged in the hospital for storage and display, or transmit the physiological data generated by the mobile monitoring to the data server 215 through the wireless network node 214 arranged in the hospital for storage. The data corresponding to the physiological parameters displayed on the bedside monitor 212 may originate from a sensor accessory directly connected above the monitor, or from the portable monitoring device 213, or from a data server.

In one embodiment, the portable monitoring device 213 is configured to acquire a pulse wave signal over a period of time and transmit the acquired pulse wave signal to the central station 211, so that the central station 211 performs feature extraction on the pulse wave signal to obtain one or more feature quantities corresponding to the pulse wave signal. The central station 211 is further configured to analyze the feature quantity and output an analysis result to the portable monitoring device 213, where the analysis result at least includes the regularity evaluation information, i.e. the central station 211 can perform the functions of step 104 and step 106 in the above embodiments. The portable monitoring device 213 controls the display screen to display an analysis result display area for medical personnel to perform input operation, wherein the analysis result display area displays the regularity evaluation information and supports the medical personnel to confirm or change the identification of the analysis result; the portable monitoring device 213 receives an input operation of the user and determines a determination result confirmed by the medical staff based on the input operation, and the portable monitoring device 213 further controls the display screen to display the determination result confirmed by the medical staff and transmits the determination result confirmed by the medical staff to the central station 211. The central station 211 may store the determination result, such as changing the type of the regularity evaluation information of the pulse wave signal.

In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments. The definition, identification or obtaining method, output mode, display scheme, signal processing procedure, and the like of the fluctuation rhythm information of the pulse wave can be referred to the relevant description in the foregoing embodiments, and will not be described in detail here.

Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable memory, which may include: flash Memory disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.

The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations 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

1. A rhythm regularity prompting method based on pulse waves is characterized by comprising the following steps:

acquiring pulse wave signals within a period of time;

2. The method for rhythm regularity prompting of claim 1, the method further comprising:

and outputting and displaying the judgment result confirmed by the user.

3. The method of rhythmic regularity prompting according to claim 1 or 2, wherein the determination sub-region includes an identification that supports a user to confirm or modify the regularity evaluation information.

4. The rhythm regularity prompting method according to any one of claims 1 through 3, wherein the displaying of the analysis result display area for the user to perform the input operation includes one of the following steps:

And displaying the analysis result display area in a new window popped up on the vital sign display interface.

5. The method for rhythm regularity prompting of claim 4, wherein said displaying the analysis result display area on a vital signs display interface includes:

6. The method for rhythm regularity prompting of claim 2, the method further comprising:

7. The method of rhythmicity prompting according to claim 6, wherein the follow-up work function prompting interface includes an identification of selection of one or more of:

8. The rhythm regularity prompting method according to any one of claims 1 to 7, wherein the regularity evaluation information is displayed in the analysis result display area in a form of a text prompt, a graphic prompt, or a combination of text and graphic prompts.

9. The method for rhythm regularity prompting of any one of claims 1 through 8, the method further comprising:

displaying an icon for a user to click on to trigger a save operation, an

10. The rhythm regularity prompting method according to any one of claims 1-9, wherein the waveform related information includes pulse wave waveforms and/or rhythm quantization parameters corresponding to the pulse wave signals within the period of time, wherein the rhythm quantization parameters include pulse interval, pulse amplitude, pulse width, pulse slope, pulse area, difference of pulse interval, difference of pulse amplitude, difference of pulse slope, difference of pulse area, mean of pulse interval, mean of difference of pulse interval, mean of pulse amplitude, mean of pulse slope, mean of pulse area, standard deviation of pulse interval, standard deviation of pulse amplitude, standard deviation of pulse wave slope, standard deviation of pulse area, fastest waveform segment, slowest waveform segment, waveform identifier, waveform interval measurement value, maximum waveform interval measurement value, Information of one or more of a minimum waveform interval, a maximum pulse rate value, a minimum pulse rate value, a waveform variability number threshold, and a waveform variability threshold.

11. The rhythm regularity prompting method according to any one of claims 1 through 10, wherein the analyzing the pulse wave signal to obtain an analysis result includes:

and analyzing the characteristic quantity to obtain the analysis result.

12. The rhythm regularity prompting method according to claim 11, wherein the content displayed in the analysis result display area further includes the one or more feature quantities.

13. The rhythm regularity prompting method according to claim 11 or 12, wherein the characteristic quantity includes one or more of frequency, phase, entropy value and complexity of a pulse wave corresponding to the pulse wave signal.

14. The rhythm regularity prompting method as set forth in any one of claims 11 through 13, wherein the performing feature extraction on the pulse wave signal includes:

15. The method of rhythm regularity prompting according to claim 14, wherein the time domain feature extraction includes extracting one or more feature quantities of pulse interval, pulse amplitude, pulse area, pulse slope or pulse envelope of the pulse wave corresponding to the pulse wave signal.

16. The rhythm regularity prompting method as set forth in claim 14 or 15, wherein the frequency domain feature extraction includes converting the pulse wave signal into a frequency domain for analysis to extract frequency domain features of the pulse wave signal.

17. The rhythm regularity prompting method according to any one of claims 11 through 16, wherein the analyzing the feature quantity includes:

18. The method of rhythm regularity prompting according to claim 17, wherein the new feature extraction of the feature quantity includes:

integrating a plurality of characteristic quantities to obtain new characteristic quantities; and

and analyzing the new characteristic quantity.

19. The method of rhythm regularity prompting according to claim 18, wherein the new feature quantity includes one or more of a pulse rate, a pulse sound, and a pulse amplitude of the pulse wave signal.

20. The rhythm regularity prompting method according to any one of claims 11 through 19, wherein the analyzing the feature quantity to obtain the analysis result includes:

obtaining the analysis result, wherein the analysis result at least comprises corresponding regularity evaluation information of the testee.

21. The method according to claim 11, wherein the characteristic quantity is pulse interval information of a pulse wave corresponding to the pulse wave signal, wherein the pulse interval information includes a plurality of pulse intervals; the analyzing the characteristic quantity to obtain the analysis result comprises:

22. The method according to claim 11, wherein the characteristic quantity is pulse interval information of a pulse wave corresponding to the pulse wave signal, wherein the pulse interval information includes a plurality of pulse intervals;

obtaining the difference value of continuous adjacent pulse intervals;

23. The rhythm regularity prompting method according to claim 11, wherein the characteristic quantity is pulse wave interval information of a pulse wave of the pulse wave signal; the analyzing the characteristic quantity to obtain an analysis result comprises the following steps:

24. The method for prompting rhythm regularity of claim 17, wherein performing a statistical analysis on the feature quantity to obtain an analysis result includes:

judging whether the statistic meets a preset condition:

and obtaining the analysis result, wherein the analysis result at least comprises corresponding regularity evaluation information of the testee.

25. The method of rhythm regularity hinting according to claim 24, wherein the statistics include one or more of a mean, a standard deviation, a variance, a maximum, a minimum, a difference between a maximum and a minimum, different types of proportion statistics, and continuous feature statistics.

26. The method for rhythm regularity prompting according to claim 24 or 25, wherein the preset condition includes: one or more of a fixed condition, a sliding window condition, a dynamic condition, a fuzzy range condition, an adaptive condition.

27. The method of rhythm regularity prompting of claim 17 wherein said feature-binding analysis includes:

28. A method for displaying display interfaces of a monitoring device, the monitoring device including a display screen for receiving user input operations, the display screen being configured to display one or more display interfaces, the method comprising:

29. The display method as recited in claim 28, said method further comprising:

30. The display method according to claim 28, wherein displaying the determined sub-region supporting the user's input operation for the regularity evaluation information includes:

displaying an identifier supporting a user to confirm or change the regularity evaluation information.

31. The display method according to claim 28, wherein displaying a plurality of vital sign data item areas including at least an analysis result display area on the pulse wave signal in the vital sign display interface state includes one of:

32. The display method of claim 31, wherein displaying the analysis result display area on the vital signs display interface comprises:

33. The display method of claim 29, wherein the method further comprises:

34. The display method of claim 33, wherein the follow-up work function prompt interface includes an identification of selection of one or more of:

35. The display method according to any one of claims 28 to 34, wherein the regularity evaluation information is displayed in the analysis result display area in a form of a text prompt, a graphic prompt, or a combination of text and graphic prompts.

36. The display method according to any one of claims 28 to 35, wherein the waveform related information includes pulse wave waveforms and/or rhythm quantization parameters corresponding to the pulse wave signals acquired during the period of time, wherein the rhythm quantization parameters include pulse interval, pulse amplitude, pulse width, pulse slope, pulse area, pulse interval difference, pulse amplitude difference, pulse slope difference, pulse area difference, pulse interval mean, pulse interval difference mean, pulse amplitude mean, pulse slope mean, pulse area mean, pulse interval standard deviation, pulse amplitude standard deviation, pulse wave slope standard deviation, pulse area standard deviation, fastest waveform segment, slowest waveform segment, waveform identifier, waveform interval measurement value, largest waveform interval, Information of one or more of a minimum waveform interval, a maximum pulse rate value, a minimum pulse rate value, a waveform variability number threshold, and a waveform variability threshold.

37. The display method according to any one of claims 28 to 36, further comprising displaying one or more feature quantities of the pulse wave signal, which are obtained by performing feature extraction on the pulse wave signal, in the analysis result display area.

38. A monitoring device, characterized in that the monitoring device comprises:

a display screen for serving as a display and input device;

controlling the display screen to display an analysis result display area for a user to perform input operation, wherein the content displayed in the analysis result display area comprises waveform information, regularity evaluation information and a determining sub-area supporting the user to perform input operation on the regularity evaluation information, and controlling the display screen to display prompt information representing irregular pulse in the analysis result display area at least when the regularity evaluation information is irregular pulse;

39. A monitoring system comprising a monitoring device and a central station, said monitoring device comprising a display screen for being a display and input device, wherein:

the monitoring device is further configured to:

40. A computer readable storage medium storing computer instructions which, when executed by a processor, implement the method of any one of claims 1 to 37.