A signal processing method and related apparatus

Abstract

The application provides a signal processing method and related device, comprising: obtaining a breathing signal and a heartbeat signal of a target object; determining an instantaneous heart rate signal of the target object according to the heartbeat signal; determining a cardiopulmonary coupling degree index of the target object based on the breathing signal and the instantaneous heart rate signal, the cardiopulmonary coupling degree index being used to identify the degree of respiratory sinus arrhythmia of the target object. Through the above method, the breathing signal and the heartbeat signal of the target object can be comprehensively analyzed, and the cardiopulmonary coupling degree index used to identify the degree of respiratory sinus arrhythmia of the target object can be obtained from the perspective of cardiopulmonary coupling, so that the respiratory sinus arrhythmia of the target object can be more accurately analyzed.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of data processing, and in particular, to a signal processing method and related apparatus. BACKGROUND

[0002] Respiratory sinus arrhythmia (RSA) refers to a normal physiological phenomenon that heart rate increases during inhalation and decreases during exhalation. Respiratory sinus arrhythmia can match intermittent exhalation ventilation and relatively continuous pulmonary blood perfusion, i.e., ventilation / perfusion match (V / Q match), which means that respiratory sinus arrhythmia can improve pulmonary gas exchange efficiency by adjusting heart rate and changing the distribution of cardiac output in the respiratory cycle.

[0003] From the perspective of the interaction between the heart and the lung, the respiratory sinus arrhythmia phenomenon embodies the driving effect of respiration on heart rate and the compensatory effect of heart rate on respiration. This good coupling can effectively ensure that the heart and lung efficiently adapt to the large fluctuations in the body's oxygen supply and metabolic demand under different internal and external environments, and maintain body function stability. When affected by internal pathological factors of the heart or respiration, the appropriate coupling between the heart and the lung reflected by the respiratory sinus arrhythmia phenomenon can also play a key benign or malignant compensatory role. It can be seen that appropriate respiratory sinus arrhythmia degree is a sign of the body's self-adaptation to maintain body homeostasis, and in practical applications, quantitative evaluation of the respiratory sinus arrhythmia degree is of great significance.

[0004] In the related art, the respiratory sinus arrhythmia degree is usually evaluated in heart rate variability (HRV) analysis. Since the respiratory sinus arrhythmia is the main source of short-term heart rate variability, the standard deviation indicators such as the standard deviation of all NN intervals (SDNN) and the root mean square of the successive differences (RMSSD) have a certain correlation with the respiratory sinus arrhythmia degree, and can be used to measure the respiratory sinus arrhythmia degree, but the SDNN, RMSSD and other standard deviation indicators are not specific indicators of the respiratory sinus arrhythmia. In this regard, although the maximum heart rate and minimum heart rate difference (HRmax-HRmin) indicator in the heart rate variability analysis imposes a respiratory cycle constraint on the basis of describing the dispersion degree of the instantaneous heart rate sequence, it can more specifically describe the respiratory sinus arrhythmia degree, but the HRmax-HRmin indicator is still a simple statistical indicator, and in many cases it still cannot accurately evaluate the respiratory sinus arrhythmia degree, and there is high uncertainty. At the same time, since the power of the high frequency band is usually considered to have a strong correlation with the respiratory sinus arrhythmia degree in the frequency domain heart rate variability analysis, the high frequency band power indicator can also be used to measure the respiratory sinus arrhythmia degree, but the high frequency band power indicator is also not a specific indicator of the respiratory sinus arrhythmia.

[0005] That is, in the related art, the time domain standard deviation indicators and the high frequency band power indicators that can reflect the respiratory sinus arrhythmia degree in the heart rate variability analysis are not specific indicators for the respiratory sinus arrhythmia, but are related indicators in the heart rate variability analysis. The correlation of these indicators with the respiratory sinus arrhythmia degree is usually attributed to the fact that the respiratory sinus arrhythmia has a greater contribution to the short-term heart rate variability, and when the respiratory sinus arrhythmia degree is weak, the above indicators cannot accurately analyze the respiratory sinus arrhythmia degree. SUMMARY

[0006] Embodiments of the present application provide at least a signal processing method and related device, which can comprehensively analyze the respiratory signal and the heartbeat signal of a target object, obtain a cardiopulmonary coupling degree index for identifying the degree of respiratory sinus arrhythmia of the target object from the perspective of cardiopulmonary coupling, and thus more accurately analyze the respiratory sinus arrhythmia of the target object.

[0007] In a first aspect, the present application provides a signal processing method, comprising:

[0008] acquire a respiration signal and a heartbeat signal of a target object;

[0009] determine an instantaneous heart rate signal of the target object according to the heartbeat signal;

[0010] determine a cardio-respiratory coupling index of the target object based on the respiration signal and the instantaneous heart rate signal, the cardio-respiratory coupling index being used to identify a degree of respiratory sinus arrhythmia of the target object.

[0011] In a possible implementation, the determining of the instantaneous heart rate signal of the target object according to the heartbeat signal comprises:

[0012] determining the instantaneous heart rate signal of the target object according to RR interval information of the heartbeat signal.

[0013] In a possible implementation, the determining of the instantaneous heart rate signal of the target object according to the RR interval information of the heartbeat signal comprises:

[0014] determining the instantaneous heart rate signal of the target object according to inverse of the RR interval information of the heartbeat signal and through spline interpolation.

[0015] In a possible implementation, the determining of the cardio-respiratory coupling index of the target object based on the respiration signal and the instantaneous heart rate signal comprises:

[0016] determining a time-frequency correlation strength between the respiration signal and the instantaneous heart rate signal;

[0017] determining the cardio-respiratory coupling index of the target object based on the time-frequency correlation strength.

[0018] In a possible implementation, the determining of the time-frequency correlation strength between the respiration signal and the instantaneous heart rate signal comprises:

[0019] transforming the respiration signal and the instantaneous heart rate signal into a time-frequency space to obtain a respiration time-frequency signal corresponding to the respiration signal and an instantaneous heart rate time-frequency signal corresponding to the instantaneous heart rate signal;

[0020] determining the time-frequency correlation strength based on a same-frequency power strength or a same-phase power strength between the respiration time-frequency signal and the instantaneous heart rate time-frequency signal.

[0021] In a possible implementation, the determining of the cardio-respiratory coupling index of the target object based on the respiration signal and the instantaneous heart rate signal comprises:

[0022] determining a causality strength between the respiration signal and the instantaneous heart rate signal, the causality strength being used to identify a unidirectional driving response strength between respiration and heart rate of the target object;

[0023] determining the cardio-respiratory coupling index of the target object based on the causality strength.

[0024] In a possible implementation, the method further includes:

[0025] determining a heartbeat response sensitivity index of the target object based on the respiration signal and the heartbeat signal;

[0026] determining a respiration driving force index of the target object according to the cardiopulmonary coupling degree index and the heartbeat response sensitivity index.

[0027] In a possible implementation, the method further includes:

[0028] determining an average respiration frequency of the target object based on the respiration signal; determining an average heart rate and an average diastolic period length of the target object based on the heartbeat signal;

[0029] determining the heartbeat response sensitivity index by the following formula: RSI = T D × (f e ) 2 / f r

[0030] wherein RSI represents the heartbeat response sensitivity index, T D represents the average diastolic period length, f e represents the average heart rate, and f r represents the average respiration frequency.

[0031] In a possible implementation, the method further includes:

[0032] determining the respiration driving force index by the following formula: RDI = (q / RSI) x K

[0033] wherein RDI represents the respiration driving force index, q represents the cardiopulmonary coupling degree index, RSI represents the heartbeat response sensitivity index, and K represents a preset normalization constant.

[0034] In a possible implementation, the method further includes:

[0035] synchronously collecting the respiration signal and the heartbeat signal.

[0036] In a possible implementation, the method further includes:

[0037] collecting the heartbeat signal;

[0038] determining the respiration signal according to the heartbeat signal.

[0039] In a second aspect, the present application provides a signal processing apparatus, comprising:

[0040] an acquisition module configured to acquire a respiration signal and a heartbeat signal of a target object;

[0041] a first determination module configured to determine an instantaneous heart rate signal of the target object according to the heartbeat signal;

[0042] a second determination module configured to determine a cardiorespiratory coupling degree index of the target object based on the respiration signal and the instantaneous heart rate signal, the cardiorespiratory coupling degree index being used to identify a degree of respiratory sinus arrhythmia of the target object.

[0043] In a third aspect, the present application provides an electronic device, comprising a processor, a memory and a bus, the memory storing machine readable instructions executable by the processor, the processor and the memory being in communication through the bus when the electronic device is running, and the machine readable instructions being executed by the processor to perform the signal processing method provided by the present application.

[0044] In a fourth aspect, the present application provides a computer readable storage medium, the computer readable storage medium storing a computer program, the computer program being executed by a processor to perform the signal processing method provided by the present application.

[0045] In a fifth aspect, the present application provides a computer program product, comprising a computer program, the computer program being executed by a processor to perform the signal processing method provided by the present application.

[0046] In summary, the present application provides a signal processing method and related apparatus, comprising: acquiring a respiration signal and a heartbeat signal of a target object; determining an instantaneous heart rate signal of the target object according to the heartbeat signal; and determining a cardiorespiratory coupling degree index of the target object based on the respiration signal and the instantaneous heart rate signal, the cardiorespiratory coupling degree index being used to identify a degree of respiratory sinus arrhythmia of the target object. Through the above method, the respiration signal and the heartbeat signal of the target object are comprehensively analyzed, and the cardiorespiratory coupling degree index used to identify the degree of respiratory sinus arrhythmia of the target object is obtained from the perspective of cardiorespiratory coupling, so that the respiratory sinus arrhythmia of the target object can be more accurately analyzed.

[0047] Other advantages of the present application will be described in more detail in conjunction with the following description and drawings.

[0048] It should be understood that the above description is only a summary of the technical solutions of the present application, so as to enable a general understanding of the technical means of the present application, and then the content of the specification is implemented. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the following specific embodiments of the present application are described. BRIEF DESCRIPTION OF DRAWINGS

[0049] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required to be used in the embodiments will be briefly introduced. The drawings incorporated into the specification and form a part of the specification, which show the embodiments consistent with the present application, and are used to explain the technical solutions of the present application together with the specification. It should be understood that the drawings only show some of the embodiments of the present application, and therefore should not be regarded as a limitation on the scope of protection, and for those skilled in the art, other related drawings can also be obtained without creative labor. Moreover, the same reference numerals are used to represent the same components throughout the drawings. In the drawings:

[0050] Figure 1 Method flow chart of a signal processing method provided by an embodiment of the present application;

[0051] Figure 2 Method flow chart of another signal processing method provided by an embodiment of the present application;

[0052] Figure 3 Device equipment diagram of a signal processing device provided by an embodiment of the present application. Specific embodiments

[0053] The exemplary embodiments of the present application will be described in detail with reference to the accompanying drawings. Although the exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application can be implemented in various forms, and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided so that the present application can be more thoroughly understood, and the scope of the present application can be fully conveyed to those skilled in the art.

[0054] In the description of the embodiments of the present application, it should be understood that terms such as "include" or "have" are intended to indicate that the features, numbers, steps, actions, components, parts or combinations thereof disclosed in the specification exist, and do not exclude the possibility of existence of one or more other features, numbers, steps, actions, components, parts or combinations thereof.

[0055] Unless otherwise specified, " / " means or, for example, A / B can mean A or B; "and / or" in this document is only a description of the relationship between the associated objects, which means that there can be three relationships, for example, A and / or B can mean that A exists alone, A and B exist together, and B exists alone.

[0056] The terms "first", "second", and the like are merely intended to distinguish similar or identical technical features, and cannot be understood as indicating or implying relative importance or quantity of the technical features. Therefore, the features defined by "first", "second", and the like can be explicitly or implicitly included one or more of the features. In the description of the embodiments of the present application, unless otherwise specified, the meaning of the term "plurality" is two or more than two.

[0057] In the related art, although the degree of respiratory sinus arrhythmia is evaluated in heart rate variability analysis, since the time domain standard deviation type index and the high frequency band power index capable of reflecting the degree of respiratory sinus arrhythmia in the heart rate variability analysis are not specific indexes for respiratory sinus arrhythmia, but are related indexes in the heart rate variability analysis, the correlation of these indexes with the degree of respiratory sinus arrhythmia is usually attributed to the fact that respiratory sinus arrhythmia has a greater contribution to short-term heart rate variability, and when the degree of respiratory sinus arrhythmia is weak, the above indexes cannot accurately analyze the degree of respiratory sinus arrhythmia.

[0058] In view of this, the embodiments of the present application at least provide a signal processing method and related device, which can comprehensively analyze the respiratory signal and the heartbeat signal of a target object, obtain a cardiopulmonary coupling degree index for identifying the degree of respiratory sinus arrhythmia of the target object from the perspective of cardiopulmonary coupling, and thus more accurately analyze the respiratory sinus arrhythmia of the target object.

[0059] The signal processing method provided by the embodiments of the present application can be implemented by a computer device, which can be a terminal device or a server. The server can be a physical server, a server cluster composed of multiple physical servers, or a distributed system, or a cloud server providing cloud computing services. The terminal device includes but is not limited to a mobile phone, a computer, a smart voice interaction device, a smart home appliance, a vehicle-mounted terminal, an aircraft, etc. The terminal device and the server can be directly or indirectly connected through wired or wireless communication, which is not limited in the present application.

[0060] The signal processing method provided by the embodiments of the present application will be described below by means of method embodiments, as shown in Figure 1 Figure 1 The method flowchart of the signal processing method provided by the embodiments of the present application is shown in the foregoing computer device, which can be a server. The method includes the following steps.

[0061] S101, obtaining a respiratory signal and a heartbeat signal of a target object.

[0062] Specifically, the target object is an object that needs to be detected for respiratory sinus arrhythmia.

[0063] ​The respiratory signal refers to a physiological signal caused by respiratory movement. The characteristics of the respiratory signal can be collected through various channels, such as using a chest wall respiratory movement sensor, a nasopharyngeal pressure sensor, and the like. Preferably, the respiratory signal can be a respiratory impedance signal, or a respiratory movement signal collected by a stress-strain sensor, which can reflect respiratory cycle fluctuations. In this application, the respiratory signal can be represented by X r (t) represents.

[0064] The heartbeat signal refers to a physiological signal reflecting the situation of heart beating. The heartbeat signal can be recorded and analyzed by medical equipment such as an electrocardiogram (ECG). Preferably, the heartbeat signal can be an electrocardiogram signal, so as to reflect the heart cycle and systole and diastole. In this application, the heartbeat signal can be represented by X e (t) represents.

[0065] In order for the server to comprehensively analyze the degree of cardiopulmonary coupling of the target object in subsequent steps, the server can obtain the respiratory signal and the heartbeat signal of the target object.

[0066] In one possible implementation, the respiratory signal and the heartbeat signal of the target object are obtained in S101, including:

[0067] The respiratory signal and the heartbeat signal are synchronously collected.

[0068] Specifically, the server can directly synchronously collect the respiratory signal and the heartbeat signal through a collection device including two analog-to-digital converters. In actual application, the collection duration of the collection device can usually be 60s. In order to ensure synchronous collection of the respiratory signal and the heartbeat signal, the collection front end corresponding to the heartbeat signal and the collection front end corresponding to the respiratory signal both need to be controlled by a synchronous clock.

[0069] In one possible implementation, the respiratory signal and the heartbeat signal of the target object are obtained in S101, including:

[0070] The heartbeat signal is collected.

[0071] The respiratory signal is determined according to the heartbeat signal.

[0072] Specifically, the server can collect the heartbeat signal through a collection device including one analog-to-digital converter. Since the fluctuation of the chest cavity during the respiratory process will cause changes in the electrical activity of the heart, the server can determine the respiratory signal according to the heartbeat signal, for example, through the method of ECG-derived Respiration (EDR) to determine the respiratory signal according to the heartbeat signal.

[0073] S102, determining the instantaneous heart rate signal of the target object according to the heartbeat signal.

[0074] Specifically, after obtaining the respiration signal and the heartbeat signal of the target object in S101, in order to better analyze the cardiopulmonary coupling of the target object subsequently, the server can first determine the instantaneous heart rate signal of the target object according to the heartbeat signal. The instantaneous heart rate signal refers to the rate of each heartbeat of the target object. In the present application, the instantaneous heart rate signal can be represented by X(t), where t represents time. h (t) represents.

[0075] In a possible implementation, the determination of the instantaneous heart rate signal of the target object according to the heartbeat signal in S102 includes:

[0076] The instantaneous heart rate signal of the target object is determined according to the RR interval information of the heartbeat signal.

[0077] Specifically, the RR interval is a parameter on an electrocardiogram. The RR interval refers to the time interval between two consecutive R wave peaks in a ventricular depolarization (QRS) complex. The ventricular depolarization complex represents the depolarization process of the ventricle, and the R wave is the most prominent peak in the ventricular depolarization complex.

[0078] The server can determine the instantaneous heart rate signal of the target object according to the RR interval information of the heartbeat signal.

[0079] In a possible implementation, the determination of the instantaneous heart rate signal of the target object according to the RR interval information of the heartbeat signal includes:

[0080] The instantaneous heart rate signal of the target object is determined according to the reciprocal of the RR interval information of the heartbeat signal and through spline interpolation.

[0081] Specifically, since spline interpolation can be used to estimate and fill in missing heart rate data to estimate the instantaneous heart rate value at each time point, the server can determine the instantaneous heart rate signal of the target object according to the reciprocal of the RR interval information of the heartbeat signal and through spline interpolation, so that the determined instantaneous heart rate signal is equal in length to the respiration signal. For example, the server can identify the position sequence of the R wave peak in the heartbeat signal through the Pan-Tompkins algorithm, and then obtain an initial instantaneous heart rate signal. The initial instantaneous heart rate signal is then converted into an instantaneous heart rate signal equal in length to the respiration signal through cubic spline interpolation, so as to ensure the synchronization between the instantaneous heart rate signal and the respiration signal.

[0082] S103, determining the cardiopulmonary coupling degree index of the target object based on the respiration signal and the instantaneous heart rate signal.

[0083] Specifically, based on the respiratory signal and the instantaneous heart rate signal, the server can determine the cardiopulmonary coupling degree index of the target object by performing overall coupling analysis on the cardiopulmonary system of the target object. Since respiratory sinus arrhythmia mainly manifests as acceleration of heart rate during inhalation and deceleration of heart rate during exhalation, the cardiopulmonary coupling degree index, as an index capable of identifying the coupling degree between the respiratory signal and the instantaneous heart rate signal, can be used to identify the degree of respiratory sinus arrhythmia of the target object.

[0084] It should be noted that, unlike the analysis of heart rate variability in the related art, which only relies on the heartbeat signal to empirically analyze the degree of respiratory sinus arrhythmia, in the present application, the heartbeat signal is processed to obtain the corresponding instantaneous heart rate signal, and overall cardiopulmonary coupling analysis is performed on the instantaneous heart rate signal and the respiratory signal to obtain the cardiopulmonary coupling degree index, so as to more accurately analyze the respiratory sinus arrhythmia of the target object through the cardiopulmonary coupling index.

[0085] In one possible implementation, based on the respiratory signal and the instantaneous heart rate signal, the server determines the cardiopulmonary coupling degree index of the target object, including:

[0086] determining the time-frequency correlation strength between the respiratory signal and the instantaneous heart rate signal;

[0087] based on the time-frequency correlation strength, determining the cardiopulmonary coupling degree index of the target object.

[0088] Specifically, the server can first determine the time-frequency correlation strength between the respiratory signal and the instantaneous heart rate signal, which is used to identify the correlation between the respiratory signal and the instantaneous heart rate signal from the time and frequency dimensions.

[0089] After determining the time-frequency correlation, the server can determine the cardiopulmonary coupling degree index of the target object based on the time-frequency correlation strength.

[0090] In one possible implementation, the time-frequency correlation strength between the respiratory signal and the instantaneous heart rate signal is determined, including:

[0091] transforming the respiratory signal and the instantaneous heart rate signal into a time-frequency space to obtain a respiratory time-frequency signal corresponding to the respiratory signal and an instantaneous heart rate time-frequency signal corresponding to the instantaneous heart rate signal;

[0092] based on the same frequency power strength or the in-phase power strength between the respiratory time-frequency signal and the instantaneous heart rate time-frequency signal, determining the time-frequency correlation strength.

[0093] Specifically, in order to analyze the respiratory signal and the instantaneous heart rate signal from two dimensions of time and frequency, the server can transform the respiratory signal and the instantaneous heart rate signal into a time-frequency space to obtain a respiratory time-frequency signal corresponding to the respiratory signal and an instantaneous heart rate time-frequency signal corresponding to the instantaneous heart rate signal. In this application, the respiratory time-frequency signal in the time-frequency space can be represented as S r (t,w), and the instantaneous heart rate time-frequency signal can be represented as S h (t,w).

[0094] After obtaining the respiratory time-frequency signal and the instantaneous heart rate time-frequency signal, the server can determine the time-frequency correlation strength based on the co-frequency power intensity or the in-phase power intensity between the respiratory time-frequency signal and the instantaneous heart rate time-frequency signal, that is, from two dimensions of time and frequency.

[0095] In one possible implementation, the time-frequency correlation strength quantification method for calculating the cardiorespiratory coupling degree of the server can be cross wavelet transform.

[0096] Specifically, the server can perform cross wavelet transform on the instantaneous heart rate signal and the respiratory signal, that is, calculate the average power density of the instantaneous heart rate signal and the respiratory signal in the cross wavelet time-frequency spectrum, as the cardiorespiratory coupling degree, wherein the time window width used for calculating the cross wavelet time-frequency spectrum can be 60 s, and the selected frequency domain scale range can be 0.2 Hz~0.5 Hz, that is, the general respiratory frequency range.

[0097] In one possible implementation, based on the respiratory signal and the instantaneous heart rate signal, the cardiorespiratory coupling degree index of the target object is determined, including:

[0098] Determining the causality strength between the respiratory signal and the instantaneous heart rate signal, the causality strength being used to identify the one-way driving response strength between the respiration and the heart rate of the target object;

[0099] Determining the cardiorespiratory coupling degree index of the target object based on the causality strength.

[0100] Specifically, since respiratory sinus arrhythmia mainly manifests as acceleration of heart rate during inspiration and deceleration of heart rate during expiration, the respiratory signal and the instantaneous heart rate signal can be processed from the dimension of one-way driving response between the respiration and the heart rate, that is, the server can determine the causality strength between the respiratory signal and the instantaneous heart rate signal, the causality strength being used to identify the one-way driving response strength between the respiration and the heart rate of the target object.

[0101] After determining the causality strength, the server can determine the cardiorespiratory coupling degree index of the target object based on the causality strength.

[0102] In the embodiment, the server can determine the causality strength between the respiration signal and the instantaneous heart rate signal in four ways as follows: (1) Granger causality analysis based on time series prediction technology; (2) transfer entropy based on conditional probability distribution estimation; (3) convergent cross mapping based on phase space reconstruction; and (4) coupling term estimation based on a multi-oscillator dynamics coupling model (for example, Winfree coupling model).

[0103] In a possible implementation, the server can determine the causality strength between the respiration signal and the instantaneous heart rate signal by using the convergent cross mapping based on phase space reconstruction.

[0104] The convergent cross mapping refers to a directional manifold structure comparison of two signals in a phase space to analyze the causality strength between the two signals. In simple terms, compared with the time-frequency correlation evaluation method, the method further introduces directional information in the similarity comparison of the phase space structure, thereby reflecting the causality between the two signals.

[0105] Although the respiration signal and the instantaneous heart rate signal are both nonlinear signals, they both have obvious periodic rhythm, and therefore, a clear phase space manifold structure diagram can be reconstructed by using a simple delay coordinate method. Compared with a method based on linear model assumption such as Granger causality analysis, the convergent cross mapping method running in the phase space does not need linear model assumption, is particularly suitable for nonlinear signal analysis, and has small calculation amount, and therefore, is preferred.

[0106] After accurately and comprehensively analyzing the respiratory sinus arrhythmia of the target object from the perspective of cardiopulmonary coupling, in a possible implementation, the cardiopulmonary coupling degree index can be decoupled and quantified, that is, the signal processing method can further include the following steps.

[0107] S201, determining a heart beat response sensitivity index of the target object based on the respiration signal and the heart beat signal.

[0108] S202, determining a respiration driving force index of the target object according to the cardiopulmonary coupling degree index and the heart beat response sensitivity index.

[0109] Specifically, by the related steps of S101-S103, the cardiopulmonary coupling degree index of the target object is obtained from the perspective of cardiopulmonary coupling of the target object, so that the respiratory sinus arrhythmia of the target object is analyzed as a whole. On this basis, since the respiratory sinus arrhythmia mainly manifests that the heart rate accelerates during inspiration and decelerates during expiration, i.e., the respiration is the driver and the heart rate is the driven, the cardiopulmonary coupling degree index can be expressed as the product of the respiratory drive index (RDI) and the response sensitivity index (RSI), wherein the respiratory drive index is an index for measuring the driving strength of respiration and can be used to reflect the contribution of respiration in the respiratory sinus arrhythmia phenomenon, and the response sensitivity index can be used to describe the sensitivity of the heartbeat to certain stimulation or condition change and can be used to reflect the contribution of the heart in the respiratory sinus arrhythmia phenomenon.

[0110] Based on this, the server can first determine the response sensitivity index of the target object based on the respiration signal and the heartbeat signal, and then determine the respiratory drive index of the target object according to the cardiopulmonary coupling degree index and the response sensitivity index. That is, in the embodiment, the cardiopulmonary coupling degree index is decoupled and quantified from the perspective of multiplicative coupling of "driver-driven", so as to obtain the respiratory drive index which can independently evaluate the contribution of respiration and the response sensitivity index which can independently evaluate the contribution of heartbeat, so as to be able to more accurately analyze the respiratory sinus arrhythmia of the target object through the cardiopulmonary coupling degree index, the respiratory drive index and the response sensitivity index.

[0111] In a possible implementation, the determination of the response sensitivity index of the target object based on the respiration signal and the heartbeat signal in S201 includes:

[0112] determining the average respiration frequency of the target object based on the respiration signal, and determining the average heart rate and the average diastolic period of the target object based on the heartbeat signal;

[0113] The response sensitivity index is determined by the following formula: RSI=T D ×(f e ) 2 / f r

[0114] wherein RSI represents the response sensitivity index, T D represents the average diastolic period, f e represents the average heart rate, and f r represents the average respiration frequency.

[0115] Specifically, the heartbeat response sensitivity index can be calculated based on the respiratory signal and the heartbeat signal of the target object, that is, the server can determine the average respiratory frequency of the target object based on the respiratory signal, and determine the average heart rate and the average diastolic period length of the target object based on the heartbeat signal, for example, the server can determine the average respiratory frequency of the target object based on the respiratory signal with a window width of 60s, and determine the average heart rate and the average diastolic period length of the target object based on the heartbeat signal with a window width of 60s; the server can further determine the heartbeat response sensitivity index by the above formula.

[0116] In a possible implementation, the determination of the respiratory driving force index of the target object according to the cardiopulmonary coupling degree index and the heartbeat response sensitivity index in S202 comprises:

[0117] The respiratory driving force index is determined by the following formula: RDI=(q / RSI)×K

[0118] Wherein, RDI represents the respiratory driving force index, q represents the cardiopulmonary coupling degree index, RSI represents the heartbeat response sensitivity index, and K represents a preset normalization constant.

[0119] Specifically, according to the multiplicative coupling assumption of "cardiopulmonary coupling degree index= respiratory driving force index x heartbeat response sensitivity index" in the respiratory sinus arrhythmia phenomenon, the server can determine the respiratory driving force index by the above formula, wherein in actual application, the preset normalization constant can be 3-5, that is, the empirical value range of the ratio of human heart rate to respiratory frequency f e / f r .

[0120] Therefore, the application provides a signal processing method, which comprises: acquiring a respiratory signal and a heartbeat signal of a target object; determining an instantaneous heart rate signal of the target object according to the heartbeat signal; and determining a cardiopulmonary coupling degree index of the target object based on the respiratory signal and the instantaneous heart rate signal, the cardiopulmonary coupling degree index being used to identify the degree of respiratory sinus arrhythmia of the target object. Through the above method, the respiratory signal and the heartbeat signal of the target object can be comprehensively analyzed, and the cardiopulmonary coupling degree index used to identify the degree of respiratory sinus arrhythmia of the target object can be obtained from the perspective of cardiopulmonary coupling, so that the respiratory sinus arrhythmia of the target object can be more accurately analyzed.

[0121] In addition, in a further preferred embodiment, the cardiopulmonary coupling degree index is also decoupled and quantified from the perspective of "driver-driven" multiplicative coupling, so as to obtain a respiratory driving force index capable of independently evaluating the contribution degree of the respiratory aspect and a heartbeat response sensitivity index capable of independently evaluating the contribution degree of the heartbeat aspect, so that the respiratory sinus arrhythmia of the target object can be more comprehensively and accurately analyzed through the cardiopulmonary coupling degree index, the respiratory driving force index and the heartbeat response sensitivity index.

[0122] In the description of the present specification, the description referring to the terms "some possible embodiments", "some embodiments", "an example", "a specific example", or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application, and the above terms do not necessarily represent the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in any one or more embodiments or examples. In addition, the person skilled in the art can combine and combine the different embodiments or examples described in the specification and the features of the different embodiments or examples without contradiction.

[0123] Regarding the method flowchart of the embodiments of the present application, some operations are described as different steps executed in a certain order. Such flowcharts are illustrative rather than limiting. Some steps described herein can be grouped together and executed in a single operation, or some steps can be divided into multiple sub-steps, and some steps can be executed in an order different from that shown herein. Each step shown in the flowchart can be implemented in any way by any circuit structure and / or tangible mechanism (for example, by software running on a computer device, hardware (for example, processor or chip implemented logic function) and the like, and / or any combination thereof) in any manner.

[0124] The person skilled in the art can understand that in the method described in the above specific embodiments, the writing order of each step does not mean a strict execution order, and the specific execution order of each step should be determined by its function and possible inherent logic.

[0125] Based on the foregoing Figure 1 and Figure 2 , the present application provided by the device embodiments is described as follows, as shown in Figure 3 The signal processing device 300 comprises:

[0126] The acquisition module 301 is configured to acquire a breathing signal and a heartbeat signal of a target object.

[0127] The first determination module 302 is configured to determine an instantaneous heart rate signal of the target object according to the heartbeat signal.

[0128] The second determination module 303 is configured to determine a cardiopulmonary coupling degree index of the target object based on the breathing signal and the instantaneous heart rate signal, the cardiopulmonary coupling degree index being used to identify the degree of respiratory sinus arrhythmia of the target object.

[0129] In a possible implementation, the first determination module 302 is configured to:

[0130] According to the RR interval information of the heartbeat signal, a momentary heart rate signal of the target object is determined.

[0131] In a possible implementation, the first determination module 302 is configured to:

[0132] According to the RR interval information of the heartbeat signal, the momentary heart rate signal of the target object is determined by taking the reciprocal and performing spline interpolation.

[0133] In a possible implementation, the second determination module 303 is configured to:

[0134] determine a time-frequency correlation strength between the respiratory signal and the momentary heart rate signal;

[0135] determine a cardiopulmonary coupling degree index of the target object based on the time-frequency correlation strength.

[0136] In a possible implementation, the second determination module 303 is configured to:

[0137] transform the respiratory signal and the momentary heart rate signal into a time-frequency space to obtain a respiratory time-frequency signal corresponding to the respiratory signal and a momentary heart rate time-frequency signal corresponding to the momentary heart rate signal;

[0138] determine the time-frequency correlation strength based on a same-frequency power strength or a same-phase power strength between the respiratory time-frequency signal and the momentary heart rate time-frequency signal.

[0139] In a possible implementation, the second determination module 303 is configured to:

[0140] determine a causality strength between the respiratory signal and the momentary heart rate signal, the causality strength being used to identify a one-way driving response strength between the respiration and the heart rate of the target object;

[0141] determine the cardiopulmonary coupling degree index of the target object based on the causality strength.

[0142] In a possible implementation, the second determination module 303 is further configured to:

[0143] determine a heartbeat response sensitivity index of the target object based on the respiratory signal and the heartbeat signal;

[0144] determine a respiratory driving force index of the target object according to the cardiopulmonary coupling degree index and the heartbeat response sensitivity index.

[0145] In a possible implementation, the second determination module 303 is further configured to:

[0146] determine an average respiratory frequency of the target object based on the respiratory signal, determine an average heart rate and an average diastolic period length of the target object based on the heartbeat signal.

[0147] The heartbeat response sensitivity index is determined by the following formula: RSI=T D ×(f e ) 2 / f r

[0148] wherein RSI represents the heartbeat response sensitivity index, T D represents the average diastolic period length, f e represents the average heart rate, and f r represents the average respiratory frequency.

[0149] In a possible implementation, the second determining module 303 is further configured to:

[0150] The respiratory drive index is determined by the following formula: RDI=(q / RSI)×K

[0151] wherein RDI represents the respiratory drive index, q represents the cardiopulmonary coupling degree index, RSI represents the heartbeat response sensitivity index, and K represents a preset normalization constant.

[0152] In a possible implementation, the acquisition module 301 is configured to:

[0153] synchronously acquire the respiratory signal and the heartbeat signal.

[0154] In a possible implementation, the acquisition module 301 is configured to:

[0155] acquire the heartbeat signal;

[0156] determine the respiratory signal according to the heartbeat signal.

[0157] It should be noted that the apparatus in the embodiments of the present application can implement each process of the embodiments of the foregoing method, and achieve the same effects and functions, which will not be described here.

[0158] The present application also provides an electronic device, comprising a processor, a memory and a bus. The memory stores machine-readable instructions executable by the processor, and the processor communicates with the memory through the bus when the electronic device is running. When the machine-readable instructions are executed by the processor, the following processing is performed:

[0159] acquiring a respiratory signal and a heartbeat signal of a target object;

[0160] determining an instantaneous heart rate signal of the target object according to the heartbeat signal;

[0161] determining a cardiopulmonary coupling degree index of the target object based on the respiratory signal and the instantaneous heart rate signal, the cardiopulmonary coupling degree index being used to identify a degree of respiratory sinus arrhythmia of the target object.

[0162] The embodiment of the present application further provides a computer readable storage medium, and the computer readable storage medium stores a computer program. When the computer program is run by a processor, steps of the signal processing method described in the method embodiment are executed. The storage medium can be a volatile or non-volatile computer readable storage medium.

[0163] The embodiment of the present application further provides a computer program product, and the computer program product includes a computer program. The computer program product carries program codes, and the program codes include instructions used for executing steps of the signal processing method described in the method embodiment. Details can be referred to the method embodiment, and will not be described here.

[0164] The computer program product can be specifically implemented by means of hardware, software or combination thereof. In an optional embodiment, the computer program product is specifically embodied as a computer storage medium. In another optional embodiment, the computer program product is specifically embodied as a software product, such as a software development kit (SDK) and the like.

[0165] The embodiments of the present application are described in a progressive manner, and the same or similar parts of each embodiment can be referred to each other. Each embodiment mainly describes differences from other embodiments. Especially, the apparatus, device and computer readable storage medium are basically similar to the method embodiment, so the description is simplified, and the related parts can be referred to the description of the method embodiment.

[0166] The apparatus, device and computer readable storage medium provided by the embodiments of the present application correspond to the method, so the apparatus, device and computer readable storage medium also have similar beneficial technical effects as the method. Since the beneficial technical effects of the method have been described in detail above, the beneficial technical effects of the apparatus, device and computer readable storage medium will not be described here.

[0167] Although the spirit and principles of the present application have been described with reference to several specific embodiments, it should be understood that the present application is not limited to the disclosed specific embodiments, and the division of aspects does not mean that the features in these aspects cannot be combined. The present application is intended to cover various modifications and equivalent arrangements included in the spirit and scope of the appended claims.

Claims

1. A signal processing method, characterized by, The method comprises: acquiring a respiratory signal and a heartbeat signal of a target object; determining an instantaneous heart rate signal of the target object according to the heartbeat signal; determining a cardiopulmonary coupling degree index q of the target object based on the respiratory signal and the instantaneous heart rate signal, the cardiopulmonary coupling degree index being used to identify a degree of respiratory sinus arrhythmia of the target object; the cardiopulmonary coupling degree index comprises two parts of a respiratory driving force index and a heartbeat response sensitivity index, wherein the respiratory driving force index is used to identify the contribution of respiratory factors in the degree of respiratory sinus arrhythmia, and the heartbeat response sensitivity index is used to identify the contribution of heartbeat factors in the degree of respiratory sinus arrhythmia; the determination method of the heartbeat response sensitivity index comprises: determining an average respiratory frequency of the target object based on the respiratory signal; determining an average heart rate and an average diastolic period length of the target object based on the heartbeat signal; and determining the heartbeat response sensitivity index through the following formula: RSI = (T_D) x (f_e) 2 / (f_r) wherein RSI represents the heartbeat response sensitivity index, (T_D) represents the average diastolic period length, (f_e) represents the average heart rate, and (f_r) represents the average respiratory frequency; the respiratory driving force index is determined according to the cardiopulmonary coupling degree index and the heartbeat response sensitivity index, comprising: determining the respiratory driving force index through the following formula: RDI = (q / RSI) x K wherein RDI represents the respiratory driving force index, q represents the cardiopulmonary coupling degree index, RSI represents the heartbeat response sensitivity index, and K represents a preset normalization constant.

2. The method of claim 1, wherein, The determination of the instantaneous heart rate signal of the target object according to the heartbeat signal comprises: determining the instantaneous heart rate signal of the target object according to RR interval information of the heartbeat signal.

3. The method of claim 2, wherein, The determination of the instantaneous heart rate signal of the target object according to the RR interval information of the heartbeat signal comprises: determining the instantaneous heart rate signal of the target object according to the RR interval information of the heartbeat signal by taking the inverse and performing spline interpolation.

4. The method of claim 1, wherein, The determination of the cardiopulmonary coupling degree index of the target object based on the respiratory signal and the instantaneous heart rate signal comprises: determining a time-frequency correlation strength between the respiratory signal and the instantaneous heart rate signal; determining the cardiopulmonary coupling degree index of the target object based on the time-frequency correlation strength.

5. The method of claim 4, wherein, The determination of the time-frequency correlation strength between the respiratory signal and the instantaneous heart rate signal comprises: transforming the respiratory signal and the instantaneous heart rate signal into a time-frequency space to obtain a respiratory time-frequency signal corresponding to the respiratory signal and an instantaneous heart rate time-frequency signal corresponding to the instantaneous heart rate signal; determining the time-frequency correlation strength based on a same-frequency power strength or a same-phase power strength between the respiratory time-frequency signal and the instantaneous heart rate time-frequency signal.

6. The method of claim 1, wherein, The determination of the cardiopulmonary coupling degree index of the target object based on the respiratory signal and the instantaneous heart rate signal comprises: determine a causality strength between the respiratory signal and the instantaneous heart rate signal, the causality strength being used to identify a unidirectional driving response strength between respiration and heart rate of the target object; determine a cardiopulmonary coupling degree index of the target object based on the causality strength.

7. The method of claim 1, wherein, The acquiring the respiratory signal and the heartbeat signal of the target object comprises: synchronously collecting the respiratory signal and the heartbeat signal.

8. The method of claim 1, wherein, The acquiring the respiratory signal and the heartbeat signal of the target object comprises: collecting the heartbeat signal; and determining the respiratory signal according to the heartbeat signal.

9. A signal processing device, characterized by The method comprises: an acquiring module configured to acquire a respiratory signal and a heartbeat signal of a target object; a first determining module configured to determine an instantaneous heart rate signal of the target object according to the heartbeat signal; a second determining module configured to determine a cardiopulmonary coupling degree index q of the target object based on the respiratory signal and the instantaneous heart rate signal, the cardiopulmonary coupling degree index being used to identify a degree of respiratory sinus arrhythmia of the target object; the second determining module is further configured to acquire an average respiratory frequency (f_r) based on the respiratory signal, acquire an average heart rate (f_e) and an average diastolic period length (T_D) based on the heartbeat signal, and then determine a heartbeat response sensitivity index RSI=(T_D)×(f_e)^2 / (f_r) of the target object, the heartbeat response sensitivity index being used to identify a contribution of a heartbeat factor in the degree of respiratory sinus arrhythmia; the second determining module is further configured to determine a respiratory driving force index RDI=(q / RSI)×K of the target object based on the cardiopulmonary coupling degree index q, the heartbeat response sensitivity index RSI and a preset normalization constant K, the respiratory driving force index being used to identify a contribution of a respiratory factor in the degree of respiratory sinus arrhythmia.

10. An electronic device, comprising: The method comprises: a processor, a memory and a bus, the memory stores machine readable instructions executable by the processor, when the electronic device is running, the processor and the memory communicate through the bus, the machine readable instructions are executed by the processor to execute the signal processing method in any one of claims 1 to 8.

11. A computer readable storage medium, characterized in that, The computer readable storage medium stores a computer program, the computer program is executed by the processor to execute the signal processing method in any one of claims 1 to 8.

12. A computer program product, characterised in that, The computer program is executed by the processor to execute the signal processing method in any one of claims 1 to 8.

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