Heart rate variability monitoring method, device, radar and readable storage medium

Abstract

The present invention provides a heart rate variability monitoring method, device, radar and readable storage medium, the method comprising: obtaining a heartbeat signal obtained by radar detection of a human body; normalizing the heartbeat signal based on the amplitude of the heartbeat signal to reduce the interference of breathing on the heartbeat signal; performing Fourier transform on the normalized heartbeat signal to obtain an amplitude spectrum of the normalized heartbeat signal, and setting the amplitude of the frequency point whose amplitude does not meet the preset amplitude condition in the amplitude spectrum to zero, thereby eliminating the interference of other frequencies; performing inverse Fourier transform on the amplitude spectrum after eliminating the frequency interference to obtain a reconstructed heartbeat time domain signal; and calculating a heart rate variability index according to the reconstructed heartbeat time domain signal, thereby improving the accuracy of the heart rate variability index.

Description

Technical Field

[0001] The present invention relates to the field of radar technology, and in particular to a heart rate variability monitoring method, device, radar and readable storage medium. Background Art

[0002] As society pays more and more attention to the elderly care industry, the demand for smart elderly care products is also increasing. A typical demand is a radar-based non-contact vital signs monitoring device. This device monitors the vital signs of the elderly in bed in a non-contact manner and outputs the elderly's breathing and heart rate in real time. With the continuous advancement of radar technology, the accuracy of respiratory and heart rate detection is getting higher and higher. In addition to respiratory and heart rate, heart rate variability (HRV) is also one of the indicators of medical concern. Specifically, heart rate focuses on the average number of heartbeats per minute, while heart rate variability (HRV) measures the change in the time between consecutive heartbeats. The time between two heartbeats is measured in milliseconds (ms) and is called the Inter-Beat Interval (IBI).

[0003] The radar detects the rise and fall of the chest cavity to obtain the human body's breathing and heart rate, and the echo contains both breathing and heart rate information. Since the breathing rate and heart rate are in different frequency ranges, the echo can be filtered separately through bandpass filters with different passbands to obtain breathing and heart rate signals. The peaks of the heart rate signal are further extracted and the time intervals between the peaks are calculated to obtain the IBI. The statistical value of the IBI over a period of time is further calculated to obtain the HRV. However, since the amplitude of human breathing is much larger than that of the heart rate, even if the radar echo passes through the bandpass filter, the heart rate signal is still easily interfered by breathing, resulting in inaccurate peak position extraction and inaccurate HRV monitoring. Summary of the invention

[0004] In view of this, the present invention provides a heart rate variability monitoring method, device, radar and readable storage medium, which can solve the problem of inaccurate HRV monitoring caused by respiratory interference.

[0005] In a first aspect, an embodiment of the present invention provides a heart rate variability monitoring method, comprising:

[0006] Obtain the heartbeat signal detected by radar on human body;

[0007] normalizing the heartbeat signal based on the amplitude of the heartbeat signal;

[0008] Performing Fourier transform on the normalized heartbeat signal to obtain an amplitude spectrum of the normalized heartbeat signal, and setting the amplitudes of frequency points in the amplitude spectrum whose amplitudes do not meet a preset amplitude condition to zero to obtain an amplitude spectrum with frequency interference removed;

[0009] Performing an inverse Fourier transform on the amplitude spectrum after removing the frequency interference to obtain a reconstructed heartbeat time domain signal;

[0010] The beat interval is calculated according to the reconstructed heartbeat time domain signal, and the heart rate variability index is calculated based on the beat interval.

[0011] In a second aspect, an embodiment of the present invention provides a heart rate variability monitoring device, comprising:

[0012] A heartbeat signal acquisition module is used to acquire the heartbeat signal detected by the radar on the human body;

[0013] A normalization processing module, used for performing normalization processing on the heartbeat signal based on the amplitude of the heartbeat signal;

[0014] An amplitude spectrum acquisition module is used to perform Fourier transform on the normalized heartbeat signal to obtain the amplitude spectrum of the normalized heartbeat signal, and set the amplitude of the frequency points in the amplitude spectrum that do not meet the preset amplitude condition to zero to obtain the amplitude spectrum with frequency interference removed;

[0015] A heartbeat time domain signal acquisition module is used to perform an inverse Fourier transform on the amplitude spectrum after removing the frequency interference to obtain a reconstructed heartbeat time domain signal;

[0016] The heart rate variability index calculation module is used to calculate the beat interval according to the reconstructed heartbeat time domain signal, and calculate the heart rate variability index based on the beat interval.

[0017] In a third aspect, an embodiment of the present invention provides a radar, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the method described in any possible implementation manner of the first aspect are implemented.

[0018] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method described in any possible implementation manner of the first aspect above are implemented.

[0019] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0020] The embodiment of the present invention normalizes the heartbeat signal by the amplitude of the heartbeat signal; it can reduce the interference of breathing on the heartbeat signal; then Fourier transform is performed on the normalized heartbeat signal to obtain the amplitude spectrum of the normalized heartbeat signal, and the amplitude of the frequency point whose amplitude does not meet the preset amplitude condition in the amplitude spectrum is set to zero, thereby eliminating the interference of other frequencies; finally, the amplitude spectrum with the frequency interference eliminated is inverse Fourier transformed; the heart rate variability index is calculated according to the reconstructed heartbeat time domain signal, thereby improving the accuracy of the heart rate variability index. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0022] Figure 1 is a flow chart of an implementation of a heart rate variability monitoring method provided by an embodiment of the present invention;

[0023] Figure 2 is a schematic diagram of a heartbeat signal before normalization provided by an embodiment of the present invention;

[0024] Figure 3 is a schematic diagram of a normalized heartbeat signal provided by an embodiment of the present invention;

[0025] Figure 4 is a schematic diagram of the structure of a heart rate variability monitoring device provided by an embodiment of the present invention;

[0026] Figure 5 Schematic diagram of a radar provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0027] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.

[0028] In order to make the purpose, technical solutions and advantages of the present invention more clear, specific embodiments will be described below in conjunction with the accompanying drawings.

[0029] See also Figure 1 , which shows a flowchart of the implementation of the heart rate variability monitoring method provided by an embodiment of the present invention, and the method is described in detail as follows:

[0030] S101: Acquire a heartbeat signal detected by a radar on a human body.

[0031] In this embodiment, in order to perform non-contact monitoring of heart rate variability, a radar may be set up facing the human body, and a detection signal is sent to the human body by the radar to detect the heartbeat signal of the human body.

[0032] Preferably, the radar may be a millimeter wave radar, and the radar may be mounted on the ceiling above the bed. The radar may monitor the user's heartbeat signal in real time while the user is resting.

[0033] In a possible implementation, the specific implementation process of S101 includes:

[0034] Acquire the echo signal obtained by radar detecting human body;

[0035] The echo signal is band-pass filtered to extract the heartbeat signal.

[0036] Specifically, the radar receives the echo signal transmitted to the human body and reflected by the human body through the transmitting and receiving module, and preprocesses the echo signal to obtain the preprocessed echo signal. Among them, the radar obtains a frame of echo signal every ts seconds, and obtains T seconds of data in total, so the number of data frames is N = T / ts, and the preprocessed echo signal is S(n), n = 1, 2, ... N.

[0037] Furthermore, the preprocessing process of the echo signal may include:

[0038] Perform FFT (fast Fourier transform) on the echo signal to obtain a range image, find the distance point where the human body is located, save the data of the distance point, and use it as the preprocessed echo signal.

[0039] After obtaining the preprocessed echo signal, the echo signal S(n) is bandpass filtered, and the filter passband range is 0.8Hz~2Hz, and the heartbeat signal S_heart(i) is extracted, i=1,2,...N, wherein the passband range 0.8Hz~2Hz is the heartbeat frequency range.

[0040] S102: Normalizing the heartbeat signal based on the amplitude of the heartbeat signal.

[0041] In a possible implementation, the specific implementation process of S102 includes:

[0042] For each signal point in the heartbeat signal, calculate the amplitude mean value of the signal point based on the amplitude of the signal point and the signal points within a preset range around the signal point, and divide the amplitude of the signal point by the corresponding amplitude mean value of the signal point to obtain the signal point after normalization processing.

[0043] In a possible implementation manner, the specific implementation process of S102 further includes:

[0044] Based on the formula Calculate the amplitude mean value of the signal point;

[0045] Wherein, S_mean(i) represents the amplitude mean value of the i-th signal point, S_heart(i) represents the amplitude of the i-th signal point, and N represents the number of signal points of the heartbeat signal.

[0046] In this embodiment, if K + 1 ≤ i ≤ N - K, then take the mean value of the absolute values of the amplitudes of S_mean(i) and its K signal points on the left and right to obtain the amplitude mean value of S_mean(i). If i < K + 1, then take the mean value of the absolute values of the amplitudes of S_mean(i) and its K signal points on the right to obtain the amplitude mean value of S_mean(i); if i > N - K, then take the mean value of the absolute values of the amplitudes of S_mean(i) and its K signal points on the left to obtain the amplitude mean value of S_mean(i). Wherein, K is a preset value, and 0 < K < N. Preferably, K can be taken as 5.

[0047] After obtaining the amplitude mean value of S_mean(i), divide S_heart(i) by S_mean(i) to obtain the amplitude-normalized signal S_heart_norn(i). The S_heart(i) before normalization is shown in Figure 2 The S_heart_norn(i) after normalization is shown in Figure 3 .

[0048] As can be seen from the above embodiments, this embodiment performs amplitude normalization on the band-pass filtered heartbeat signal, which can reduce the interference of respiration on the heartbeat signal.

[0049] S103: Perform Fourier transform on the normalized heartbeat signal to obtain the amplitude spectrum of the normalized heartbeat signal, and set the amplitudes of the frequency points in the amplitude spectrum that do not meet the preset amplitude condition to zero to obtain the amplitude spectrum with frequency interference removed.

[0050] Since the radar is a non-contact detector and the signal has a large attenuation in the air, the signal-to-noise ratio of the heartbeat is relatively low. Directly extracting the wave peaks from the time-domain signal of the heartbeat results in large errors in the IBI and HRV, making it difficult to meet the accuracy requirements for medical use. Therefore, in this embodiment, after normalizing the heartbeat signal, the radar converts the heartbeat signal to the frequency domain to obtain the spectrum of the heartbeat signal, and then calculates the amplitude of each frequency point in the spectrum to obtain the amplitude spectrum SFFTabs_heart.

[0051] Specifically, the amplitude spectrum is the curve of the signal amplitude and frequency (angular frequency). In the frequency-domain description of the signal, with frequency as the independent variable and the amplitudes of the various frequency components that make up the signal as the dependent variable, such a frequency function is called the amplitude spectrum, which characterizes the distribution of the signal amplitude with frequency.

[0052] In this embodiment, the radar can sort all the frequency points in the amplitude spectrum in descending order of amplitude, find the top M frequency points, retain the amplitudes of these M frequency points in SFFTabs_heart, and set the values of other frequency points to zero, so as to extract the main heartbeat frequencies and obtain the amplitude spectrum with frequency interference removed.

[0053] Specifically, 0 < M < N / 2; a typical value can be 20.

[0054] It can be understood that as a variation of the above method, the radar can also sort all the frequency points in the amplitude spectrum in ascending order of amplitude, find the top M frequency points, and set the amplitudes of the top M frequency points to zero to obtain the amplitude spectrum with frequency interference removed.

[0055] The radar can also set the amplitudes of all frequency points in the amplitude spectrum that are less than a preset amplitude threshold to zero to obtain the amplitude spectrum with frequency interference removed.

[0056] S104: Perform an inverse Fourier transform on the amplitude spectrum with frequency interference removed to obtain the reconstructed heartbeat time-domain signal.

[0057] S105: Calculate the beat interval based on the reconstructed heartbeat time-domain signal, and calculate the heart rate variability index based on the beat interval.

[0058] In a possible implementation manner, the specific implementation process of S105 includes:

[0059] S201: Obtain the peak positions in the reconstructed heartbeat time-domain signal;

[0060] S202: Perform weighted calculations on each peak position respectively, and calculate the beat interval based on the weighted peak positions.

[0061] In a possible implementation, the specific implementation process of S202 includes:

[0062] Perform weighted calculation on each peak position based on the peak weighted calculation formula;

[0063] Inputting the peak position after weighted calculation into the beat interval calculation formula to obtain the beat interval;

[0064] The peak weighted calculation formula is:

[0065]

[0066] Wherein, indWeight(n) represents the nth peak position after weighted calculation, ind(n) represents the nth peak position, L represents the total number of peaks, and S_heart_rebuid(n) represents the amplitude of the nth peak position in the reconstructed heartbeat time domain signal;

[0067] The beat interval calculation formula is:

[0068] IBI(n)=[indWeight(n+1)-indWeight(n)]*ts,n=1,2...L-1;

[0069] Where IBI(n) represents the beat interval of the nth peak position, and ts represents the radar frame period.

[0070] In the prior art, the peak extraction position is usually an integer multiple of the sampling interval. Due to the radar sampling rate, the IBI estimation accuracy is limited. In order to reduce the error caused by the radar sampling interval, this embodiment uses the peak position and the peak positions of the two adjacent left and right peak positions and their time domain heartbeat signals for each peak position to calculate the position mean of the peak position when n=2,3...L-1. When n=1 or n=L, indWeight(n)=ind(n).

[0071] Specifically, the position of the heartbeat signal point in the time domain is the time corresponding to the heartbeat signal point.

[0072] In a possible implementation, the heart rate variability index includes an average IBI, a root mean square of consecutive IBI differences and / or a standard deviation of the IBI; the specific implementation process of S105 also includes:

[0073] Based on the formula Calculate the average IBI;

[0074] Based on the formula Calculate the RMS of consecutive IBI differences;

[0075] Based on the formula Calculate the standard deviation of IBI;

[0076] Where IBI(n) represents the beat interval of the nth peak position; L represents the total number of peaks, IBI_mean represents the average IBI, RMSSD represents the root mean square of the difference between consecutive IBIs, and SDRR represents the standard deviation of IBI.

[0077] In this embodiment, the communication module of the radar can output the above-mentioned heart rate variability index to the outside for use by third-party devices. Among them, the output interface can be a network port, a serial port, etc.

[0078] The embodiment of the present invention normalizes the heartbeat signal through the amplitude of the heartbeat signal; the interference of breathing on the heartbeat signal can be reduced; then the normalized heartbeat signal is Fourier transformed to obtain the amplitude spectrum of the normalized heartbeat signal, and the frequency points in the amplitude spectrum are sorted in descending order according to the amplitude, and the amplitudes of the frequency points not ranked in the first M positions are set to zero, thereby eliminating the interference of other frequencies; finally, the amplitude spectrum with the frequency interference eliminated is inverse Fourier transformed; the peak position of the reconstructed heartbeat time domain signal is extracted, and the extracted peak position is weightedly calculated, thereby reducing the error caused by the radar sampling interval and improving the accuracy of the heart rate variability index.

[0079] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0080] The following is an embodiment of the device of the present invention. For details not described in detail therein, reference may be made to the corresponding method embodiment described above.

[0081] Figure 4 FIG. 1 is a schematic diagram showing the structure of a heart rate variability monitoring device provided by an embodiment of the present invention. For the convenience of explanation, Figure 4 Only the parts related to the embodiments of the present invention are shown, which are described in detail as follows:

[0082] like Figure 4 As shown, the heart rate variability monitoring device 100 includes:

[0083] A heartbeat signal acquisition module is used to acquire the heartbeat signal detected by the radar on the human body;

[0084] A normalization processing module, used for performing normalization processing on the heartbeat signal based on the amplitude of the heartbeat signal;

[0085] An amplitude spectrum acquisition module is used to perform Fourier transform on the normalized heartbeat signal to obtain the amplitude spectrum of the normalized heartbeat signal, and set the amplitude of the frequency points in the amplitude spectrum that do not meet the preset amplitude condition to zero to obtain the amplitude spectrum with frequency interference removed;

[0086] A heartbeat time domain signal acquisition module is used to perform an inverse Fourier transform on the amplitude spectrum after removing the frequency interference to obtain a reconstructed heartbeat time domain signal;

[0087] The heart rate variability index calculation module is used to calculate the beat interval according to the reconstructed heartbeat time domain signal, and calculate the heart rate variability index based on the beat interval.

[0088] In a possible implementation, the normalization processing module is used to:

[0089] For each signal point in the heartbeat signal, the amplitude mean of the signal point is calculated based on the amplitudes of the signal point and signal points within a preset range around the signal point, and the amplitude of the signal point is divided by the amplitude mean corresponding to the signal point to obtain a normalized signal point.

[0090] In a possible implementation, the normalization processing module is further used for:

[0091] Based on the formula Calculate the amplitude mean of the signal point;

[0092] Wherein, S_mean(i) represents the amplitude mean of the i-th signal point, S_heart(i) represents the amplitude of the i-th signal point, and N represents the number of signal points of the heartbeat signal.

[0093] In a possible implementation, the heart rate variability index calculation module includes:

[0094] A peak position extraction unit, used to obtain the peak position in the reconstructed heartbeat time domain signal;

[0095] The beat interval calculation unit is used to perform weighted calculation on each peak position respectively, and calculate the beat interval based on the peak position after weighted calculation.

[0096] In a possible implementation, the beat interval calculation unit is specifically used to:

[0097] Perform weighted calculation on each peak position based on the peak weighted calculation formula;

[0098] Inputting the peak position after weighted calculation into the beat interval calculation formula to obtain the beat interval;

[0099] The peak weighted calculation formula is:

[0100]

[0101] Wherein, indWeight(n) represents the nth peak position after weighted calculation, ind(n) represents the nth peak position, L represents the total number of peaks, and S_heart_rebuid(n) represents the amplitude of the nth peak position in the reconstructed heartbeat time domain signal;

[0102] The beat interval calculation formula is:

[0103] IBI(n)=[indWeight(n+1)-indWeight(n)]*ts,n=1,2...L-1;

[0104] Where IBI(n) represents the beat interval of the nth peak position, and ts represents the radar frame period.

[0105] In a possible implementation, the heart rate variability index includes an average IBI, a root mean square of consecutive IBI differences and / or a standard deviation of the IBI; the heart rate variability index calculation module further includes a heart rate variability index calculation unit, which is used to:

[0106] Based on the formula Calculate the average IBI;

[0107] Based on the formula Calculate the RMS of consecutive IBI differences;

[0108] Based on the formula Calculate the standard deviation of IBI;

[0109] Where IBI(n) represents the beat interval of the nth peak position; L represents the total number of peaks, IBI_mean represents the average IBI, RMSSD represents the root mean square of the difference between consecutive IBIs, and SDRR represents the standard deviation of IBI.

[0110] In a possible implementation, the heartbeat signal acquisition module is specifically used to:

[0111] Acquire the echo signal obtained by radar detecting human body;

[0112] The echo signal is band-pass filtered to extract the heartbeat signal.

[0113] The embodiment of the present invention normalizes the heartbeat signal through the amplitude of the heartbeat signal; the interference of breathing on the heartbeat signal can be reduced; then the normalized heartbeat signal is Fourier transformed to obtain the amplitude spectrum of the normalized heartbeat signal, and the frequency points in the amplitude spectrum are sorted in descending order according to the amplitude, and the amplitudes of the frequency points not ranked in the first M positions are set to zero, thereby eliminating the interference of other frequencies; finally, the amplitude spectrum with the frequency interference eliminated is inverse Fourier transformed; the peak position of the reconstructed heartbeat time domain signal is extracted, and the extracted peak position is weightedly calculated, thereby reducing the error caused by the radar sampling interval and improving the accuracy of the heart rate variability index.

[0114] The heart rate variability monitoring device provided in this embodiment can be used to execute the above-mentioned heart rate variability monitoring method embodiment. Its implementation principle and technical effects are similar, and this embodiment will not be repeated here.

[0115] Figure 5 FIG. 1 is a schematic diagram of a radar provided by an embodiment of the present invention. Figure 5 As shown, the radar 5 of this embodiment includes: a processor 50, a memory 51, and a computer program 52 stored in the memory 51 and executable on the processor 50. When the processor 50 executes the computer program 52, the steps in the above-mentioned various heart rate variability monitoring method embodiments are implemented, for example Figure 1 Alternatively, when the processor 50 executes the computer program 52, the functions of each module / unit in the above-mentioned device embodiments are realized, for example Figure 4 The functions of the modules 110 to 150 are shown.

[0116] Exemplarily, the computer program 52 may be divided into one or more modules / units, which are stored in the memory 51 and executed by the processor 50 to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, which are used to describe the execution process of the computer program 52 in the radar 5.

[0117] The radar 5 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The radar 5 may include, but is not limited to, a processor 50 and a memory 51. Those skilled in the art will appreciate that Figure 5 It is only an example of radar 5 and does not constitute a limitation of radar 5. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the radar may also include input and output devices, network access devices, buses, etc.

[0118] The processor 50 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0119] The memory 51 may be an internal storage unit of the radar 5, such as a hard disk or memory of the radar 5. The memory 51 may also be an external storage device of the radar 5, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the radar 5. Further, the memory 51 may also include both an internal storage unit of the radar 5 and an external storage device. The memory 51 is used to store the computer program and other programs and data required by the radar. The memory 51 may also be used to temporarily store data that has been output or is to be output.

[0120] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0121] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0122] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0123] In the embodiments provided by the present invention, it should be understood that the disclosed devices / radars and methods can be implemented in other ways. For example, the device / radar embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0124] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0125] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0126] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned heart rate variability monitoring method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practices in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practices, computer-readable media does not include electrical carrier signals and telecommunication signals.

[0127] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A heart rate variability monitoring method, characterized in that: include: Obtain the heartbeat signal detected by radar on human body; normalizing the heartbeat signal based on the amplitude of the heartbeat signal; Performing Fourier transform on the normalized heartbeat signal to obtain an amplitude spectrum of the normalized heartbeat signal, and setting the amplitudes of frequency points in the amplitude spectrum whose amplitudes do not meet a preset amplitude condition to zero to obtain an amplitude spectrum with frequency interference removed; Performing an inverse Fourier transform on the amplitude spectrum after removing the frequency interference to obtain a reconstructed heartbeat time domain signal; Calculating the beat interval according to the reconstructed heartbeat time domain signal, and calculating the heart rate variability index based on the beat interval; The normalizing the heartbeat signal based on the amplitude of the heartbeat signal comprises: For each signal point in the heartbeat signal, calculate the amplitude mean of the signal point based on the amplitudes of the signal point and signal points within a preset range around the signal point, and divide the amplitude of the signal point by the amplitude mean corresponding to the signal point to obtain a normalized signal point; The calculating the amplitude mean of the signal point based on the amplitudes of the signal point and the signal points within a preset range around the signal point includes: Based on the formula Calculate the amplitude mean of the signal point; Wherein, S_mean(i) represents the amplitude mean of the i-th signal point, S_heart(i) represents the amplitude of the i-th signal point, N represents the number of signal points of the heartbeat signal; K represents a preset value, and 0 <K<N。 2. The heart rate variability monitoring method according to claim 1, characterized in that: The step of calculating the beat interval according to the reconstructed heartbeat time domain signal comprises: Obtaining the peak position of the reconstructed heartbeat time domain signal; Each peak position is weighted and the beat interval is calculated based on the weighted peak position.

3. The heart rate variability monitoring method according to claim 2, characterized in that: The step of performing weighted calculation on each peak position and calculating the beat interval based on the peak position after weighted calculation includes: Perform weighted calculation on each peak position based on the peak weighted calculation formula; Inputting the peak position after weighted calculation into the beat interval calculation formula to obtain the beat interval; The peak weighted calculation formula is: Wherein, indWeight(n) represents the nth peak position after weighted calculation, ind(n) represents the nth peak position, L represents the total number of peaks, and S_heart_rebuid(n) represents the amplitude of the nth peak position in the reconstructed heartbeat time domain signal; The beat interval calculation formula is: IBI(n)=[indWeight(n+1)-indWeight(n)]*ts,n=1,2...L-1; Where IBI(n) represents the beat interval of the nth peak position, and ts represents the radar frame period.

4. The heart rate variability monitoring method according to claim 1, characterized in that: The heart rate variability index includes the average IBI, the root mean square of consecutive IBI differences and / or the standard deviation of IBI; The calculating of the heart rate variability index based on the beat interval comprises: Based on the formula Calculate the average IBI; Based on the formula Calculate the RMS of consecutive IBI differences; Based on the formula Calculate the standard deviation of IBI; Where IBI(n) represents the beat interval of the nth peak position; L represents the total number of peaks, IBI_mean represents the average IBI, RMSSD represents the root mean square of the difference between consecutive IBIs, and SDRR represents the standard deviation of IBI.

5. The heart rate variability monitoring method according to claim 1, characterized in that: The step of obtaining a heartbeat signal detected by a radar on a human body includes: Acquire the echo signal obtained by radar detecting human body; The echo signal is band-pass filtered to extract the heartbeat signal.

6. A heart rate variability monitoring device, characterized in that: include: A heartbeat signal acquisition module is used to acquire the heartbeat signal detected by the radar on the human body; A normalization processing module, used for performing normalization processing on the heartbeat signal based on the amplitude of the heartbeat signal; An amplitude spectrum acquisition module is used to perform Fourier transform on the normalized heartbeat signal to obtain the amplitude spectrum of the normalized heartbeat signal, and set the amplitude of the frequency points in the amplitude spectrum that do not meet the preset amplitude condition to zero to obtain the amplitude spectrum with frequency interference removed; A heartbeat time domain signal acquisition module is used to perform an inverse Fourier transform on the amplitude spectrum after removing the frequency interference to obtain a reconstructed heartbeat time domain signal; A heart rate variability index calculation module, used to calculate the beat interval according to the reconstructed heartbeat time domain signal, and calculate the heart rate variability index based on the beat interval; The normalization processing module is used for: For each signal point in the heartbeat signal, calculate the amplitude mean of the signal point based on the amplitudes of the signal point and signal points within a preset range around the signal point, and divide the amplitude of the signal point by the amplitude mean corresponding to the signal point to obtain a normalized signal point; The normalization processing module is specifically used for: Based on the formula Calculate the amplitude mean of the signal point; Wherein, S_mean(i) represents the amplitude mean of the i-th signal point, S_heart(i) represents the amplitude of the i-th signal point, N represents the number of signal points of the heartbeat signal; K represents a preset value, and 0 <K<N。 7. A radar, characterized in that: The method comprises a processor and a memory, wherein the memory is used to store a computer program, and the processor is used to call and run the computer program stored in the memory to execute the method according to any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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