阅读说明：本技术 一种基于毫米波雷达的hrv信号提取方法及设备 (Millimeter wave radar-based HRV signal extraction method and equipment ) 是由 王泽涛 丁玉国 董明 吴昊 饶玮 于 2021-09-14 设计创作，主要内容包括：本申请公开了一种基于毫米波雷达的HRV信号提取方法及设备,用以解决现有的HRV信号提取方法无法对使用者进行非接触长期监测的技术问题。方法包括：采集人体在睡眠状态下的雷达回波数据,并对所述雷达回波数据进行处理,得到所述人体的生命体征信号；其中,所述雷达回波数据是通过毫米波雷达作用于所述人体得到的；基于第一预设滤波器对所述生命体征信号进行滤波,得到第一滤波信号,以及基于第二预设滤波器对所述生命体征信号进行滤波,得到第二滤波信号；通过第一预设算法对所述第一滤波信号进行心跳周期划分,得到心跳周期信号；通过第二预设算法,利用所述第二滤波信号对所述心跳周期信号进行筛选得到HRV信号。(The application discloses a millimeter wave radar-based HRV signal extraction method and equipment, which are used for solving the technical problem that the conventional HRV signal extraction method cannot carry out non-contact long-term monitoring on a user. The method comprises the following steps: collecting radar echo data of a human body in a sleep state, and processing the radar echo data to obtain vital sign signals of the human body; the radar echo data are obtained by acting a millimeter wave radar on the human body; filtering the vital sign signal based on a first preset filter to obtain a first filtered signal, and filtering the vital sign signal based on a second preset filter to obtain a second filtered signal; carrying out heartbeat cycle division on the first filtering signal through a first preset algorithm to obtain a heartbeat cycle signal; and screening the heartbeat periodic signal by using the second filtering signal through a second preset algorithm to obtain an HRV signal.)

1. A HRV signal extraction method based on millimeter wave radar is characterized by comprising the following steps:

collecting radar echo data of a human body in a sleep state, and processing the radar echo data to obtain vital sign signals of the human body; the radar echo data are obtained by acting a millimeter wave radar on the human body;

filtering the vital sign signal based on a first preset filter to obtain a first filtered signal, and filtering the vital sign signal based on a second preset filter to obtain a second filtered signal;

carrying out heartbeat cycle division on the first filtering signal through a first preset algorithm to obtain a heartbeat cycle signal;

and screening the heartbeat periodic signals by using the second filtering signal through a second preset algorithm to obtain HRV signals.

2. The millimeter wave radar-based HRV signal extraction method according to claim 1, wherein the dividing of the heartbeat cycle of the first filtered signal by the first preset algorithm specifically comprises:

taking the starting time of the first filtering signal as the starting time of the signal to be divided;

intercepting the signal to be divided from the first filtering signal based on the starting time and a preset signal processing length;

performing autocorrelation processing on the signal to be divided to obtain an autocorrelation signal;

determining the maximum value of the amplitude of the autocorrelation signal in a preset minimum heartbeat cycle and a preset time period corresponding to the maximum heartbeat cycle;

and determining the time point corresponding to the maximum amplitude value as the heartbeat cycle corresponding to the signal to be divided.

3. The millimeter wave radar-based HRV signal extraction method according to claim 2, wherein after determining the heartbeat cycle corresponding to the signal to be divided, the method further comprises:

taking the termination time of the signal to be divided as the starting time of the signal to be divided of the next heartbeat cycle; the end time of the signal to be divided is a time point corresponding to the sum of the start time of the signal to be divided and the heartbeat cycle corresponding to the signal to be divided;

repeatedly executing the process until the signal to be divided which meets the preset signal processing length cannot be intercepted, and obtaining a plurality of heartbeat cycles corresponding to the first filtering signal;

and marking the plurality of heartbeat cycles on the first filtering signal to obtain the heartbeat cycle signal.

4. The millimeter wave radar-based HRV signal extraction method according to claim 2, wherein the preset signal processing length is 2 times of the maximum heartbeat period.

5. The millimeter wave radar-based HRV signal extraction method according to claim 1, wherein the filtering the heartbeat cycle signal with the second filtered signal through a second preset algorithm specifically comprises:

starting time t of signal to be divided used in k-th heartbeat cycle division_k-1And end time t_kDetermining the maximum value a of the amplitude of the second filtered signal in a corresponding time period_kWith a minimum value of amplitude b_k；

And, ticking at the k +1 heartbeat cycleStarting time t of divided signals to be divided_kAnd end time t_k+1Determining the maximum value a of the amplitude of the second filtered signal in a corresponding time period_k+1With a minimum value of amplitude b_k+1；

And performing validity detection on the kth heartbeat cycle division through the following formula:

|a_k-a_k+1|/(a_k+a_k+1-b_k-b_k+1)

|b_k-b_k+1|/(a_k+a_k+1-b_k-b_k+1)。

6. the millimeter wave radar-based HRV signal extraction method according to claim 5, wherein the effectiveness detection of the kth heartbeat cycle division specifically comprises:

at | a_k-a_k+1|/(a_k+a_k+1-b_k-b_k+1) Is less than a first predetermined threshold, and b_k-b_k+1|/(a_k+a_k+1-b_k-b_k+1) Determining that the kth heartbeat cycle is effectively divided and reserving a heartbeat cycle obtained by dividing the kth heartbeat cycle under the condition that the value of (1) is smaller than a second preset threshold value;

and, at | a_k-a_k+1|/(a_k+a_k+1-b_k-b_k+1) Is greater than or equal to a first preset threshold, and/or | b_k-b_k+1|/(a_k+a_k+1-b_k-b_k+1) And under the condition that the value of the first threshold value is greater than or equal to a second preset threshold value, determining that the kth heartbeat cycle division is invalid, and rejecting the heartbeat cycle obtained by the kth heartbeat cycle division.

7. The millimeter wave radar-based HRV signal extraction method according to claim 1, wherein the first preset filter and the second preset filter both adopt FIR filters;

and the order of the first preset filter is the same as that of the second filter, and the passband range of the first filter comprises the passband range of the second filter.

8. The millimeter wave radar-based HRV signal extraction method according to claim 1, wherein the processing of the radar echo data to obtain the vital sign signal of the human body comprises:

carrying out body motion detection on the radar echo data to divide the radar echo data into body motion segment data and stationary segment data;

determining a distance gate corresponding to the human thorax in the stationary section data; the distance gate is used for indicating distance information between the human thorax and the millimeter wave radar;

extracting an original phase signal in the plateau data based on the range gate; wherein the raw phase signal is used to indicate a correspondence between time and the range gate phase angle;

and carrying out unwrapping processing on the original phase signals to obtain the vital sign signals of the human body.

9. The millimeter wave radar-based HRV signal extraction method according to claim 8, wherein the millimeter wave radar is mounted on a wall right above the center of the bed head of the bed where the human body is located, and the distance between the millimeter wave radar and the bed surface of the bed is 1 m;

and the radar wave beam emitted by the millimeter wave radar points to the position of the chest cavity of the human body.

10. An HRV signal extraction apparatus based on a millimeter wave radar, the apparatus comprising:

at least one processor; and the number of the first and second groups,

a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,

the memory stores instructions executable by the at least one processor to cause the at least one processor to perform a millimeter wave radar-based HRV signal extraction method according to any one of claims 1 to 9.

Technical Field

The application relates to the technical field of radar signal processing and biomedical engineering processing, in particular to a millimeter wave radar-based HRV signal extraction method and equipment.

Background

With the continuous improvement of medical technology level, modern people pay more and more attention to their health. The Heart is one of the most important organs of the human body, the Heart Rate of a normal person is not absolutely regular, the Heart Rate Variability (HRV) signal describes the change of the Heart Rate rhythm speed along with the time, the related information of the nervous system for controlling the Heart rhythm can be obtained by analyzing the HRV signal, and the Heart Rate Variability (HRV) has important significance for early diagnosis, monitoring in diseases, prognosis evaluation and the like of cardiovascular diseases.

The traditional HRV signal acquisition mode is mainly contact type, and electrocardiosignals are measured from the chest of a user or a patient through a lead electrode, but the traditional HRV signal acquisition mode is very easy to cause discomfort to the user or the patient and is inconvenient for long-term monitoring.

Disclosure of Invention

The embodiment of the application provides an HRV signal extraction method and equipment based on a millimeter wave radar, and aims to solve the technical problem that the existing HRV signal acquisition method cannot realize long-term monitoring on a user or a patient in a non-contact mode.

In one aspect, an embodiment of the present application provides a method for extracting an HRV signal based on a millimeter wave radar, where the method includes: collecting radar echo data of a human body in a sleep state, and processing the radar echo data to obtain vital sign signals of the human body; the radar echo data are obtained by acting a millimeter wave radar on the human body; filtering the vital sign signal based on a first preset filter to obtain a first filtered signal, and filtering the vital sign signal based on a second preset filter to obtain a second filtered signal; carrying out heartbeat cycle division on the first filtering signal through a first preset algorithm to obtain a heartbeat cycle signal; and screening the heartbeat periodic signals by using the second filtering signal through a second preset algorithm to obtain HRV signals.

In a possible implementation manner of the embodiment of the present application, the dividing the heartbeat cycle of the first filtered signal by using a first preset algorithm specifically includes: taking the starting time of the first filtering signal as the starting time of the signal to be divided; intercepting the signal to be divided from the first filtering signal based on the starting time and a preset signal processing length; performing autocorrelation processing on the signal to be divided to obtain an autocorrelation signal; determining the maximum value of the amplitude of the autocorrelation signal in a preset minimum heartbeat cycle and a preset time period corresponding to the maximum heartbeat cycle; and determining the time point corresponding to the maximum amplitude value as the heartbeat cycle corresponding to the signal to be divided.

In a possible implementation manner of the embodiment of the present application, after determining a heartbeat cycle corresponding to the signal to be divided, the method further includes: taking the termination time of the signal to be divided as the starting time of the signal to be divided of the next heartbeat cycle; the end time of the signal to be divided is a time point corresponding to the sum of the start time of the signal to be divided and the heartbeat cycle corresponding to the signal to be divided; repeatedly executing the process until the signal to be divided which meets the preset signal processing length cannot be intercepted, and obtaining a plurality of heartbeat cycles corresponding to the first filtering signal; and marking the plurality of heartbeat cycles on the first filtering signal to obtain the heartbeat cycle signal.

In a possible implementation manner of the embodiment of the present application, the preset signal processing length is 2 times of the maximum heartbeat period.

In a possible implementation manner of the embodiment of the present application, the screening the heartbeat periodic signal by using the second filtering signal through a second preset algorithm specifically includes: starting time t of signal to be divided used in k-th heartbeat cycle division_k-1And end time t_kDetermining the maximum value a of the amplitude of the second filtered signal in a corresponding time period_kWith a minimum value of amplitude b_k(ii) a And the starting time t of the signal to be divided used in the k +1 th heartbeat cycle division_kAnd end time t_k+1Determining the maximum value a of the amplitude of the second filtered signal in a corresponding time period_k+1With a minimum value of amplitude b_k+1(ii) a And performing validity detection on the kth heartbeat cycle division through the following formula: | a_k-a_k+1|/(a_k+a_k+1-b_k-b_k+1)

|b_k-b_k+1|/(a_k+a_k+1-b_k-b_k+1)。

In a possible implementation manner of the embodiment of the present application, performing validity detection on the kth heartbeat cycle partition specifically includes: at | a_k-a_k+1|/(a_k+a_k+1-b_k-b_k+1) Is less than a first predetermined threshold, and b_k-b_k+1|/(a_k+a_k+1-b_k-b_k+1) Determining that the kth heartbeat cycle is effectively divided and reserving a heartbeat cycle obtained by dividing the kth heartbeat cycle under the condition that the value of (1) is smaller than a second preset threshold value; and, at | a_k-a_k+1|/(a_k+a_k+1-b_k-b_k+1) Is greater than or equal to a first preset threshold, and/or | b_k-b_k+1|/(a_k+a_k+1-b_k-b_k+1) And under the condition that the value of the first threshold value is greater than or equal to a second preset threshold value, determining that the kth heartbeat cycle division is invalid, and rejecting the heartbeat cycle obtained by the kth heartbeat cycle division.

In a possible implementation manner of the embodiment of the present application, the first preset filter and the second preset filter both employ FIR filters; and the order of the first preset filter is the same as that of the second filter, and the passband range of the first filter comprises the passband range of the second filter.

In a possible implementation manner of the embodiment of the present application, the processing the radar echo data to obtain the vital sign signal of the human body specifically includes: carrying out body motion detection on the radar echo data to divide the radar echo data into body motion segment data and stationary segment data; determining a distance gate corresponding to the human thorax in the stationary section data; the distance gate is used for indicating distance information between the human thorax and the millimeter wave radar; extracting an original phase signal in the plateau data based on the range gate; wherein the raw phase signal is used to indicate a correspondence between time and the range gate phase angle; and carrying out unwrapping processing on the original phase signals to obtain the vital sign signals of the human body.

In a possible implementation manner of the embodiment of the application, the millimeter wave radar is mounted on a wall right above the center of the bed head of the bed where the human body is located, and the distance between the millimeter wave radar and the bed surface of the bed is 1 meter; and the radar wave beam emitted by the millimeter wave radar points to the position of the chest cavity of the human body.

On the other hand, the embodiment of the present application further provides a millimeter wave radar-based HRV signal extraction device, the device includes: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute a millimeter wave radar-based HRV signal extraction method according to any one of the above embodiments.

The HRV signal extraction method and device based on the millimeter wave radar have the following advantages:

the radar beam transmitted by the millimeter wave radar acts on the human body to collect radar echo signals, and HRV signals are extracted based on the radar echo signals, so that the vital sign data of the human body can be detected under the condition of not contacting the human body, discomfort of a user or a patient is avoided, and the millimeter wave radar is very suitable for monitoring the user or the patient continuously for a long time. In addition, the vital sign signals are filtered through the two filters, the heartbeat cycle of the vital sign signals is divided and screened based on the filtered signals obtained through filtering, and then the final HRV signals are extracted, so that the adverse effect of the human body respiration signals on the extraction of the HRV signals is well inhibited, and the effectiveness and the accuracy of the extracted HRV signals are ensured.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:

fig. 1 is a flowchart of a method for extracting an HRV signal based on a millimeter wave radar according to an embodiment of the present disclosure;

fig. 2 is a schematic view of a mounting position of a millimeter wave radar according to an embodiment of the present disclosure;

fig. 3 is a schematic waveform diagram of a vital sign signal according to an embodiment of the present application;

fig. 4 is a schematic diagram of a heartbeat cycle division result according to an embodiment of the present application;

fig. 5 is a schematic view of an internal structure of a millimeter-wave radar-based HRV signal extraction device according to an embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

The embodiment of the application provides a millimeter wave radar-based HRV signal extraction method and equipment, wherein radar echo data are processed to obtain vital sign signals of a tested person, and then the vital sign signals are filtered through two filters with different passband ranges to obtain filtered signals; the filtering signals corresponding to the filters based on the wide pass band range are subjected to heartbeat period division, and then the filtering signals corresponding to the filters based on the narrow pass band range are subjected to heartbeat period screening, so that the HRV signals finally extracted are obtained, the non-contact HRV signal extraction process is realized, the personnel to be detected can be continuously monitored for a long time, and the effectiveness and the accuracy of the extracted HRV signals can be ensured.

The technical solutions proposed in the embodiments of the present application are described in detail below with reference to the accompanying drawings.

Fig. 1 is a flowchart of an HRV signal extraction method based on a millimeter wave radar according to an embodiment of the present application. It should be noted that, in the HRV signal extraction method in the embodiment of the present application, an execution subject thereof may be a computer device or a server having a data processing function. As shown in fig. 1, the HRV signal extraction method provided in the embodiment of the present application mainly includes the following implementation processes:

step 101, collecting radar echo data of a human body in a sleep state, and processing the radar echo data to obtain vital sign signals of the human body.

The HRV signal extraction method provided in the embodiment of the application firstly acts on the human body of a person to be detected through a millimeter wave radar and collects radar echo data of the human body. It should be noted that, when radar echo data is acquired, the person to be tested is preferably in a sleep state, because the breathing signal of the human body in the sleep state is relatively stable, and the heartbeat is relatively stable, the influence on the extraction of the HRV signal is relatively weak.

Fig. 2 is a schematic view of an installation position of a millimeter wave radar provided in an embodiment of the present application. As shown in fig. 2, the millimeter wave radar is installed on a wall, specifically, right above the bed head of the bed where the person to be measured is located, and the radar beam of the millimeter wave radar is directed to the chest position of the person to be measured. In one or more embodiments of this application, set up the height of millimeter wave radar apart from the bed surface to 1 meter, can guarantee to have more radar beam of millimeter wave radar transmission to act on surveyed personnel's thorax position this moment.

Further, the millimeter wave radar in the embodiment of the present application transmits a frequency modulated continuous wave FMCW signal. In the embodiment of the present application, the FMCW signal in one period is referred to as a Chirp signal, and the signal modulation mode is a sawtooth waveChirp period of T_ChirpSecond, N Chirps continuously transmitted form a frame with a frame period of T_frameAnd second. That is, in the transmission signal of the millimeter wave radar or the radar echo data in the embodiment of the present application, a plurality of frames are included, each frame includes N Chirp, and one Chirp is an FMCW signal in one period.

In the installation mode and the signal transmission mode, the received echo signals and the transmission signals of the millimeter wave radar are subjected to frequency mixing processing to obtain difference frequency signals, and then the difference frequency signals are subjected to high-pass filtering, low-noise amplification and ADC (analog-to-digital converter) sampling processing to finally obtain digitized radar echo data. It should be noted that the high-pass filtering, the low-noise amplification, and the ADC sampling processing may be implemented by existing equipment or an existing algorithm, and are not described herein again in this embodiment of the application.

After radar echo data of the tested person in a sleep state are collected, the radar echo data are continuously processed to obtain vital sign signals of the tested person. Specifically, firstly, body motion detection is carried out on collected radar echo data so as to divide the radar echo data into body motion segment data and stationary segment data; then, determining a distance gate corresponding to the chest cavity of the tested person in the stationary section data, and extracting an original phase signal from the stationary section data based on the distance gate; and finally, performing unwrapping processing on the extracted original phase signal, wherein the phase signal obtained after unwrapping processing is the vital sign signal, and the vital sign signal contains information related to the heart activity of the tested person. The range gate indicates the distance information between the millimeter wave radar and the chest cavity of the person to be tested, and the raw phase signal indicates the corresponding relationship between time and the range gate phase angle.

In one or more embodiments of the present application, dividing the collected radar echo data into body motion segment data and stationary segment data through body motion detection may be implemented as follows: firstly, with Chirp as a processing unit, performing DC removal processing and FFT (fast Fourier transform) conversion processing on acquired radar echo data to obtain a distance dimension complex signal. In the distance-dimensional complex signal, the horizontal axis indicates distance information, and the vertical axis indicates the complex signal after FFT. Secondly, performing slow time de-direct current on the N distance dimensional complex signals in each frame, namely performing de-direct current processing on the N complex signals corresponding to each distance gate by taking the distance gate as a processing unit; then, obtaining a power value in a current frame time monitoring distance range by using the distance dimension complex signal after the direct current removal; the concrete mode is as follows: and intercepting the part in the monitoring distance range of the millimeter wave radar from the N distance dimension complex signals (N distance dimension complex signals in one frame) subjected to direct current removal, and performing power accumulation, wherein the accumulated value is used as a power value in the monitoring distance range at the current frame moment. Thirdly, the body movement detection is carried out by adopting a sliding window detection mode, and the specific mode is as follows: and respectively calculating the average power of the left half side and the average power of the right half side in the current sliding window, considering that body movement exists in the current sliding window when the average powers of the two sides have large difference, and considering that the tested person in the current sliding window is in a stable state if the average powers of the two sides are not in the large difference. For example, the time of the sliding window is set to 10s, then the sliding window is moved on the power signal (the horizontal axis is the frame time, and the vertical axis is the power value in the monitoring distance range corresponding to the frame time), and the average power corresponding to the left 5s of the sliding window and the average power corresponding to the right 5s of the sliding window are calculated. And finally, dividing the radar echo data into stationary segment data and body motion segment data based on the body motion detection result.

Further, extracting an original phase signal containing vital sign information from the stationary phase data, which can be implemented by using a distance dimension complex signal corresponding to the first Chirp of each frame of the stationary phase data, wherein the specific implementation manner is as follows: firstly, removing static clutter in a distance dimension complex signal along the time dimension of each frame; then, the power strongest point in the monitoring distance range of the millimeter wave radar is searched along the distance dimension of each frame, and a range gate (indicating the distance information between the millimeter wave radar and the chest cavity of the tested person) corresponding to the power strongest point is used as an alternative range gate for extracting the vital sign signals. In order to ensure the reliability of the extracted range gate of the selected vital sign signal, the embodiment of the present application uses median filtering to smooth the candidate range gates within a time window, uses the smoothed result as the extracted range gate of the final vital sign signal, and updates the extracted range gate information of the vital sign signal at fixed time intervals. And finally, extracting a range gate phase angle in the range dimension complex signal corresponding to the first Chirp of each frame, and further obtaining an original phase signal containing vital sign information.

Furthermore, in the embodiment of the present application, the unwrapping processing performed on the original phase signal may be implemented by an existing device or an existing algorithm, and details of the embodiment of the present application are not described herein.

Thus, the vital sign signals of the tested person are obtained. Fig. 3 is a schematic waveform diagram of a vital sign signal according to an embodiment of the present application. As shown in fig. 3, the horizontal axis of the waveform of the vital sign signal in the embodiment of the present application represents time, and the vertical axis represents phase angle.

102, filtering the vital sign signal based on a first preset filter to obtain a first filtered signal, and filtering the vital sign signal based on a second preset filter to obtain a second filtered signal.

Because the displacement of the thoracic cavity caused by the respiratory motion of the human body is far larger than that caused by the heartbeat motion, the energy of the respiratory signal in the extracted vital sign signals is far larger than that of the heartbeat signal. Therefore, in order to suppress the adverse effect of the respiration signal on the HRV signal extraction, the vital sign signal needs to be filtered in the embodiment of the present application. Specifically, in the embodiment of the present application, two FIR filters are respectively used to perform filtering processing on the vital sign signals, so as to obtain a first filtered signal and a second filtered signal. The first preset filter obtains a first filtering signal, and the second preset filter obtains a second filtering signal.

In one or more embodiments of the present application, the first predetermined filter and the second predetermined filter have the same order and different pass band ranges. And the passband range of the first preset filter comprises the passband range of the second preset filter. For example, the pass band range of the first preset filter is set to 0.7Hz to 10.0Hz, and the pass band range of the second preset filter is set to 0.7Hz to 2.0 Hz.

103, carrying out heartbeat cycle division on the first filtering signal through a first preset algorithm to obtain a heartbeat cycle signal.

After the first filtering signal is obtained through the steps, heartbeat cycle division is carried out on the first filtering signal through a first preset algorithm, and a heartbeat cycle signal is obtained. In one or more embodiments of the present application, the first preset algorithm may adopt an autocorrelation method, that is, the heartbeat cycle division process of the first filtered signal is implemented by using the autocorrelation method.

Specifically, first, a minimum heart cycle T is set_minMaximum heart cycle T_maxAnd the signal processing length T of the autocorrelation_cor. In the embodiment of the present application, the set minimum heartbeat period is 0.45 seconds, the set maximum heartbeat period is 2 seconds, and the set maximum heartbeat period, which is 2 times the autocorrelation signal processing length, is 4 seconds. Then, the starting time of the first filtering signal is used as the starting time of the signal to be divided, and the signal to be divided is intercepted from the first filtering signal based on the starting time and the set autocorrelation signal processing length. For example, the starting time of the first filtered signal is 0s, and the length of the intercepted band division signal is the first filtered signal within 0-4 s. Secondly, performing autocorrelation processing on the signal to be divided to obtain an autocorrelation signal; determining the maximum value of the amplitude value of the autocorrelation signal through the set minimum heartbeat period and the set maximum heartbeat period; and finally, determining the time point corresponding to the maximum amplitude value as the heartbeat cycle corresponding to the signal to be divided.

Further, after the signal to be divided is divided, taking the sum of the determined heartbeat period and the starting time as the termination time of the signal to be divided; and then, taking the termination time as the starting time of the signal to be divided used for next heartbeat cycle division, repeatedly executing the processes of autocorrelation and the like until the signal to be divided which meets the preset signal processing length cannot be intercepted, and finishing the heartbeat cycle division process of the first filtering signal. In the above process, a plurality of heartbeat cycles are obtained, and the heartbeat cycles are marked on the first filtering signal to obtain a heartbeat cycle signal.

For example, assume that the start time of the kth heart cycle division is t_k-1Intercepting the first filtered signal S₁(t) in t_k-1To t_k-1+T_corThe signals of the time interval are subjected to autocorrelation to obtain autocorrelation signals S_cor(v) Wherein v is not less than 0 and not more than T_cor. Then, for the autocorrelation signal S_cor(v) Middle T_minTo T_maxThe maximum value of the amplitude value is obtained from the signals of the time period, and the time point corresponding to the maximum value of the amplitude value is taken as the heartbeat cycle T estimated this time_k. Further, the end time of the kth heartbeat cycle division is determined as t_k＝t_k-1+T_kThe starting time of the k +1 th heartbeat cycle division is t_kRepeatedly executing the above process to obtain a heartbeat-successive period division sequence X ═ t₀，...t_k，...t_K]And a beat-to-beat periodic signal Y ═ T₁，...T_k，...T_K]Wherein, t₀And K is the total dividing times of the heartbeat cycle.

Fig. 4 is a schematic diagram of a heartbeat cycle division result according to an embodiment of the present application. As shown in fig. 4, the horizontal axis of the heart cycle signal indicates time, and the vertical axis indicates phase angle. And in fig. 4, a first filtered signal (obtained by a first preset filter with a passband ranging from 0.7Hz to 10.0 Hz) indicated by a dotted line, a second filtered signal (obtained by a second preset filter with a passband ranging from 0.7Hz to 2.0 Hz) indicated by a solid line, and asterisks indicate the result of dividing the heartbeat cycle. As can be seen from fig. 4, the heartbeat cycle division result is obtained by marking the heartbeat cycle corresponding to each signal to be divided on the first filtered signal in the form of an asterisk, that is, the heartbeat cycle signal.

And 104, screening the heartbeat periodic signal by using the second filtering signal through a second preset algorithm to obtain an HRV signal.

In order to ensure the effectiveness of the extracted HRV signal, in the embodiment of the present application, the heartbeat cycle division is further screened by using the second filtering signal, so as to obtain a final HRV signal.

In particular, for the kth heart cycle division, the second filtered signal S is filtered₂(t) in t_k-1To t_kAmplitude maximum a is found for signals in time segments_kWith a minimum value of amplitude b_k(ii) a And, for the (k + 1) th beat cycle division, applying the second filtered signal S₂(t) in t_kTo t_k+1Amplitude maximum a is found for signals in time segments_k+1With a minimum value of amplitude b_k+1. Then, using the above results, pass | a_k-a_k+1|/(a_k+a_k+1-b_k-b_k+1) And | b_k-b_k+1|/(a_k+a_k+1-b_k-b_k+1) Detecting the effectiveness of the k-th heartbeat cycle division; specifically, at | a_k-a_k+1|/(a_k+a_k+1-b_k-b_k+1) Is less than a first predetermined threshold, and b_k-b_k+1|/(a_k+a_k+1-b_k-b_k+1) And under the condition that the value of (1) is smaller than a second preset threshold value, the kth heartbeat cycle division is considered to be effective, and the heartbeat cycle obtained by the kth heartbeat cycle division is reserved at the moment. Otherwise, the partition of the kth heartbeat cycle is considered to be invalid, and the heartbeat cycle obtained by the partition of the kth heartbeat cycle is eliminated.

Further, the above process is repeatedly executed, all heartbeat cycle partitions are screened, heartbeat cycles corresponding to all effective heartbeat cycle partitions are recorded, and a screened heartbeat cycle signal Z ═ R is obtained₁，...，R_m，...，R_M]Wherein R is_mThe value of the mth screened effective heartbeat cycle is shown, M is the number of the screened effective heartbeat cycles, and Z is the sleep heart rate variability signal extracted by the embodiment of the application, namely the HRV signal.

The foregoing is an embodiment of the method in the embodiment of the present application, and based on the same inventive concept, the embodiment of the present application further provides an HRV signal extraction device based on a millimeter wave radar, and an internal structure of the HRV signal extraction device is shown in fig. 5.

Fig. 5 is a schematic view of an internal structure of a millimeter-wave radar-based HRV signal extraction device according to an embodiment of the present application. As shown in fig. 5, the apparatus includes:

at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform:

collecting radar echo data of a human body in a sleep state, and processing the radar echo data to obtain vital sign signals of the human body;

filtering the vital sign signal based on a first preset filter to obtain a first filtered signal, and filtering the vital sign signal based on a second preset filter to obtain a second filtered signal;

carrying out heartbeat cycle division on the first filtering signal through a first preset algorithm to obtain a heartbeat cycle signal;

and screening the heart skipping period signal by using a second filtering signal through a second preset algorithm to obtain an HRV signal.

The embodiments in the present application are described in a progressive manner, and the same and similar parts among the embodiments can be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the apparatus embodiment, since it is substantially similar to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiment.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.