Sleep scene-oriented robust millimeter wave radar heart rate estimation methodTechnical Field
The invention belongs to the technical field of radar signal processing, and particularly relates to a sleep scene-oriented robust millimeter wave radar heart rate estimation method.
Background
Heart-derived diseases are one of the main chronic diseases faced by the old, and the heart rate of the old is continuously monitored, so that the heart-derived diseases are important ways for health management of the heart-derived chronic diseases of the old.
In the existing heart rate monitoring equipment, millimeter wave radar has gained more attention due to the advantages of large detection range, strong privacy, no contact and the like. The technical scheme includes that an intermediate frequency signal containing displacement information of a human chest is obtained by means of a millimeter wave radar, the intermediate frequency signal is preprocessed to obtain a chest wall displacement signal, the chest wall displacement signal is decomposed and extracted in a second harmonic frequency band, the extracted second harmonic signal is weighted, and a heart rate value is obtained through power spectrum estimation. The publication number CN112674738A proposes that an echo signal reflected by an obstacle is acquired when an electromagnetic wave signal emitted by a radar encounters the obstacle, a target echo signal is extracted from the echo signal, wherein the target echo signal is a signal reflected by the chest of a human body when the electromagnetic wave signal encounters the chest, a respiratory signal and a heartbeat signal of the human body are extracted from the target echo signal, the respiratory frequency of the human body is determined according to the respiratory signal, and the heartbeat frequency of the human body is determined according to the heartbeat signal. "
However, in the conventional method, after clutter suppression, a certain resolution unit is selected as a target position through a target detection algorithm, a heart rate spectrum is obtained through fourier transformation, and then the heart rate is obtained through extracting the maximum value of the heart rate spectrum. The method mainly has two problems, namely, fluctuation of body position is caused by human respiration in the heart rate measurement process, the strongest point position of radar echo is changed, only a single distance unit is extracted and possibly deviates from the chest position, so that heart rate signals are not existed in the extracted signals, and the heart rate signals are extremely weak due to non-ideal factors such as human body micro motion, environmental interference and posture change in the heart rate measurement process, the frequency spectrum of the extracted heart rate signals is poor in quality, and the heart rate value estimated by using a peak point method has larger error, so that the direct output can influence the evaluation of the health state of the old people. Therefore, there is still an unresolved problem with stable estimation of heart rate.
Disclosure of Invention
The invention aims to provide a sleep scene-oriented robust millimeter wave radar heart rate estimation method, which aims to solve the problems of inaccurate measurement and larger error in heart rate monitoring of the elderly in the prior art.
In order to solve the technical problems, the invention adopts the following technical scheme:
a robust millimeter wave radar heart rate estimation method facing sleep scenes comprises the following steps:
step S1, acquiring data of a detected object through a radar, wherein the data comprises M pulses, and each pulse comprises N sampling points;
Step S2, processing the pulse acquired by the radar to acquire a phase sequence;
Step S3, for the phase sequenceBand-pass filtering to obtain heart rate signal;
Step S4, for heart rate signalsTransforming to obtain heart rate spectrum SF;
step S5, evaluating the confidence coefficient of the heart rate spectrum SF to obtain a confidence coefficient SV;
Step S6, estimating the target heart rate based on the confidence SV, comprising:
Step S601, ifWhereinFor the confidence level high threshold, defining the frequency spectrum at the moment as high confidence level, estimating and outputting the heart rate at the moment through the position of the maximum peak point:
step S602, ifWhereinFor a high threshold of confidence level,Defining the frequency spectrum at the moment as middle-set confidence level for a confidence level low threshold, and estimating the heart rate at the moment by selecting K peaks;
step S603, ifWherein,And defining the frequency spectrum at the moment as low confidence degree for the confidence degree low threshold, wherein the heart rate output value at the moment directly adopts the output value at the last moment.
According to the above technical solution, in step S2, the processing of the pulse acquired by the radar to acquire the phase sequence specifically includes:
Step S201, performing distance dimension imaging on each pulse acquired by the radar to obtain a one-dimensional distance image of an observation scene;
Step S202, for eachExtracting the position of the maximum pointAnd in positionTaking the first r units and the last r units as centers to obtain signals;
Step S203, calculateFor M pulses, a phase sequence can be obtained;
Step S204, performing differential processing on the phase sequence to inhibit the influence of low-frequency motion, thereby obtaining a new phase sequence。
According to the above technical solution, in step S3, the phase sequence is repeatedBand-pass filtering to obtain heart rate signalThe method comprises the following steps:
Wherein,Filter coefficients that are band pass filters; Representing a convolution operation.
According to the above technical solution, in step S5, the confidence is defined as:
Wherein: Representing the maximum peak amplitude of the extracted signal,Representing the next largest peak amplitude of the extracted signal,Indicating the starting position in the heart rate spectrum,Indicating the end position in the heart rate spectrum SF.
According to the above technical solution, in step S601, the calculation and output are specifically:
Wherein: Representing the calculated heart rate, L representing the total number of samples of the spectrum,Representing the location of the maximum peak point; is the interval between adjacent pulses.
According to the above technical solution, in step S602, the estimation is performed by selecting the peak values, which specifically includes the following steps:
Step S6021, extracting K peak values and recording the position serial numbers;
Step S6022, calculating the frequencies corresponding to the K peaks:
Step S6023, selecting a value closest to the heart rate of the previous frame:
Wherein: representing the heart rate value selected at the current time,Representing the value of the corresponding frequency to be used,A heart rate output value representing a previous time;
Step S6024, calculating the heart rate output value at the current time:
Wherein: Is a filter coefficient.
According to the above technical solution, in step S603, the heart rate output value adopts the output value of the previous moment, specifically:
Wherein,Representing the heart rate output value at the last moment.
Compared with the prior art, the invention has the following beneficial effects:
According to the method, raw data are acquired through a radar, distance dimension imaging, target phase extraction, spectrum confidence judgment and heart rate estimation are carried out, and different heart rate estimation is adopted according to different signal spectrum qualities. By the method, the signal at the target true value position can be effectively acquired, and the influence of poor signal quality on an output result is avoided, so that a robust heart rate measurement result is acquired.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a typical one-dimensional range profile;
FIG. 3 is a representative target phase sequence;
FIG. 4 is a typical heart rate signal;
FIG. 5 is a typical heart rate spectrum;
Fig. 6 is a representative heart rate estimate obtained using the method of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
As shown in fig. 1, a sleep scene-oriented robust millimeter wave radar heart rate estimation method includes the following steps:
step S1, acquiring data of a detected object through a radar, wherein the data comprises M pulses, and each pulse comprises N sampling points;
Step S2, processing the pulse acquired by the radar to acquire a phase sequence;
Step S3, for the phase sequenceBand-pass filtering to obtain heart rate signal;
Step S4, carrying out Fourier transform with the length of the heart rate signal to obtain a heart rate spectrum SF;
step S5, evaluating the confidence coefficient of the heart rate spectrum to obtain a confidence coefficient SV;
Step S6, estimating the target heart rate based on the confidence SV, comprising:
Step S601, ifWhereinFor the confidence level high threshold, defining the frequency spectrum at the moment as high confidence level, estimating and outputting the heart rate at the moment through the position of the maximum peak point:
step S602, ifWhereinFor a high threshold of confidence level,Defining the frequency spectrum at the moment as middle-set confidence level for a confidence level low threshold, and estimating the heart rate at the moment by selecting K peaks;
step S603, if, wherein,And defining the frequency spectrum at the moment as low confidence degree for the confidence degree low threshold, wherein the heart rate output value at the moment directly adopts the output value at the last moment.
According to the method, raw data are acquired through a radar, distance dimension imaging, target phase extraction, spectrum confidence judgment and heart rate estimation are carried out, and different heart rate estimation is adopted according to different signal spectrum qualities. By the method, the signal at the target true value position can be effectively acquired, and the influence of poor signal quality on an output result is avoided, so that a robust heart rate measurement result is acquired.
Example two
The present embodiment provides a specific implementation manner:
a robust millimeter wave radar heart rate estimation method facing sleep scenes comprises the following steps:
step S1, acquiring data of a detected object by a radar, assuming that the data comprises M pulses, each pulse comprising N sampling points, wherein typical values are。
Step S2, performing distance dimension imaging on each pulse acquired by the radar to obtain a one-dimensional distance image of an observation sceneAs shown in fig. 2.
Step S3, for eachExtracting the position of the maximum pointAnd accumulate the surroundingsThe individual units obtain signalsWherein typical values are;
Step S4, calculatingFor M pulses, a target phase sequence can be obtainedAs shown in fig. 3;
step S5, performing differential processing on the phase sequence to inhibit the influence of low-frequency motion, thereby obtaining a new phase sequence;
Step S6, as shown in FIG. 4, for the phase sequenceBand-pass filtering to obtain heart rate signalWhereinIs a filter coefficient of a band-pass filter, by setting the order thereofFirst cut-off frequencyAnd a second cut-off frequencyObtaining the product. The heart rate of normal people is generally 50-100 times/min, soAndTypical values of (2) may be taken as 0.8Hz and 1.7Hz; Representing a convolution operation.
In step S7, as shown in fig. 5, a fourier transform with length L is performed on the heart rate signal, resulting in a heart rate spectrum SF with typical value of 1024.
Step S8, evaluating the confidence of the heart rate spectrum, wherein the confidence is defined as:
Wherein: Representing the maximum peak amplitude of the extracted signal,Representing the next largest peak amplitude of the extracted signal,Represents the starting position in the heart rate spectrum SF (typical value 5),The end position in the heart rate spectrum SF is indicated (typical value 60).
Step S9, as shown in fig. 6, based on the confidence SV, different strategies are adopted to estimate the target heart rate:
step S901, ifWhereinFor the confidence high threshold, defining the frequency spectrum at the moment as high confidence, and calculating and outputting the heart rate at the moment through the position of the maximum peak point:
Wherein: Representing the calculated heart rate, L representing the total number of samples of the spectrum,The position of the maximum peak point is indicated,Is the interval between adjacent pulses.
Step S902, ifWhereinFor a high threshold of confidence level,For the confidence low threshold, define the frequency spectrum at this time as mid-set confidence, and estimate the heart rate at this time by selecting K (typically 10) peaks, the specific procedure is as follows:
Step S902-a, extracting K peak values and recording the position serial numbers;
Step S902-b, calculating frequencies corresponding to K peaks:
step S902-c, selecting the value closest to the heart rate of the previous frame:
Wherein: representing the heart rate value selected at the current time,Representing the value of the corresponding frequency to be used,Representing the heart rate output value at the last moment.
Step S902-d, calculating the heart rate output value at the current moment:
Wherein: For the filter coefficients, a typical value is taken as 0.9.
Step S903, if, wherein,For the confidence coefficient low threshold, defining the frequency spectrum at the moment as low confidence coefficient, and directly adopting the output value of the last moment as the heart rate output value at the moment:
Wherein,Representing the heart rate output value at the last moment.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, 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.
It should be noted that the above-mentioned embodiments are merely preferred embodiments of the present invention, and the present invention is not limited thereto, but may be modified or substituted for some of the technical features thereof by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.