Heartbeat frequency extraction method, detection device and storage medium

Abstract

The present invention provides a heartbeat frequency extraction method, detection equipment and storage medium, the method comprising: pre-processing the echo signal received after the radar transmits the detection signal to obtain a digital echo signal; performing fast Fourier transform on each frame of the digital echo signal to obtain a one-dimensional distance image corresponding to each frame of the digital echo signal; obtaining the value of each frame of the one-dimensional distance image at the target distance point in the one-dimensional distance image of the continuous preset number of frames to obtain a one-dimensional array, the target distance point is used to represent the distance point corresponding to the target detection object; judging whether the target detection object has body movement according to the one-dimensional array; if the target detection object does not have body movement, determining the heartbeat frequency of the target detection object according to the one-dimensional array. The present invention can improve the detection accuracy of the heartbeat frequency.

Description

Technical Field

[0001] The present invention relates to the technical field of health monitoring, and in particular to a heart rate extraction method, a detection device and a storage medium. Background Art

[0002] As society pays more attention to the elderly care industry, the demand for smart elderly care products is also increasing. A typical demand is non-contact vital signs monitoring equipment. This type of equipment 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.

[0003] One type of non-contact vital signs monitoring equipment is millimeter wave radar. It transmits and receives millimeter wave signals and processes them to obtain the human body's breathing and heart rate. For radar, the breathing rate is relatively easy to extract because the chest cavity rises and falls with a large amplitude when the human body breathes. However, the heartbeat is too small and is easily disturbed by larger movements, resulting in low accuracy in extracting the heartbeat rate.

[0004] How to achieve accurate extraction of heart rate is a technical problem that needs to be solved urgently in existing technologies. Summary of the invention

[0005] In view of this, the present invention provides a heart rate extraction method, a detection device and a storage medium, which can solve the problem of low accuracy in heart rate extraction.

[0006] In a first aspect, an embodiment of the present invention provides a heart rate extraction method, comprising:

[0007] Preprocessing the echo signal received after the radar transmits the detection signal to obtain a digital echo signal;

[0008] Perform fast Fourier transform on each frame of digital echo signal to obtain a one-dimensional range image corresponding to each frame of digital echo signal;

[0009] Obtaining the value of each one-dimensional range image at the target range point in a continuous preset number of one-dimensional range images to obtain a one-dimensional array, wherein the target range point is used to represent the range point corresponding to the target detection object;

[0010] Determining whether the target detection object has body movement according to the one-dimensional array;

[0011] If the target detection object does not have body movement, the heartbeat frequency of the target detection object is determined according to the one-dimensional array.

[0012] In a possible implementation, judging, according to the one-dimensional array, whether the target detection object has body motion includes:

[0013] Acquiring a body motion energy value of the target detection object according to the one-dimensional array;

[0014] According to the body motion energy value of the target detection object, it is determined whether the target detection object has body motion.

[0015] In a possible implementation manner, acquiring the body motion energy value of the target detection object according to the one-dimensional array includes:

[0016] Performing bandpass filtering on the one-dimensional array through a first bandpass filter to obtain a first filtering result, wherein the passband of the first bandpass filter is from a first frequency to a second frequency, the first frequency is a minimum value of the motion frequency when the target detection object performs body movement, and the second frequency is a maximum value of the motion frequency when the target detection object performs body movement;

[0017] A modulus operation is performed on each data in the first filtering result, and the modulus of each data is summed to obtain the body motion energy value of the target detection body.

[0018] In a possible implementation, if the target detection object does not have body movement, determining the heart rate of the target detection object according to the one-dimensional array includes:

[0019] Filtering the one-dimensional array and performing fast Fourier transform on the filtering result to obtain a harmonic spectrum of the heartbeat frequency of the target detection object, wherein the harmonic spectrum includes a first harmonic spectrum and multiple harmonic spectrums of the target detection object;

[0020] Obtaining a target spectrum according to the harmonic spectrum of the heartbeat frequency of the target detection object;

[0021] The heartbeat frequency of the target detection object is determined according to the target frequency spectrum.

[0022] In a possible implementation, obtaining a target spectrum according to the harmonic spectrum of the heartbeat frequency of the target detection object includes:

[0023] Calculating the confidence level of the maximum value of the multiple harmonic spectrum amplitude;

[0024] If the confidence level of the maximum value of the amplitude of the multiple harmonic spectrum is greater than or equal to a preset confidence level, determining a target spectrum according to the first harmonic spectrum and the multiple harmonic spectrum;

[0025] If the confidence level of the maximum amplitude value of the multiple harmonic spectrum is less than a preset confidence level, the target spectrum is determined according to the first harmonic spectrum.

[0026] In a possible implementation, the process of acquiring the first harmonic spectrum includes:

[0027] Performing bandpass filtering on the one-dimensional array through a second bandpass filter to obtain a second filtering result, wherein the passband of the second bandpass filter is from a third frequency to a fourth frequency, the third frequency is a preset minimum value of the heartbeat frequency of the target detection object, and the fourth frequency is a preset maximum value of the heartbeat frequency of the target detection object;

[0028] Performing a fast Fourier transform on the second filtering result to obtain a first harmonic spectrum of the heartbeat frequency of the target detection object;

[0029] The multiple harmonic spectrum is a P-order harmonic spectrum, and the acquisition process of the multiple harmonic spectrum includes:

[0030] Performing bandpass filtering on the one-dimensional array through a third bandpass filter to obtain a third filtering result, wherein the passband of the third bandpass filter is from a fifth frequency to a sixth frequency, the fifth frequency is P times the third frequency, the sixth frequency is P times the fourth frequency, and P is a positive integer greater than or equal to 2;

[0031] The third filtering result is subjected to a fast Fourier transform to obtain a P-th harmonic spectrum of the heartbeat frequency of the target detection object.

[0032] In a possible implementation manner, calculating the confidence level of the maximum value of the multiple harmonic spectrum amplitude includes:

[0033] Determine a starting index number of the P-th harmonic spectrum according to the fifth frequency, and determine an ending index number of the P-th harmonic spectrum according to the sixth frequency;

[0034] Determine the effective frequency range of the P-order harmonic spectrum according to the starting index number and the ending index number of the P-order harmonic spectrum;

[0035] The index number corresponding to the position of the maximum amplitude in the effective frequency range of the P-th harmonic spectrum is used as the center index number;

[0036] Using a plurality of consecutive index numbers centered on the central index number as target index numbers, wherein the number of the target index numbers is less than the number of index numbers in the effective frequency range of the P-th harmonic spectrum;

[0037] Performing a modulo operation on the data corresponding to the target index number, and summing the obtained moduli to obtain a first value;

[0038] Performing a modulo operation on the data corresponding to all index numbers in the effective frequency range of the P-th harmonic spectrum, and summing the obtained moduli to obtain a second value;

[0039] The first value is divided by the second value to obtain the confidence level of the maximum value of the P-th harmonic spectrum amplitude.

[0040] In a possible implementation manner, determining the target spectrum according to the first harmonic spectrum includes:

[0041] Determine a starting index number of the first harmonic spectrum according to the third frequency, and determine an ending index number of the first harmonic spectrum according to the fourth frequency;

[0042] Determine the effective frequency range of the first harmonic spectrum according to the start index number and the end index number of the first harmonic spectrum;

[0043] The effective frequency range of the first harmonic spectrum is used as the target spectrum.

[0044] In a possible implementation, if the confidence level of the maximum amplitude of the multiple harmonic spectrum is greater than or equal to a preset confidence level, determining the target spectrum according to the first harmonic spectrum and the multiple harmonic spectrum includes:

[0045] The value corresponding to each index number within the effective frequency range of the first harmonic spectrum is superimposed with the value of the position corresponding to the index number in the multiple harmonic spectrum to obtain the target spectrum.

[0046] In a possible implementation, the multiple harmonics are P harmonics, P is a positive integer greater than or equal to 2, and the value corresponding to each index number within the effective frequency range of the first harmonic spectrum is superimposed with the value of the index number at the corresponding position in the multiple harmonic spectrum to obtain the target spectrum, including:

[0047] The value corresponding to each index number in the target spectrum is calculated according to a first formula, where the first formula is:

[0048]

[0049] Among them, spectrum′(i) is the target spectrum, spectrum(i) is the effective frequency range of the first harmonic spectrum, weight(p) is the preset coefficient corresponding to the multiple harmonic spectrum, dataFFTp() is the multiple harmonic spectrum, and the value range of i is from the starting index number to the ending index number of the first harmonic spectrum.

[0050] In a possible implementation, the process of preprocessing the echo signal received after the radar transmits the detection signal includes sampling processing, the sampling rate is fs, and determining the heartbeat frequency of the target detection object according to the target spectrum includes:

[0051] Obtain the maximum heartbeat index number corresponding to the maximum amplitude in the target spectrum;

[0052] The heartbeat frequency of the target detection object is determined according to the value corresponding to the maximum heartbeat index number in the target spectrum, the sampling rate and the preset number of frames.

[0053] In a possible implementation, determining the heartbeat frequency of the target detection object according to the value corresponding to the maximum heartbeat index number in the target spectrum, the sampling rate, and the preset number of frames includes:

[0054] The heart rate of the target object is calculated according to a second formula, where the second formula is:

[0055]

[0056] Among them, heartFreq is the heart rate of the target detection object, maxIndHeart is the value corresponding to the maximum index number of the heartbeat in the target spectrum, fs is the sampling rate, N is the preset number of frames, and N is equal to a positive integer power of 2.

[0057] In a possible implementation, the detection signal is a frequency modulated continuous wave signal, the frequency modulation time width of the frequency modulated continuous wave signal is T, the process of preprocessing the echo signal received after the radar transmits the detection signal includes sampling processing, the sampling frequency is fs, then the number of sampling points in one frame of the echo signal is Ns=fs*T, and the fast Fourier transform of each frame of the digital echo signal includes:

[0058] Perform Ns-point fast Fourier transform on each frame of digital echo signal;

[0059] The process of determining the index number corresponding to the target distance point includes:

[0060] The index number corresponding to the target distance point is determined according to the third formula, and the third formula is:

[0061]

[0062] Among them, peopleIndex is used to represent the target distance point, B is used to represent the frequency modulation bandwidth of the frequency modulated continuous wave signal, R is used to represent the preset distance value, and c is used to represent the speed of light.

[0063] In a second aspect, an embodiment of the present invention provides a detection device, 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 the first aspect or any possible implementation method of the first aspect are implemented.

[0064] In a third 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 the first aspect or any possible implementation of the first aspect are implemented.

[0065] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0066] In an embodiment of the present invention, a digital echo signal is obtained by preprocessing the echo signal received after the radar transmits the detection signal; a fast Fourier transform is performed on each frame of the digital echo signal to obtain a one-dimensional distance image corresponding to each frame of the digital echo signal; the value of each frame of the one-dimensional distance image at the target distance point in the one-dimensional distance image of a continuous preset number of frames is obtained to obtain a one-dimensional array, and the target distance point is used to represent the distance point corresponding to the target detection object; according to the one-dimensional array, it is determined whether the target detection object has body movement, and if the target detection object does not have body movement, the heart rate of the target detection object is determined according to the one-dimensional array. The method provided by the present invention eliminates the influence of the body movement of the target detection object on the extraction accuracy before extracting the heart rate of the target detection object, thereby improving the accuracy of the heart rate extraction. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] 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.

[0068] Figure 1 It is a flow chart of an implementation of a heartbeat frequency extraction method provided by an embodiment of the present invention;

[0069] Figure 2 It is a schematic diagram of a frequency modulated continuous wave signal form provided by an embodiment of the present invention;

[0070] Figure 3 is a flow chart of another heart rate extraction method provided by an embodiment of the present invention;

[0071] Figure 4 is a structural schematic diagram of a heart rate extraction device provided by an embodiment of the present invention;

[0072] Figure 5 It is a schematic diagram of a detection device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0073] 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.

[0074] 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.

[0075] See also Figure 1 , which shows a flow chart of a heartbeat frequency extraction method provided by an embodiment of the present invention, which is described in detail as follows:

[0076] In step 101, the echo signal received after the radar transmits the detection signal is preprocessed to obtain a digital echo signal.

[0077] In the embodiment of the present invention, a radar is used to transmit and receive signals, including a transmitting antenna and a receiving antenna, and the transmitting antenna transmits the detection signal in frames.

[0078] In some embodiments, the detection signal emitted by the radar is a frequency modulated continuous wave signal, and the signal form is FMCW (Frequency Modulated Continuous Wave, frequency modulated continuous wave). Figure 2 shown.

[0079] Combination Figure 2 , f0 is the carrier frequency of the radar signal, which is the starting frequency of the signal, B is the frequency modulation bandwidth, T is the frequency modulation time width, and Tframe is the time interval between transmitting two frames of signals.

[0080] Among them, the typical values ​​of each parameter are f0=60GHz, B=2GHz, T=100us, Tframe=50ms.

[0081] FMCW technology is a technology used in high-precision radar ranging. Its basic principle is that the transmitted wave is a high-frequency continuous wave, and its frequency changes over time according to the law of triangular waves. The echo frequency received by FMCW has the same change law as the transmitted frequency, both of which are triangular wave laws, but there is a time difference. This tiny time difference can be used to calculate the target distance.

[0082] The transmitting antenna transmits a frame of FMCW signal, the receiving antenna receives a frame of corresponding radar echo signal, and pre-processes the received radar echo signal to obtain a digital echo signal.

[0083] In a possible implementation, the preprocessing process includes down-conversion, filtering, sampling and other processing processes. Wherein, the sampling rate is fs, and the number of sampling points in a frame of echo signal is Ns=fs*T. The typical value of fs is 640KHz, and T is the frequency modulation time width. Since the typical value of T is 100us, the typical value of Ns is 64. The digital echo signal in a frame is recorded as Sr(i), where i=1, 2...Ns.

[0084] In step 102, a fast Fourier transform is performed on each frame of digital echo signal to obtain a one-dimensional range image corresponding to each frame of digital echo signal.

[0085] In the embodiment of the present invention, a fast Fourier transform of Nfft points is performed on each frame of digital echo signal to obtain a one-dimensional range image corresponding to each frame of digital echo signal, wherein the digital echo signal is composed of Ns sampling points, 2 x-1 <Ns<=Nfft=2 x , x is a positive integer.

[0086] That is, Nfft is the smallest integer power of 2 that is greater than or equal to Ns, and the obtained fast Fourier transform (FFT) result is recorded as Sr_FFT, which is a complex array of Nfft points.

[0087] For example, in conjunction with the example in step 101, the typical value of Ns is 64, and Nfft is equal to 64. In some embodiments, Ns is not a positive integer power of 2, such as Ns=60, and Nfft is equal to 64, or Ns=120, and Nfft is equal to 128, that is, Nfft is an integer power of 2 that is greater than Ns and has the smallest difference with Ns.

[0088] The one-dimensional range image corresponding to each frame of digital echo signal is a complex array of Nfft points. For example, it is a complex array of 64 points. Taking the one-dimensional range image as a complex array of 64 points as an example, each complex number corresponds to an index number Index in order, which is 0-63, that is, the index number of the first complex number in the one-dimensional range image obtained after FFT is 0, the index number of the second complex number is 1... The index number of the 64th complex number is 63.

[0089] In step 103, the value of each one-dimensional range image at the target range point in a continuous preset number of one-dimensional range images is obtained to obtain a one-dimensional array, and the target range point is used to represent the range point corresponding to the target detection object.

[0090] In the embodiment of the present invention, depending on different application scenarios, the target detection object may be a human body or other living organisms, such as an animal, which is not limited in the embodiment of the present invention.

[0091] In the embodiment of the present invention, the target distance point refers to the distance point corresponding to the target detection object. For example, if the target detection object is a person, the index number corresponding to the target distance point can be represented by peopleIndex, and the value corresponding to the target distance point is the complex value corresponding to peopleIndex in the one-dimensional distance image.

[0092] When detecting an object, the radar sends a detection signal, which is used to detect objects within a certain range. In the embodiment of the present invention, the objects within a certain range include the target detection body. The radar receives the echo signal, pre-processes the echo signal, obtains a digital echo signal, performs FFT on the digital echo signal, and obtains 64 complex numbers, such as performing a 64-point FFT, each of which is used to represent the frequency domain data corresponding to a distance point. These 64 complex numbers include the data of the distance point corresponding to the target detection body, and also include the data of other distance points. In the embodiment of the present invention, the target distance point refers to the distance point corresponding to the target detection body.

[0093] In a possible implementation, when the detection signal emitted by the radar is a frequency modulated continuous wave signal, the frequency modulation time width of the frequency modulated continuous wave signal is T, the process of preprocessing the echo signal received after the radar emits the detection signal includes sampling processing, the sampling frequency is fs, and the number of sampling points in one frame of the echo signal is Ns=fs*T, and the fast Fourier transform of each frame of the digital echo signal includes:

[0094] Perform Ns-point fast Fourier transform on each frame of digital echo signal;

[0095] The process of determining the index number peopleIndex corresponding to the target distance point includes:

[0096] The index number corresponding to the target distance point is determined according to the third formula. The third formula is:

[0097]

[0098] Among them, peopleIndex is used to represent the target distance point, B is used to represent the frequency modulation bandwidth of the frequency modulated continuous wave signal, R is used to represent the preset distance value, and c is used to represent the speed of light.

[0099] That is to say, when the number of sampling points is the same as the number of points for performing FFT on each frame of the digital echo signal, the index number peopleIndex corresponding to the target distance point can be calculated by the third formula above. When peopleIndex is a decimal, the nearest positive integer is taken. For example, if the calculated peopleIndex=36.7, peopleIndex=37 is taken. For example, if the calculated peopleIndex=36.1, peopleIndex=36 is taken.

[0100] In an embodiment of the present invention, R is used to represent the distance between the radar and the target detection object. In a possible implementation, the target detection object is a human body, and the human body is located on a bed. The radar can be installed directly facing the human body. The typical installation position is the ceiling above the bed. The distance between the radar and the bed is measured and recorded as R. The size of R is the preset distance value of the third formula above.

[0101] In one possible implementation, a frame counter is preset, and the initial value of the frame counter is 0 when it is powered on. After each one-dimensional range image corresponding to a frame array echo signal is received, the frame counter is increased by 1 to determine whether the count value of the frame counter reaches a preset frame count threshold value N. The typical value of N is 128, and N may also take other values ​​according to actual applications, which is not limited in the embodiment of the present invention.

[0102] In the embodiment of the present invention, the continuous preset number of frames is the continuous N frames mentioned above.

[0103] When the value of the frame counter reaches N, the value of each one-dimensional range image in the N frames of one-dimensional range images at the target distance point is obtained to obtain a one-dimensional array.

[0104] In a possible implementation, the value Sr_FFT(peopleIndex) of each frame of the one-dimensional range image at the target range point is recorded in dataBuffer(n). dataBuffer(n) is a one-dimensional array of length N, and the initial value is N zeros. When the frame counter reaches N, the one-dimensional array includes N peopleIndex data.

[0105] In step 104, it is determined whether the target detection object has body movement according to the one-dimensional array.

[0106] In a possible implementation, a body motion energy value of the target detection object is obtained according to a one-dimensional array; and according to the body motion energy value of the target detection object, it is determined whether the target detection object has body movement.

[0107] In one possible implementation, the process of obtaining the body motion energy value of the target detection object includes: performing bandpass filtering on a one-dimensional array through a first bandpass filter to obtain a first filtering result, wherein the passband of the first bandpass filter is from a first frequency to a second frequency, the first frequency is the minimum value of the motion frequency when the target detection object performs body movement, and the second frequency is the maximum value of the motion frequency when the target detection object performs body movement; performing a modulus operation on each data in the first filtering result, and summing the modulus of each data to obtain the body motion energy value of the target detection object.

[0108] The N data in dataBuffer are subjected to FIR (Finite Impulse Response, finite unit impulse response) bandpass filtering, and the passband of the bandpass filtering is from the first frequency f1 to the second frequency f2, wherein the first frequency f1 is the minimum value of the motion frequency when the target detection object performs body movement, that is, the lower limit value, and the second frequency f2 is the maximum value of the motion frequency when the target detection object performs body movement, that is, the upper limit value. When the target detection object is a human body, the typical value of f1 is 0.5Hz, and the typical value of f2 is 4Hz.

[0109] In a possible implementation, a first filtering result of performing bandpass filtering on the one-dimensional array through the first bandpass filter may be recorded as dataFilterMove, where dataFilterMove is an array of N points.

[0110] In a possible implementation, the body motion energy value of the target detection body is recorded as movePower, and movePower is calculated by the following formula:

[0111]

[0112] Wherein, abs is a complex modulus operation, and dataFilterMove(i) is the i-th data in the filtering result dataFilterMove.

[0113] In one possible implementation, the body motion energy value of the target detection object is compared with a preset body motion energy threshold. If the body motion energy value of the target detection object is less than or equal to the body motion energy threshold, there is no body movement of the target detection object. If the body motion energy value of the target detection object is greater than the body motion energy threshold, there is body movement of the target detection object.

[0114] In the embodiment of the present invention, the body motion energy threshold may be represented by moveThre.

[0115] In step 105, if the target detection object does not have body movement, the heartbeat frequency of the target detection object is determined according to the one-dimensional array.

[0116] On the basis of determining that the target detection object has no body movement, the heartbeat frequency of the target detection object is obtained through the value of each frame of the one-dimensional range image at the target distance point in a continuous preset number of one-dimensional range images, thereby improving the extraction accuracy of the heartbeat frequency.

[0117] In an embodiment of the present invention, a digital echo signal is obtained by preprocessing the echo signal received after the radar transmits the detection signal; a fast Fourier transform is performed on each frame of the digital echo signal to obtain a one-dimensional distance image corresponding to each frame of the digital echo signal; the value of each frame of the one-dimensional distance image at the target distance point in the one-dimensional distance image of a continuous preset number of frames is obtained to obtain a one-dimensional array, and the target distance point is used to represent the index number corresponding to the target detection object; based on the one-dimensional array, it is determined whether the target detection object has body movement, and if the target detection object does not have body movement, the heart rate of the target detection object is determined based on the one-dimensional array. The method provided by the present invention eliminates the influence of the body movement of the target detection object on the extraction accuracy before extracting the heart rate of the target detection object, thereby improving the accuracy of the heart rate extraction.

[0118] Figure 3 A flowchart of another heart rate extraction method provided by an embodiment of the present invention is shown, which is described in detail as follows:

[0119] In step 301, the echo signal received after the radar transmits the detection signal is preprocessed to obtain a digital echo signal.

[0120] The specific implementation of this step can be found in Figure 1 The corresponding step 101 of the embodiment will not be described in detail in the embodiment of the present invention.

[0121] In step 302, a fast Fourier transform is performed on each frame of digital echo signal to obtain a one-dimensional range image corresponding to each frame of digital echo signal.

[0122] The specific implementation of this step can be found in Figure 1 The corresponding step 102 of the embodiment will not be described in detail in the embodiment of the present invention.

[0123] In step 303, the value of each one-dimensional range image at the target range point in a continuous preset number of one-dimensional range images is obtained to obtain a one-dimensional array, and the target range point is used to represent the index number corresponding to the target detection object.

[0124] The specific implementation of this step can be found in Figure 1 The corresponding step 103 of the embodiment will not be described in detail in the embodiment of the present invention.

[0125] In step 304, it is determined whether the target detection object has body movement according to the one-dimensional array.

[0126] The specific implementation of this step can be found in Figure 1 The corresponding step 104 of the embodiment will not be described in detail in the embodiment of the present invention.

[0127] In step 305, if the target detection object does not have body movement, the one-dimensional array is filtered and the filtering result is fast Fourier transformed to obtain the harmonic spectrum of the target detection object's heartbeat frequency, which includes the first harmonic spectrum and multiple harmonic spectrum of the target detection object.

[0128] In a possible implementation, the harmonic spectrum of the target detection body's heartbeat frequency may include a first harmonic spectrum, and may also include a first harmonic spectrum and multiple harmonic spectrums. Exemplarily, the multiple harmonic spectrum may include a second harmonic spectrum; or, the multiple harmonic spectrum may include a second harmonic spectrum and a third harmonic spectrum; or, the multiple harmonic spectrum may include second and higher harmonic spectrums.

[0129] In different application scenarios, the heartbeat frequency intervals of the target detection object to be monitored are different. When the multiple harmonic spectra include the second harmonic spectrum and the third harmonic spectrum, for example, the target detection object is an elderly person, and the monitoring scenario is to monitor the elderly person at night, and the heartbeat frequency is between 50Hz and 100Hz, bandpass filtering is performed in this frequency interval, and then the filtering result is fast Fourier transformed to obtain the first harmonic spectrum of the heartbeat frequency of the target detection object. Bandpass filtering is performed at twice the frequency interval, and then the filtering result is fast Fourier transformed to obtain the second harmonic spectrum of the target detection object; bandpass filtering is performed at three times the frequency interval, and then the filtering result is fast Fourier transformed to obtain the third harmonic spectrum of the target detection object.

[0130] In other application scenarios, for example, when monitoring patients, their heart rate may be between 50 Hz and 140 Hz; or, when monitoring animals, their heart rate interval may be set according to actual conditions, which is not limited in the embodiments of the present invention.

[0131] In step 306, a target spectrum is obtained according to the harmonic spectrum of the heartbeat frequency of the target detection object.

[0132] Calculate the confidence of the maximum value of the multiple harmonic spectrum amplitude. If the confidence of the maximum value of the multiple harmonic spectrum amplitude is greater than or equal to the preset confidence, determine the target spectrum based on the primary harmonic spectrum and the multiple harmonic spectrum. If the confidence of the maximum value of the multiple harmonic spectrum amplitude is less than the preset confidence, determine the target spectrum based on the primary harmonic spectrum.

[0133] In one possible implementation, the process of acquiring the first harmonic spectrum includes: performing bandpass filtering on the one-dimensional array through a second bandpass filter to obtain a second filtering result, wherein the passband of the second bandpass filter is from the third frequency to the fourth frequency, the third frequency is a preset minimum value of the heartbeat frequency of the target detection object, and the fourth frequency is a preset maximum value of the heartbeat frequency of the target detection object; performing a fast Fourier transform on the second filtering result to obtain the first harmonic spectrum of the heartbeat frequency of the target detection object.

[0134] In one possible implementation, the multiple harmonic spectrum is a P-th harmonic spectrum, and the process of acquiring the multiple harmonic spectrum includes: performing bandpass filtering on the one-dimensional array through a third bandpass filter to obtain a third filtering result, wherein the passband of the third bandpass filter is from the fifth frequency to the sixth frequency, the fifth frequency is P times the third frequency, the sixth frequency is P times the fourth frequency, and P is a positive integer greater than or equal to 2; performing a fast Fourier transform on the third filtering result to obtain a P-th harmonic spectrum of the heartbeat frequency of the target detection object.

[0135] The following is a specific example for explanation. The target detection object is an elderly person. The application scenario is to monitor the heart rate of the elderly person during sleep at night. The heart rate of the elderly person is between 50Hz and 100Hz. The multiple harmonic spectrum includes the second harmonic spectrum and the third harmonic spectrum. The passband of the second bandpass filter is 50Hz to 100Hz, that is, the third frequency is 50Hz, and the fourth frequency is 100Hz. When the third bandpass filter is used to obtain the second harmonic spectrum and the third harmonic spectrum of the target detection object, the third bandpass filter can include two sub-filter modules, the first The passband of the first sub-filter module is twice the range from 50Hz to 100Hz, i.e., 100Hz to 200Hz, and the passband of the second sub-filter module is three times the range from 50Hz to 100Hz, i.e., 150Hz to 300Hz. For ease of understanding, the second bandpass filter can be denoted as FIR1, the first sub-filter module as FIR2, and the second sub-filter module as FIR3, where the passband of FIR1 is 50Hz-100Hz, the passband of FIR2 is 100Hz-200Hz, and the passband of FIR3 is 150Hz-300Hz.

[0136] The filtering results obtained after filtering by FIR1, FIR2 and FIR3 are recorded as dataFilter1, dataFilter2 and dataFilter3 respectively. After fast Fourier transform is performed on the three filtering results, three FFT results are obtained, which are recorded as dataFFT1, dataFFT2 and dataFFT3 respectively. dataFFT1 is the first harmonic spectrum, dataFFT2 is the second harmonic spectrum, and dataFFT3 is the third harmonic spectrum.

[0137] In one possible implementation, calculating the confidence level of the maximum amplitude of a multiple harmonic spectrum includes: determining the starting index number of the P-th harmonic spectrum according to the fifth frequency, and determining the ending index number of the P-th harmonic spectrum according to the sixth frequency; determining the effective frequency range of the P-th harmonic spectrum according to the starting index number and the ending index number of the P-th harmonic spectrum; taking the index number corresponding to the position of the maximum amplitude in the effective frequency range of the P-th harmonic spectrum as the center index number; taking multiple consecutive index numbers centered on the center index number as target index numbers, the number of target index numbers being less than the number of index numbers in the effective frequency range of the P-th harmonic spectrum; performing a modulo operation on the data corresponding to the target index number, and summing the obtained modulos to obtain a first value; performing a modulo operation on the data corresponding to all index numbers in the effective frequency range of the P-th harmonic spectrum, and summing the obtained modulos to obtain a second value; dividing the first value by the second value to obtain the confidence level of the maximum amplitude of the P-th harmonic spectrum.

[0138] The multiple harmonic spectra are taken as the second harmonic spectrum and the third harmonic spectrum as an example for description.

[0139] In the embodiment of the present invention, the starting index number of the first harmonic spectrum is recorded as ind1, the ending index number of the first harmonic spectrum is recorded as ind2, the starting index number of the second harmonic spectrum is recorded as ind3, the ending index number of the second harmonic spectrum is recorded as ind4, the starting index number of the third harmonic spectrum is recorded as ind5, and the ending index number of the third harmonic spectrum is recorded as ind6. Take the passband of FIR1 as 50Hz-100Hz, the passband of FIR2 as 100Hz-200Hz, and the passband of FIR3 as 150Hz-300Hz as an example for explanation.

[0140] First, calculate the values ​​of ind3, ind4, ind5 and ind6 respectively, where ind3 is the index number corresponding to 100Hz in dataFFT2, ind4 is the index number corresponding to 200Hz in dataFFT2, ind5 is the index number corresponding to 150Hz in dataFFT3, and ind6 is the index number corresponding to 300Hz in dataFFT3.

[0141] In a possible implementation, the values ​​of ind3, ind4, ind5, and ind6 are calculated respectively by the following formulas:

[0142]

[0143]

[0144]

[0145]

[0146] Among them, floor() is used to represent the rounding down operation, which is used to take the positive integer that is smaller than the calculated value and closest to the calculated value. For example, if the calculated value is 5.6, 5 is taken. The process of preprocessing the echo signal received after the radar transmits the detection signal includes sampling processing, and the sampling rate is fs, that is, fs in the above formula is the sampling rate; N is the preset frame number, and the typical value is 256.

[0147] Then the effective frequency range of the second harmonic spectrum is from ind3 to ind4, and the effective frequency range of the third harmonic spectrum is from ind5 to ind6.

[0148] For any harmonic spectrum, the harmonic spectrum is composed of multiple complex numbers, each of which contains both amplitude information and phase information. Find the index number corresponding to the maximum amplitude position within the effective frequency range of the second harmonic spectrum dataFFT2, recorded as maxInd2, and the index number corresponding to the maximum amplitude position within the effective frequency range of the third harmonic spectrum dataFFT3, recorded as maxInd3.

[0149] For example, three consecutive index numbers centered around maxInd2 are determined as target index numbers, namely maxInd2-1, maxInd2, and maxInd2+1; three consecutive index numbers centered around maxInd3 are determined as target index numbers, namely maxInd3-1, maxInd3, and maxInd3+1.

[0150] When calculating the confidence level of the maximum value of the second harmonic spectrum amplitude, the following formula is used:

[0151]

[0152] When calculating the confidence level of the maximum value of the third harmonic spectrum amplitude, the following formula is used:

[0153]

[0154] Among them, confidence2 is the confidence of the maximum amplitude of the second harmonic spectrum, abs() is the modulo operation, and confidence3 is the confidence of the maximum amplitude of the third harmonic spectrum.

[0155] The above-mentioned taking three consecutive index numbers centered on the central index number as the target index number is only an example. According to actual needs, five consecutive index numbers, seven index numbers, etc. centered on the central index number can also be taken as the target index number. The embodiment of the present invention is not limited to this.

[0156] The preset confidence can be recorded as confidenceThre. Taking multiple harmonic spectra including the second harmonic spectrum and the third harmonic spectrum as an example, different situations are discussed:

[0157] In the first case, confidence2<confidenceThre, confidence3<confidenceThre, then the target spectrum is determined only based on the first harmonic spectrum;

[0158] In the second case, confidence2≥confidenceThre, confidence3<confidenceThre, the target spectrum is determined according to the first harmonic spectrum and the second harmonic spectrum;

[0159] In the third case, confidence2<confidenceThre, confidence3≥confidenceThre; the target spectrum is determined according to the first harmonic spectrum and the third harmonic spectrum;

[0160] In the fourth case, confidence2≥confidenceThre, confidence3≥confidenceThre, the target spectrum is determined based on the first harmonic spectrum, the second harmonic spectrum and the third harmonic spectrum.

[0161] It should be noted that, in another possible actual situation, the preset confidence Thres corresponding to confidence2 and confidence3, that is, the confidence threshold values, may be the same or different, and this is not limited in the embodiment of the present invention.

[0162] When the first condition is met, the target spectrum is determined based on the first harmonic spectrum only, including:

[0163] Determine the starting index number of the first harmonic spectrum according to the third frequency, and determine the ending index number of the first harmonic spectrum according to the fourth frequency; determine the effective frequency range of the first harmonic spectrum according to the starting index number and the ending index number of the first harmonic spectrum; and use the effective frequency range of the first harmonic spectrum as the target spectrum.

[0164] Assuming the passband of FIR1 is 50Hz-100Hz, the starting index of the first harmonic spectrum is recorded as ind1, and the ending index of the first harmonic spectrum is recorded as ind2, then:

[0165]

[0166]

[0167] Then the effective frequency range corresponding to ind1 to ind2 in dataFFT1 is the target spectrum.

[0168] When the second to fourth situations mentioned above are met, the value corresponding to each index number in the effective frequency range of the primary harmonic spectrum is superimposed with the value of the index number at the corresponding position in the multiple harmonic spectra to obtain the target spectrum.

[0169] In a possible implementation, the value corresponding to each index number in the target spectrum is calculated according to a first formula, where the first formula is:

[0170]

[0171] Among them, spectrum′(i) is the target spectrum, spectrum(i) is the effective frequency range of the first harmonic spectrum, weight(p) is the preset coefficient corresponding to the multiple harmonic spectrum, dataFFTp() is the multiple harmonic spectrum, and the value range of i is from the starting index number to the ending index number of the first harmonic spectrum.

[0172] When the second case is met, in the above formula, p=2, weight(p) is the preset coefficient corresponding to the second harmonic spectrum, for example, weight(2)=0.5;

[0173] When the third situation is met, in the above formula, p=3, weight(p) is the preset coefficient corresponding to the third harmonic spectrum, for example, weight(3)=0.5.

[0174] The value range of i in the above first formula is from ind1 to in2.

[0175] When the fourth situation mentioned above is met, then:

[0176]

[0177] The value range of i is from ind1 to in2.

[0178] In another possible implementation, when the second and third conditions above are met, the value corresponding to each index number in the target spectrum can also be calculated by the following formula:

[0179] spectrum'(i)=spectrum(i)+weight(p)dataFFp(pi)

[0180] In step 307, the heartbeat frequency of the target detection object is determined according to the target frequency spectrum.

[0181] In an embodiment of the present invention, the maximum heartbeat index number corresponding to the maximum amplitude in the target spectrum is obtained; the heartbeat frequency of the target detection object is determined according to the value corresponding to the maximum heartbeat index number in the target spectrum, the sampling rate and the preset frame number.

[0182] In a possible implementation, the heart rate of the target detection object is calculated according to the second formula, and the second formula is:

[0183]

[0184] Among them, heartFreq is the heartbeat frequency of the target detection object, maxIndHeart is the value corresponding to the maximum index number of the heartbeat in the target spectrum, fs is the sampling rate, N is the preset number of frames, and N is equal to a positive integer power of 2.

[0185] The present invention determines the target spectrum through the first harmonic spectrum and multiple harmonic spectrum of the heartbeat spectrum of the target detection object. When the amplitude of the first harmonic spectrum of the heartbeat frequency is not high, but the amplitudes of multiple harmonic spectrums such as the second and third harmonics are relatively high, the first harmonic spectrum and the multiple harmonic spectrum are comprehensively extracted to comprehensively extract the heartbeat frequency of the target detection object, thereby improving the extraction accuracy of the heartbeat frequency.

[0186] 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.

[0187] 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.

[0188] Figure 4 The structure diagram of the heart rate extraction device provided by the embodiment of the present invention is shown. For the convenience of description, only the part related to the embodiment of the present invention is shown, which is described in detail as follows:

[0189] like Figure 4 As shown, the heart rate extraction device 4 includes: a preprocessing module 41, a one-dimensional range image acquisition module 42, a one-dimensional array acquisition module 43, a body movement judgment module 44 and a heart rate detection module 45;

[0190] The preprocessing module 41 is used to preprocess the echo signal received after the radar transmits the detection signal to obtain a digital echo signal;

[0191] A one-dimensional range image acquisition module 42 is used to perform a fast Fourier transform on each frame of digital echo signal to obtain a one-dimensional range image corresponding to each frame of digital echo signal;

[0192] A one-dimensional array acquisition module 43 is used to acquire the value of each one-dimensional range image at a target range point in a continuous preset number of one-dimensional range images to obtain a one-dimensional array, wherein the target range point is used to represent the range point corresponding to the target detection object;

[0193] A body movement determination module 44 is used to determine whether the target detection object has body movement according to the one-dimensional array;

[0194] The heart rate detection module 45 is used to determine the heart rate of the target detection object according to the one-dimensional array if there is no body movement of the target detection object.

[0195] In an embodiment of the present invention, a digital echo signal is obtained by preprocessing the echo signal received after the radar transmits the detection signal; a fast Fourier transform is performed on each frame of the digital echo signal to obtain a one-dimensional distance image corresponding to each frame of the digital echo signal; the value of each frame of the one-dimensional distance image at the target distance point in the one-dimensional distance image of a continuous preset number of frames is obtained to obtain a one-dimensional array, and the target distance point is used to represent the index number corresponding to the target detection object; based on the one-dimensional array, it is determined whether the target detection object has body movement, and if the target detection object does not have body movement, the heart rate of the target detection object is determined based on the one-dimensional array. The method provided by the present invention eliminates the influence of the body movement of the target detection object on the extraction accuracy before extracting the heart rate of the target detection object, thereby improving the accuracy of the heart rate extraction.

[0196] In a possible implementation, the body movement determination module 44 is used to:

[0197] According to the one-dimensional array, the body motion energy value of the target detection body is obtained;

[0198] According to the body motion energy value of the target detection object, it is determined whether the target detection object has body motion.

[0199] In a possible implementation, the body movement determination module 44 is used to:

[0200] Performing bandpass filtering on the one-dimensional array through a first bandpass filter to obtain a first filtering result, wherein the passband of the first bandpass filter is from a first frequency to a second frequency, the first frequency is a minimum frequency when the target detection object performs body movement, and the second frequency is a maximum frequency when the target detection object performs body movement;

[0201] A modulus operation is performed on each data in the first filtering result, and the modulus of each data is summed to obtain the body motion energy value of the target detection body.

[0202] In a possible implementation, the body movement determination module 44 is used to:

[0203] The body motion energy value of the target detection object is compared with the preset body motion energy threshold. If the body motion energy value of the target detection object is less than or equal to the body motion energy threshold, there is no body movement of the target detection object. If the body motion energy value of the target detection object is greater than the body motion energy threshold, there is body movement of the target detection object.

[0204] In a possible implementation, the heart rate detection module 45 is used to:

[0205] Filtering the one-dimensional array and performing fast Fourier transform on the filtering result to obtain the harmonic spectrum of the heartbeat frequency of the target detection object, where the harmonic spectrum includes the first harmonic spectrum and multiple harmonic spectrum of the target detection object;

[0206] According to the harmonic spectrum of the heartbeat frequency of the target detection object, a target spectrum is obtained;

[0207] According to the target frequency spectrum, the heartbeat frequency of the target detection object is determined.

[0208] In a possible implementation, the heart rate detection module 45 is used to:

[0209] Calculate the confidence level of the maximum value of the multiple harmonic spectrum amplitude;

[0210] If the confidence level of the maximum value of the multiple harmonic spectrum amplitude is greater than or equal to the preset confidence level, the target spectrum is determined based on the first harmonic spectrum and the multiple harmonic spectrum;

[0211] If the confidence level of the maximum value of the multiple harmonic spectrum amplitude is less than the preset confidence level, the target spectrum is determined based on the single harmonic spectrum.

[0212] In a possible implementation, the heart rate detection module 45 is used to:

[0213] Performing bandpass filtering on the one-dimensional array through a second bandpass filter to obtain a second filtering result, wherein the passband of the second bandpass filter is from the third frequency to the fourth frequency, the third frequency is a preset minimum value of the heartbeat frequency of the target detection object, and the fourth frequency is a preset maximum value of the heartbeat frequency of the target detection object;

[0214] The second filtering result is subjected to a fast Fourier transform to obtain a first harmonic spectrum of the heartbeat frequency of the target detection object.

[0215] In a possible implementation, the heart rate detection module 45 is used to:

[0216] Performing bandpass filtering on the one-dimensional array through a third bandpass filter to obtain a third filtering result, wherein the passband of the third bandpass filter is from the fifth frequency to the sixth frequency, the fifth frequency is P times the third frequency, the sixth frequency is P times the fourth frequency, and P is a positive integer greater than or equal to 2;

[0217] The third filtering result is subjected to a fast Fourier transform to obtain a P-th harmonic spectrum of the heartbeat frequency of the target detection body.

[0218] In a possible implementation, the heart rate detection module 45 is used to:

[0219] Determine the starting index number of the P-th harmonic spectrum according to the fifth frequency, and determine the ending index number of the P-th harmonic spectrum according to the sixth frequency;

[0220] Determine the effective frequency range of the P-order harmonic spectrum according to the start index number and the end index number of the P-order harmonic spectrum;

[0221] The index number corresponding to the position of the maximum amplitude in the effective frequency range of the P-th harmonic spectrum is used as the center index number;

[0222] Taking a plurality of consecutive index numbers centered on the central index number as target index numbers, the number of the target index numbers being less than the number of index numbers in the effective frequency range of the P-th harmonic spectrum;

[0223] Performing a modulo operation on the data corresponding to the target index number, and summing the obtained moduli to obtain a first value;

[0224] Performing a modulo operation on the data corresponding to all index numbers in the effective frequency range of the P-th harmonic spectrum, and summing the obtained moduli to obtain a second value;

[0225] The first value is divided by the second value to obtain the confidence level of the maximum value of the P-th harmonic spectrum amplitude.

[0226] In a possible implementation, the heart rate detection module 45 is used to:

[0227] Determine a starting index number of the first harmonic spectrum according to the third frequency, and determine an ending index number of the first harmonic spectrum according to the fourth frequency;

[0228] Determine the effective frequency range of the first harmonic spectrum according to the start index number and the end index number of the first harmonic spectrum;

[0229] The effective frequency range of the first harmonic spectrum is taken as the target spectrum.

[0230] In a possible implementation, the heart rate detection module 45 is used to:

[0231] The value corresponding to each index number within the effective frequency range of the first harmonic spectrum is superimposed with the value of the index number at the corresponding position in the multiple harmonic spectra to obtain the target spectrum.

[0232] In a possible implementation, the heart rate detection module 45 is used to:

[0233] The value corresponding to each index number in the target spectrum is calculated according to the first formula. The first formula is:

[0234]

[0235] Among them, spectrum′(i) is the target spectrum, spectrum(i) is the effective frequency range of the first harmonic spectrum, weight(p) is the preset coefficient corresponding to the multiple harmonic spectrum, dataFFTp() is the multiple harmonic spectrum, and the value range of i is from the starting index number to the ending index number of the first harmonic spectrum.

[0236] In a possible implementation, the heart rate detection module 45 is used to:

[0237] Get the maximum heartbeat index number corresponding to the maximum amplitude in the target spectrum;

[0238] The heartbeat frequency of the target detection object is determined according to the value corresponding to the maximum index number of the heartbeat in the target spectrum, the sampling rate and the preset number of frames.

[0239] In a possible implementation, the heart rate detection module 45 is used to:

[0240] The heart rate of the target object is calculated according to the second formula. The second formula is:

[0241]

[0242] Among them, heartFreq is the heartbeat frequency of the target detection object, maxIndHeart is the value corresponding to the maximum index number of the heartbeat in the target spectrum, fs is the sampling rate, N is the preset number of frames, and N is equal to a positive integer power of 2.

[0243] In a possible implementation, the detection signal is a frequency modulated continuous wave signal, the frequency modulation time width of the frequency modulated continuous wave signal is T, the process of preprocessing the echo signal received after the radar transmits the detection signal includes sampling processing, the sampling frequency is fs, then the number of sampling points in one frame of echo signal is Ns=fs*T, and the one-dimensional range image acquisition module 42 is used to: perform a fast Fourier transform of Ns points on each frame of digital echo signal;

[0244] The one-dimensional array acquisition module 43 is used to determine the index number corresponding to the target distance point according to the third formula. The third formula is:

[0245]

[0246] Among them, peopleIndex is used to represent the index number corresponding to the target distance point, B is used to represent the frequency modulation bandwidth of the frequency modulated continuous wave signal, R is used to represent the preset distance value, and c is used to represent the speed of light.

[0247] The heart rate extraction device provided in this embodiment can be used to execute the above-mentioned heart rate extraction method embodiment. Its implementation principle and technical effect are similar, and this embodiment will not be repeated here.

[0248] Figure 5 Schematic diagram of a detection device provided by an embodiment of the present invention. Figure 5 As shown, the detection device 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 extraction 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 41 to 45 are shown.

[0249] 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 detection device 5.

[0250] The detection device 5 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The detection device 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 the detection device 5 and does not constitute a limitation of the detection device 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 detection device may also include input and output devices, network access devices, buses, etc.

[0251] 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.

[0252] The memory 51 may be an internal storage unit of the detection device 5, such as a hard disk or memory of the detection device 5. The memory 51 may also be an external storage device of the detection device 5, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card) etc. equipped on the detection device 5. Further, the memory 51 may also include both an internal storage unit and an external storage device of the detection device 5. The memory 51 is used to store the computer program and other programs and data required by the detection device. The memory 51 may also be used to temporarily store data that has been output or is to be output.

[0253] 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.

[0254] 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.

[0255] 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.

[0256] In the embodiments provided by the present invention, it should be understood that the disclosed devices / detection equipment and methods can be implemented in other ways. For example, the device / detection equipment 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.

[0257] 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.

[0258] 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.

[0259] 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 various heart rate extraction 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 capable of carrying 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), electric 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 practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electric carrier signals and telecommunication signals.

[0260] 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 extraction method, characterized in that: include: Preprocessing the echo signal received after the radar transmits the detection signal to obtain a digital echo signal; Perform fast Fourier transform on each frame of digital echo signal to obtain a one-dimensional range image corresponding to each frame of digital echo signal; Obtaining the value of each one-dimensional range image at a target range point in a continuous preset number of one-dimensional range images to obtain a one-dimensional array, wherein the target range point is used to represent the range point corresponding to the target detection object; Determining whether the target detection object has body movement according to the one-dimensional array; If the target detection object does not have body movement, determining the heart rate of the target detection object according to the one-dimensional array; If the target detection object does not have body movement, determining the heart rate of the target detection object according to the one-dimensional array includes: Filtering the one-dimensional array and performing fast Fourier transform on the filtering result to obtain a harmonic spectrum of the heartbeat frequency of the target detection object, wherein the harmonic spectrum includes a first harmonic spectrum and multiple harmonic spectrums of the target detection object; Obtaining a target spectrum according to the harmonic spectrum of the heartbeat frequency of the target detection object; Determining the heart rate of the target object according to the target frequency spectrum; The process of preprocessing the echo signal received after the radar transmits the detection signal includes sampling processing, and the sampling rate is fs , determining the heartbeat frequency of the target detection object according to the target frequency spectrum includes: Obtain the maximum heartbeat index number corresponding to the maximum amplitude in the target spectrum; The heartbeat frequency of the target detection object is determined according to the value corresponding to the maximum heartbeat index number in the target spectrum, the sampling rate and the preset number of frames.

2. The method according to claim 1, characterized in that The determining, according to the one-dimensional array, whether the target detection object has body movement comprises: Acquiring a body motion energy value of the target detection object according to the one-dimensional array; According to the body motion energy value of the target detection object, it is determined whether the target detection object has body motion.

3. The method according to claim 2, characterized in that The acquiring the body motion energy value of the target detection object according to the one-dimensional array comprises: Performing bandpass filtering on the one-dimensional array through a first bandpass filter to obtain a first filtering result, wherein the passband of the first bandpass filter is from a first frequency to a second frequency, the first frequency is a minimum value of the motion frequency when the target detection object performs body movement, and the second frequency is a maximum value of the motion frequency when the target detection object performs body movement; A modulus operation is performed on each data in the first filtering result, and the modulus of each data is summed to obtain the body motion energy value of the target detection body.

4. The method according to claim 1, characterized in that: The obtaining of the target spectrum according to the harmonic spectrum of the heartbeat frequency of the target detection object comprises: Calculating the confidence level of the maximum value of the multiple harmonic spectrum amplitude; If the confidence level of the maximum value of the amplitude of the multiple harmonic spectrum is greater than or equal to a preset confidence level, determining a target spectrum according to the first harmonic spectrum and the multiple harmonic spectrum; If the confidence level of the maximum amplitude value of the multiple harmonic spectrum is less than a preset confidence level, the target spectrum is determined according to the first harmonic spectrum.

5. The method according to claim 4, characterized in that The process of acquiring the first harmonic spectrum includes: Performing bandpass filtering on the one-dimensional array through a second bandpass filter to obtain a second filtering result, wherein the passband of the second bandpass filter is from a third frequency to a fourth frequency, the third frequency is a preset minimum value of the heartbeat frequency of the target detection object, and the fourth frequency is a preset maximum value of the heartbeat frequency of the target detection object; Performing a fast Fourier transform on the second filtering result to obtain a first harmonic spectrum of the heartbeat frequency of the target detection object; The multiple harmonic spectrum is a P-order harmonic spectrum, and the acquisition process of the multiple harmonic spectrum includes: Performing bandpass filtering on the one-dimensional array through a third bandpass filter to obtain a third filtering result, wherein the passband of the third bandpass filter is from a fifth frequency to a sixth frequency, the fifth frequency is P times the third frequency, the sixth frequency is P times the fourth frequency, and P is a positive integer greater than or equal to 2; The third filtering result is subjected to a fast Fourier transform to obtain a P-th harmonic spectrum of the heartbeat frequency of the target detection object.

6. The method according to claim 5, characterized in that The step of calculating the confidence level of the maximum value of the multiple harmonic spectrum amplitude comprises: Determine a starting index number of the P-th harmonic spectrum according to the fifth frequency, and determine an ending index number of the P-th harmonic spectrum according to the sixth frequency; Determine the effective frequency range of the P-order harmonic spectrum according to the starting index number and the ending index number of the P-order harmonic spectrum; The index number corresponding to the position of the maximum amplitude in the effective frequency range of the P-th harmonic spectrum is used as the center index number; Using a plurality of consecutive index numbers centered on the central index number as target index numbers, wherein the number of the target index numbers is less than the number of index numbers in the effective frequency range of the P-th harmonic spectrum; Performing a modulo operation on the data corresponding to the target index number, and summing the obtained moduli to obtain a first value; Performing a modulo operation on the data corresponding to all index numbers in the effective frequency range of the P-th harmonic spectrum, and summing the obtained moduli to obtain a second value; The first value is divided by the second value to obtain the confidence level of the maximum value of the P-th harmonic spectrum amplitude.

7. The method according to claim 5, characterized in that Determining the target spectrum according to the first harmonic spectrum includes: Determine a starting index number of the first harmonic spectrum according to the third frequency, and determine an ending index number of the first harmonic spectrum according to the fourth frequency; Determine the effective frequency range of the first harmonic spectrum according to the start index number and the end index number of the first harmonic spectrum; The effective frequency range of the first harmonic spectrum is used as the target spectrum.

8. The method according to claim 7, characterized in that If the confidence level of the maximum amplitude of the multiple harmonic spectrum is greater than or equal to a preset confidence level, determining the target spectrum according to the first harmonic spectrum and the multiple harmonic spectrum includes: The value corresponding to each index number within the effective frequency range of the first harmonic spectrum is superimposed with the value of the position corresponding to the index number in the multiple harmonic spectrum to obtain the target spectrum.

9. The method according to claim 8, characterized in that The multiple harmonics are P harmonics, where P is a positive integer greater than or equal to 2, and the value corresponding to each index number within the effective frequency range of the first harmonic spectrum is superimposed with the value of the index number at the corresponding position in the multiple harmonic spectrum to obtain the target spectrum, including: The value corresponding to each index number in the target spectrum is calculated according to a first formula, where the first formula is: in, is the target spectrum, is the effective frequency range of the first harmonic spectrum, are preset coefficients corresponding to the multiple harmonic spectrum, is the multiple harmonic spectrum, The value range of is from the starting index number to the ending index number of the first harmonic spectrum.

10. The method according to claim 1, characterized in that Determining the heartbeat frequency of the target detection object according to the value corresponding to the maximum heartbeat index number in the target spectrum, the sampling rate, and the preset number of frames includes: The heart rate of the target object is calculated according to a second formula, where the second formula is: in, is the heart rate of the target detection object, is the value corresponding to the maximum index number of the heartbeat in the target spectrum, is the sampling rate, is the preset frame number, and Equal to 2 raised to a positive integer power.

11. The method according to any one of claims 1 to 4, characterized in that The detection signal is a frequency modulated continuous wave signal, the frequency modulation time width of the frequency modulated continuous wave signal is T, and the process of pre-processing the echo signal received after the radar transmits the detection signal includes sampling processing, and the sampling frequency is fs , then the number of sampling points in a frame of echo signal is N = fs * T , performing fast Fourier transform on each frame of digital echo signal comprises: Each frame of digital echo signal is processed N Fast Fourier transform of a point; The process of determining the index number corresponding to the target distance point includes: The index number corresponding to the target distance point is determined according to the third formula, and the third formula is: in, Used to indicate the target distance point, used to represent the frequency modulation bandwidth of the frequency modulated continuous wave signal, Used to indicate the preset distance value. Used to express the speed of light.

12. A detection device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 11 are implemented.

13. 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 11 are implemented.

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