CN114983373B - Method for detecting human heart rate - Google Patents
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Abstract
The invention discloses a method for detecting human heart rate, which adopts time-sharing and frequency-dividing multiplexing radar waves to detect the heart rate of a target human body, adopts different echo processing methods according to different states of the target human body, sets calculation values with different weights according to different states, obtains a heart rate mean value through calculation, obtains a heart rate curve graph, stores the heart rate curve graph, obtains different monitoring heart rate curve graphs for comparison, and adjusts the value range of monitoring time T in real time; when a multi-channel real-time acquisition structure is used, a multi-channel ADC is needed to be used, in order to reduce the landing cost of the scheme, a dual-frequency MIMO radar with four antennas can be adopted.
Description
Technical Field
The invention relates to the technical field of health management, in particular to a method for detecting human heart rate.
Background
At present, the millimeter wave radar is adopted to monitor the old people, the monitoring application requirements on target people are continuously increased, but the practical application case experiments in theory and laboratories are very mature. The practical application cases in reality are few; at present, the cost of the microwave radar is continuously reduced, and more microwave radars are continuously adopted in actual scenes, such as families, old people apartments or hospitals and other places for monitoring target people for caring for old people or patients. The microwave radar is widely applied to detecting the heart rate and the respiratory rate, but the accuracy and the real-time performance of the microwave radar are greatly improved. The detection of the respiration rate is easy, and the error is extremely low. But the detection of heart rate does require more data and accuracy. A major challenge in radar heartbeat detection is the strong interference of respiration and its harmonics. Therefore, the heart-lung signals are separated by adopting the physical sign detection of the continuous wave Doppler radar, and the heart rate data is calculated by utilizing the chest wall frequency shift caused by capturing the micro-motion target. But various disturbances are generated when the object is in motion; the calculation error is increased.
Therefore, the person skilled in the art provides a method for detecting the heart rate of the human body, so as to solve the problems that the detection is not accurate enough, and false alarm or delayed alarm is easy.
The prior art radar monitoring systems for heart rate and respiratory rate are all directionally measured in a laboratory;
such systems are rarely, if ever, practical for use in the home and are not practical enough; the reason is that besides the cost problem, the accuracy and real-time performance of the system are not enough.
Disclosure of Invention
The invention aims to provide a method for detecting the heart rate of a human body, which aims to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme: a method of detecting a human heart rate, comprising the steps of:
step 1: starting a radar detection system, wherein the radar detection system is started by setting a passive identification tag or setting an infrared induction device and is used for detecting whether a target exists or not, and when the detection target does not exist in a specific area, the radar system is closed so as to save the power consumption of the system;
and 2, step: when a monitoring target exists, controlling a millimeter wave frequency modulation continuous wave radar to transmit microwaves to the target and receive echo signals, and tracking and positioning the movement direction of the target;
and 3, step 3: the method comprises the following steps of judging the motion state of a target based on an FMCW radar, carrying out biological feature recognition on the target, applying the biological feature recognition to terminal equipment, configuring a millimeter continuous wave radar on the terminal equipment, and monitoring the following information in real time:
calculating the distance information of the target millimeter-distance continuous wave radar in real time based on the echo signal;
based on the echo signals, calculating the angle information of the target chest relative to the radar in real time;
based on the echo signals, calculating the movement speed and movement direction information of the target relative to the radar in real time, wherein the movement speed and movement direction information comprises a plane movement state and a movement state in the height direction;
and 4, step 4: controlling the FMCW radar to execute corresponding calculation instructions based on echo information;
according to the filtering processing of the echo information, heart rate data are extracted, and according to the step 3: judging the motion state of a target based on an FMCW radar, wherein the states of the target are divided into at least four, namely a forward motion state and a forward static state, and a non-forward motion state and a non-forward static state; filtering echo signals in four states by adopting different methods, and respectively extracting heart rate data;
and 5: and setting different weights according to the monitoring data in different states, weighting and calculating heart rate data, and outputting a heart rate curve graph.
When the target is in a non-forward motion state, an FMCW radar adopting an MIMO antenna is started or a plurality of FMCW radars are adopted for detection, so that the accuracy of detection data of the angle change of the target is improved, echo signals in different directions are respectively obtained, and the heart rate values of different reflected waves are respectively calculated.
Transmitting a signal to a target in a time division multiplexing mode, simultaneously acquiring data by adopting a plurality of ADC modules, acquiring echo signals with different time intervals, processing the echo signals based on the echo signals with different angles, and acquiring heart rate data by calculation;
respectively acquiring echo signals of different motion states of a target, carrying out filtering processing on the echo signals according to a preset weight proportion, extracting heart rate data, and according to the step 2: the motion of the target is judged based on FMCW), different weights are extracted for four echo signals, and more accurate heart rate data are calculated;
target state data of a T time period are set according to different states of a target, the proportion of echo signals of different states is counted respectively and simultaneously according to the target state change of the T time period, and then more accurate heart rate data are calculated according to the weight value.
The T value of the statistical time period changes according to the change of the target state, when the target is in the motion state all the time and the corresponding time exceeds the previous T time period set by the system, the corresponding system statistical time period is correspondingly adjusted and prolonged, and if the statistical time period is smaller than the T time period of the previous period, the next T time period is correspondingly shortened;
meanwhile, recording a heart rate curve, counting a normal heart rate curve and an abnormal heart rate curve according to the heart rate curve, respectively comparing, analyzing heart rate changes in different states, extracting heart rate curves corresponding to different states, and calculating proportional weight;
based on preset weight, carrying out weighted calculation on the microwave signals transmitted and received by the FMCW radar to obtain an average value, carrying out fusion calculation to obtain a heart rate value of the target user, and meanwhile, counting a heart rate curve graph;
the weight is calculated and adjusted according to the comparison of the real-time heart rate curve and a pre-stored heart rate curve, the time interval of the current state is obtained, each time interval is divided into the superposition of each instantaneous value, and the instantaneous weight value of the current time is obtained; calculating the product of the instantaneous heart rate value of the current time point and the corresponding weight value; judging whether the product is larger than a preset value; if so, outputting the instantaneous heart rate value as an output heart rate value of the current time point; if not, calculating the product of the weight values corresponding to the historical time points, and the weighted sum of the instantaneous heart rate value of the current time point and the product of the weight values; judging whether the weighted sum is larger than a preset value or not, if so, calculating the ratio of the weighted sum to the weighted sum of the time points; and outputting the ratio as an output heart rate value of the current time point.
The FMCW radar adopts a human body action recognition method based on a dual-band FMCW radar, and the number of the FMCW radar of the MIMO antenna is four; and processing the echo signal data, extracting the characteristics and fusing the characteristics to obtain a heart rate value, wherein the number of the receiving and filtering ADCs is twice of the number of the MIMO antennas.
The MIMO antenna adopts a gap waveguide structure, the maximum distance between array elements of an antenna matrix is set to be half wavelength, and a TE10 mode is adopted as a transmission mode.
The state of the target is divided into a static state and a motion state, the motion state is divided into a low-speed motion state and a high-speed motion state, echo signals are divided into a plurality of data sections according to the state of the target, different filtering and algorithms are respectively adopted to calculate and obtain the heart rate, the echo signals of all the states are superposed according to instantaneous data to obtain the instantaneous average heart rate, and finally the average heart rate value is obtained through weighting.
Compared with the prior art, the invention has the beneficial effects that: according to the invention, time-sharing and frequency-dividing multiplexing radar waves are adopted to detect the heart rate of a target human body, different echo processing methods are adopted according to different states of the target human body, calculation values with different weights are set according to different states (weighted by time periods), a heart rate mean value is obtained through calculation, a heart rate curve graph is obtained and stored, different monitoring heart rate curve graphs are obtained for comparison, the value range of the monitoring time T is adjusted in real time, an FMCW radar of an MIMO antenna is adopted, and meanwhile, in order to obtain more accurate echo signal data, a multi-channel real-time acquisition method can be adopted, or a mixed mode of the two can be used; when using the structure of multichannel real-time collection, need use multichannel ADC (although multichannel ADC cost has increased, the accuracy and the efficiency of monitoring have improved, and it is more accurate to the target monitoring in the motion), in order to reduce the cost of falling to the ground of scheme, can take the MIMO radar of dual-frenquency, four antenna quantity.
The scheme of the invention simultaneously avoids the privacy problem of detection personnel. The respiratory rate is more accurately acquired by adopting an innovative method of frequency modulation continuous wave radar.
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FIG. 1 is a schematic flow chart of the detection method of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to fig. 1 in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In order to achieve the purpose, the invention provides the following technical scheme: the invention aims to provide a method for detecting the heart rate of a human body, which aims to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme: a method of detecting a human heart rate, comprising the steps of: step 1: starting a radar detection system, wherein the radar detection system is started by setting a passive identification tag or setting an infrared induction device for detecting the existence of a target, and the radar system is closed when the detection target does not exist in a specific area so as to save the power consumption of the system;
step 2: when a monitoring target is identified, controlling the radar to transmit microwaves to the target and receive echo signals, and tracking and positioning the movement direction of the target;
and 3, step 3: judging the motion state of a target based on an FMCW radar, and carrying out biological feature recognition on the target, wherein the frequency modulation continuous wave radar adopts a millimeter wave radar and monitors the following information in real time:
calculating the distance information of the target millimeter wave continuous wave radar in real time based on the echo signal;
based on the echo signals, calculating the angle information of the target chest relative to the radar in real time;
calculating the movement speed and movement direction information of the target relative to the radar in real time based on the echo signals; a motion state including a planar motion state and a height direction;
and 4, step 4: controlling the FMCW radar to execute corresponding calculation instructions based on echo information;
filtering the echo information, extracting heart rate data, judging the motion state of the target according to the step 2, and dividing the state of the target into at least four states, namely a forward motion state and a forward static state, and a non-forward motion state and a non-forward static state; filtering echo signals in four states by adopting different methods, and respectively extracting heart rate data;
when the target is in forward or non-forward static state relative to the radar signal, the detection signal of the FMCW radar is adopted, and then the single-frame intermediate frequency signal is processed;
when the target is in a motion state, the detection signal of the FMCW radar adopts a double frequency band;
when the target is in a non-forward motion state relative to the radar, starting an FMCW radar of the MIMO antenna to improve the accuracy of detection data of the angle change of the target, starting to respectively acquire echo signals of different directions, and respectively calculating heart rate values of different reflected waves; in order to reduce the cost, a four-antenna MIMO antenna radar is adopted; the method is only the problem of setting the number of the antennas, and the principle of obtaining low-cost high-precision monitoring data is taken as a principle in the practical application process.
And 5: setting different weights according to monitoring data in different states, calculating more accurate heart rate data, and outputting a heart rate curve graph;
when the target is in a non-forward motion state relative to the radar, transmitting a signal to the target in a time division multiplexing mode, acquiring data by adopting multiple ADC (analog to digital converter) modules, acquiring echo signals of different time intervals, processing the echo signals based on the echo signals of different angles, and acquiring heart rate data by calculation; especially when detecting multiple targets, biometric identification of the targets is used to distinguish between different targets.
Based on the fact that the typical range of the respiratory frequency is 0.1 Hz-0.5 Hz and the heart rate range is 1 Hz-3 Hz, the echo signals are filtered and denoised, and heart rate signal data are separated;
the echo classification is carried out by distinguishing the motion states of the targets according to the echoes, different targets can be distinguished according to the biological feature identification of the targets, and more state classifications are distinguished from different motion states of the targets.
The radar echo classification can also be based on the fuzzy logic technology, and the radar echo classification is classified according to specific scenes in different environments, for example, outdoors, in rainy or fog-dense environments, and the result of echo data processing of classification calculation based on the radar echo of the fuzzy logic technology is more accurate; after different classifications, the detection and echo processing algorithms in different states are different, each algorithm selects different feature quantity combinations and distributes weights, and then weighted average is carried out on each selected feature quantity; acquiring an accurate heart rate value, acquiring a heart rate curve, and comparing historical data, namely heart rate curve graphs in different environments to obtain body parameters of a target in different environments; the method can be used for statistical analysis of target human body health data under different specific environmental conditions and used as diagnosis of doctors or target health reference.
Presetting a weight proportion, carrying out filtering processing on the echo signals, extracting heart rate data, and according to the step 2: judging the motion state of a target based on FMCW, judging to extract different weights for four echo signals, and calculating more accurate heart rate data; the average value is obtained by averaging the weights, when the motion state of the target has large change, the evaluation weight is adjusted according to the duration time of a single state in different states,
target state data (for example, data of 60s per minute) of a T time period are set according to different states of a target, the proportions of echo signals of different states are respectively counted simultaneously according to the target state change of the T time period, and then more accurate heart rate data are calculated according to a weighted value; in practical application, the time T is generally between 1 minute and 10 minutes, and the like, and actually varies for different time periods.
The T value of the statistical time period changes along with the change of the target state, and when the target is in a motion state all the time and the corresponding time exceeds the T time period set by the system, the corresponding system detection statistical time period is correspondingly adjusted and prolonged;
meanwhile, recording a heart rate curve, counting a normal heart rate curve and an abnormal heart rate curve according to the heart rate curve, respectively comparing, analyzing the heart rate changes in different states, extracting heart rate curves corresponding to different states, and calculating proportion weight;
based on preset weight, carrying out weighted calculation on the microwave signals transmitted and received by the FMCW radar to obtain an average value, carrying out fusion calculation to obtain a heart rate value of the target user, and meanwhile, counting a heart rate curve graph;
the weight value is calculated and adjusted according to the comparison of the real-time heart rate curve and a pre-stored heart rate curve;
the heart rate detection calculation weight proportion is related to the time of each state, the time interval of the current state is obtained, each time interval is divided into the superposition of each instantaneous value, and the instantaneous weight value of the current time is obtained; calculating the product of the instantaneous heart rate value of the current time point and the corresponding weight value; judging whether the product is larger than a preset value; if so, outputting the instantaneous heart rate value as an output heart rate value of the current time point; if not, calculating the product of the weight values corresponding to the historical time points, and the weighted sum of the product of the instantaneous heart rate value of the current time point and the product of the weight values; judging whether the weighted sum is larger than a preset value or not, if so, calculating the ratio of the weighted sum to the weighted sum of the time points; and outputting the ratio as an output heart rate value of the current time point. The heart rate value output to the user is accurate, and the use experience of the user is enhanced.
When the measured instantaneous speed value and acceleration value are compared with the instantaneous frequency, the direction problem needs to be considered in the echo signal results obtained when the target moves away from the radar and close to the radar, the echo signal results are matched with the direction of the speed and the direction of the acceleration, and the instantaneous heart rate is obtained in the relation solution of the instantaneous speed and the frequency value (the instantaneous frequency can obtain the instantaneous time). The instantaneous heart rate value of the current time point is obtained through a radar, the frequency difference of an echo is collected, the time difference between the current time point and the previous time point can be calculated, the reciprocal of the time difference is calculated, the reciprocal is used as the instantaneous heart rate value of the current time point, and the formula is calculated as follows:
h is the instantaneous heart rate value, t0 is the current time point, and t1 is the adjacent previous time point of t 0. And then a weighting process. The invention focuses on the solution to the problem, and it is not explained here by mathematically detailed calculations.
The FMCW radar adopts a human body action recognition method based on a dual-band FMCW radar, and the number of the FMCW radar of the MIMO antenna is four; and processing the echo signal data, extracting the characteristics and fusing the characteristics to obtain the heart rate value. Based on the consideration of cost, the continuous wave can adopt double frequency bands, the FMCW radar of the MIMO antenna adopts the MIMO radar with 4 antennas, and the acquisition of accurate monitoring heart rate data can be realized. When the multi-target monitoring is performed, a time division multiplexing mode is adopted to transmit signals to the target, meanwhile, a multi-channel ADC module is adopted to collect data, echo signals of different time intervals are obtained, and the number of the ADC for receiving and filtering is twice that of the MIMO antennas based on the consideration of cost and calculation; and processing echo signals based on the echo signals at different angles, and acquiring heart rate data through calculation.
In specific implementation, the microwave radar of the MIMO antenna adopts a gap waveguide structure, the maximum distance between antenna matrix array elements is set to be half a wavelength, and a main transmission mode is a TE10 mode. It should be noted that the gap waveguide in the scheme of the present invention is different from the rectangular waveguide, and the gap waveguide needs two rows of metal electromagnetic band gap structures, which can effectively simulate the leakage of electromagnetic waves and is specially designed for the millimeter wave radar of the MIMO antenna.
The principle that a target moves, the breathing rate is detected by a radar, namely micro movement, namely breathing and heartbeat movement, filtering is carried out, the breathing movement and the heartbeat movement are calculated in different amplitudes, interference items are filtered, when the target moves, the interference items to the radar are increased due to the change of relative movement and angles, and therefore when the target moves, the detection of the target in motion is different from the detection data processing of the target in rest, and according to the detection precision of an FMCW radar of an MIMO antenna, algorithm analysis is carried out on the detection data in multi-target movement, and the data are separated to obtain a plurality of accurate heart rate data; when the device is used in environments such as families or hospitals, detection targets are all specific targets, at the moment, the detection targets are distinguished according to biological characteristics of the targets, real-time detection data are separated in real time, including data instant acquisition and instant separation of time and space (including all states), and heart rate data are obtained through a matched algorithm.
The following innovative algorithms are proposed on the method for acquiring the heart rate of the human body by utilizing the millimeter wave radar in the system algorithm, and the displacement and frequency parameters of the heartbeat and the respiration of the common adult are as follows:
now, the radar detects the phase change of FMCW radar signals in a specific range difference caused by the small vibration of the target, so that it is proposed to acquire the vital sign signals based on the following method, and the frequency modulation continuous wave radar is usually adopted according to the following specific method:
1) Performing fast Fourier transform on the ADC data to obtain a variation range curve;
the method comprises the following specific steps: in order to further enhance the heart rate signal and eliminate the phase drift in the echo signal, the waveform after phase expansion is subjected to differential processing; the phase difference is realized by continuously subtracting the expanded phase of the current sampling point from the previous sampling point, as the respiratory frequency is usually within the range of 0.1-0.6 Hz, the heartbeat frequency is usually within the range of 0.8-3.3 Hz, an IIR digital band-pass filter is adopted to preliminarily separate the respiratory signal and the heartbeat signal, fast Fourier transform is carried out on the two groups of signals, the main frequency component can be judged according to the maximum value in the amplitude-frequency characteristic curve, and then the respiratory rate and the heart rate are converted, and the respiratory rate curve is extracted for next processing; (here the same approach can be taken for processing the respiration rate curve);
2) The distance range of the target can be determined through the approximate position relation between the radar and the human body, and the range difference corresponding to the target is obtained by searching the maximum value in the range;
3) Extracting the phase at the target interval;
4) Repeating the three stages of the steps (1), (2) and (3) for circulation, wherein the frame period is 50ms, namely, extracting the phase of the target once in each frame period, if the radial distance between the target and the distance changes, obtaining the range difference at the moment according to a range difference tracking algorithm, then extracting the phase, and transmitting N frames in a circulating manner, so that the value change of the phase of the target along with the frame number can be obtained, the relation between the target phase and the time can also be regarded as the relation between the target phase and the time, and the relation is recorded as a vibration signal
5) Phase unwrapping, since the phase values are between [ -pi, pi ], and we need to unwrap to obtain the actual displacement curve. Thus whenever the phase difference between successive values is greater/less than + -pi, phase unwrapping is performed by subtracting 2 pi from the phase;
6) And performing a phase difference operation on the unwrapped phases by subtracting the continuous phase values. This helps to enhance the heartbeat signal and eliminate any phase drift;
7) Filtering the phase value by using a band-pass filter according to different heartbeat and respiratory frequencies so as to distinguish;
8) Performing range estimation, namely performing fast Fourier transform on the phase signal, and acquiring corresponding heartbeat frequency within N frames (4 = < N = < 10) according to the peak value and harmonic characteristics thereof;
9) Judging, recording the heartbeat frequency within a period of time, judging the heartbeat frequency at the moment according to different confidence indexes, and outputting the relation of the change of the respiratory frequency along with the time;
10 After the phase is filtered, the sample is divided, a threshold value is set to judge whether the variation range of the heart rate is met, and data in a stable state is selected for the next estimation; finally, a heartbeat frequency curve is obtained.
The purpose here is to reduce the influence of the relative position shift of the human body on the heart rate measurement. Because the measurement of the heart rate is based on the phase change caused by the distance difference generated by the micro motion of the systole and diastole, according to the microwave Doppler principle, when the human body greatly swings, the accuracy of the human body is influenced; the method is similar to the method for calculating the respiratory frequency, and finally the vital sign signals are obtained.
The working principle of the invention is as follows: in the scheme of the invention, an innovative radar detection method and an innovative radar echo data processing method are adopted, so that the detection of the vital signs of the human body is more accurate.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered as the technical solutions and the inventive concepts of the present invention within the technical scope of the present invention.
Claims (6)
1. A method of detecting a human heart rate, comprising the steps of:
step 1: starting a radar detection system, wherein the radar detection system is started by setting a passive identification tag or setting an infrared induction device and is used for detecting whether a target exists or not, and when the detection target does not exist in a specific area, the radar system is closed so as to save the power consumption of the system;
and 2, step: when a monitoring target is identified, controlling a frequency modulation continuous wave radar of the millimeter waves to transmit microwaves to the target and receive echo signals, and tracking and positioning the movement direction of the target;
and step 3: the method comprises the following steps of judging the motion state of a target based on an FMCW radar, carrying out biological feature recognition on the target, applying the biological feature recognition to terminal equipment, configuring a millimeter continuous wave radar on the terminal equipment, and monitoring the following information in real time:
calculating the distance information of the target distance millimeter continuous wave radar in real time based on the echo signal;
based on the echo signals, calculating the angle information of the target chest relative to the radar in real time;
based on the echo signals, calculating the movement speed and movement direction information of the target relative to the radar in real time, wherein the movement speed and movement direction information comprises a plane movement state and a movement state in the height direction;
and 4, step 4: controlling the FMCW radar to execute corresponding calculation instructions based on echo information;
according to the filtering processing of the echo information, heart rate data are extracted, and according to the step 3: judging the motion state of a target based on an FMCW radar, wherein the states of the target are divided into at least four, namely a forward motion state and a forward static state, and a non-forward motion state and a non-forward static state; filtering echo signals in four states by adopting different methods, and respectively extracting heart rate data;
and 5: setting different weights according to monitoring data in different states, weighting and calculating heart rate data, and outputting a heart rate curve graph;
when the target is in a non-forward motion state, starting an FMCW radar adopting an MIMO antenna or detecting by adopting a plurality of FMCW radars so as to improve the accuracy of detection data of the angle change of the target, respectively acquiring echo signals in different directions, and respectively calculating the heart rate values of different reflected waves;
transmitting a signal to a target in a time division multiplexing mode, simultaneously acquiring data by adopting a plurality of ADC modules, acquiring echo signals with different time intervals, processing the echo signals based on the echo signals with different angles, and acquiring heart rate data by calculation;
respectively acquiring echo signals of different motion states of a target, carrying out filtering processing on the echo signals according to a preset weight proportion, extracting heart rate data, and according to the step 2: judging the motion state of a target based on FMCW, judging to extract different weights for four echo signals, and calculating more accurate heart rate data;
target state data of a T time period are set according to different states of a target, the proportion of echo signals of different states is counted respectively and simultaneously according to the target state change of the T time period, and then more accurate heart rate data are calculated according to the weight value.
2. A method of detecting a human heart rate as claimed in claim 1, wherein: the T value of the statistical time period changes according to the change of the target state, when the target is in the motion state all the time and the corresponding time exceeds the previous T time period set by the system, the corresponding system statistical time period is correspondingly adjusted and prolonged, and if the statistical time period is smaller than the T time period of the previous period, the next T time period is correspondingly shortened;
and meanwhile, recording a heart rate curve, counting a normal heart rate curve and an abnormal heart rate curve according to the heart rate curve, respectively comparing, analyzing heart rate changes in different states, extracting heart rate curves corresponding to different states, and calculating proportion weight.
3. A method of detecting a human heart rate as claimed in claim 2, wherein: based on preset weight, carrying out weighted calculation on the transmitted and received microwave signals of the FMCW radar to obtain an average value, carrying out fusion calculation to obtain a heart rate value of the target user, and meanwhile, counting a heart rate curve graph;
the weight is calculated and adjusted according to the comparison of the real-time heart rate curve and the pre-stored heart rate curve, the time interval of the current state is obtained, each time interval is divided into the superposition of all instantaneous values, and the instantaneous weight value of the current time is obtained; calculating the product of the instantaneous heart rate value of the current time point and the corresponding weight value; judging whether the product is larger than a preset value or not; if so, outputting the instantaneous heart rate value as an output heart rate value of the current time point; if not, calculating the product of the weight values corresponding to the historical time points, and the weighted sum of the instantaneous heart rate value of the current time point and the product of the weight values; judging whether the weighted sum is larger than a preset value or not, if so, calculating the ratio of the weighted sum to the weighted sum of the time points; and outputting the ratio as an output heart rate value of the current time point.
4. A method of detecting a human heart rate as claimed in claim 2 or 3, wherein:
the FMCW radar adopts a human body action recognition method based on a dual-band FMCW radar, and the number of the FMCW radar of the MIMO antenna is four; and processing the echo signal data, extracting the characteristics and fusing the characteristics to obtain a heart rate value, wherein the number of the receiving and filtering ADCs is twice of the number of the MIMO antennas.
5. A method of detecting a human heart rate as claimed in claim 4, wherein: the MIMO antenna adopts a gap waveguide structure, the distance between antenna matrix array elements is set to be half wavelength at most, and a TE10 mode is adopted as a transmission mode.
6. The method for detecting the heart rate of the human body as claimed in claim 4, wherein:
the state of the target is divided into a static state and a motion state, the motion state is divided into a low-speed motion state and a high-speed motion state, echo signals are divided into a plurality of data sections according to the state of the target, different filtering and algorithms are respectively adopted to calculate and obtain the heart rate, the echo signals of all the states are superposed according to instantaneous data to obtain the instantaneous average heart rate, and finally the average heart rate value is obtained through weighting.
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