CN114983373A - 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 the like 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 heart rate detection does require more data and accuracy. A major challenge in radar heartbeat detection is the strong interference of breathing and its harmonics. Therefore, continuous wave Doppler radar sign detection is adopted to separate cardiopulmonary signals, and heart rate data are calculated by capturing chest wall frequency shift caused by a micro-motion target. But various disturbances are generated when the target 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 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 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, identifying biological characteristics of the target, applying the target to a terminal device, configuring the millimeter continuous wave radar on the terminal device, 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;
calculating the movement speed and movement direction information of the target relative to the radar in real time based on the echo signals, 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 is 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, the FMCW radar (or a plurality of FMCW radars) adopting the MIMO antenna is started to detect so as to improve the accuracy of the detection data of the angle change of the target, echo signals of 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 of different time intervals, processing the echo signals based on the echo signals of 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 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.
The T value of the statistical time period changes according to the change of the target state, when the target is always in a moving state 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;
simultaneously 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 a proportional weight;
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 calculates and adjusts a weight value according to the comparison of the real-time heart rate curve and a pre-stored heart rate curve, time intervals of the current state are obtained, each time interval is divided into superposition of each instantaneous value, and an 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 and the weight value of the current time point; 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, feature extraction and feature fusion are carried out on the echo signal data to obtain a heart rate value, and 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 distance between antenna matrix array elements is maximally set to be half wavelength, and a transmission mode adopts a TE10 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, a time-sharing and frequency-dividing multiplex radar wave is 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, monitoring heart rate curve graphs of different times are obtained for comparison, the value range of 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 a multi-channel real-time acquisition structure is used, a multi-channel ADC (although the cost of the multi-channel ADC is increased, the accuracy and the efficiency of monitoring are improved, and targets in motion are monitored more accurately) is needed, and in order to reduce the ground cost of a scheme, a dual-frequency MIMO radar with four antennas can be adopted.
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 of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to 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 in the scheme of the invention so as 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 step 3: judging the motion state of a target based on an FMCW radar, and identifying biological characteristics of 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, a forward static state, 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 direction or non-forward direction static state relative to the radar signal, adopting a detection signal of an FMCW radar, and processing a single-frame intermediate frequency signal;
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 a problem of setting the number of the antennas, and the principle of acquiring 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 a plurality of ADC 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 through 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 characteristic quantities to combine and distribute weight, and then weighted average is carried out on each selected characteristic 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 the target in different environments; the method can be used for statistical analysis of the physical health data of the target human body under different specific environmental conditions and used as a doctor diagnosis or target health reference.
Presetting a weight proportion, carrying out filtering processing on the echo signals, extracting heart rate data, and carrying out filtering processing 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 is changed greatly, 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 for one minute) in a T time period are set according to different states of a target, the proportions of echo signals in different states are respectively counted simultaneously according to the target state change in the T time period, and then more accurate heart rate data are calculated according to a weight 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;
simultaneously 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 a proportional weight;
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 value is calculated and adjusted according to the comparison of the real-time heart rate curve and a pre-stored heart rate curve;
the proportion of the heart rate detection calculation weight 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 value obtains the instantaneous weight value of the current time; 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 heart rate value output to the user by the heart rate detection 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 as the result of the echo signals obtained when the target moves away from the radar and close to the radar, the instantaneous heart rate is obtained in the relation solution of the instantaneous speed and the instantaneous frequency value (the instantaneous frequency can obtain the instantaneous time) by matching with the direction of the speed and the direction of the acceleration. 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 calculation is as the formula:
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 weighted. The invention is mainly directed to solving the problem, and the mathematical detailed calculation is not described here.
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 a dual-frequency band, 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 plurality of paths of ADC modules are adopted to collect data, echo signals of different time gaps are obtained, and the number of the ADC modules 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 the antenna array elements is set to be half wavelength, and the 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 of detecting a target by a radar is that the target moves, the detection of the respiratory rate is micro movement, namely movement of respiration and heartbeat, filtering is carried out, the respiratory 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, detection is different from the detection data processing of the target which is static, and according to the detection accuracy of an FMCW radar of an MIMO antenna, the data are subjected to algorithm analysis of the detection data in the multi-target movement, and the data are separated to obtain a plurality of accurate heart rate data; when the system 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, the data are instantly collected and instantly separated in 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:
| vital signs | Frequency of | Amplitude of vibration | Amplitude of vibration |
| Respiration rate (adult) | 0.1-0.5Hz | ～1-12mm | ～0.1-0.5mm |
| Heart rate (adult) | 0.8-2.0Hz | ～0.1-0.5mm | ～0.01-0.2mm |
Now, the radar detects the phase change of the FMCW radar signal which is poor in a specific range and caused by the micro-vibration of the target, so that the vital sign signal is proposed to be acquired 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 expansion phase of the current sampling point from the previous sampling point, the respiratory frequency is usually within the range of 0.1-0.6 Hz, the heart frequency hopping rate is usually within the range of 0.8-3.3 Hz, an IIR digital band-pass filter is adopted to preliminarily separate respiratory signals and heartbeat signals, 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 method can acquire the respiration rate curve for processing);
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 steps, 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 according to the range difference tracking algorithm, then extracting the phase, circularly transmitting N frames, namely obtaining the value change of the phase of the target along with the frame number, and also considering the relation between the target phase and the time to be 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. So 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 successive 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 the difference of the heartbeat and the respiratory frequency 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 features 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 respiratory frequency changing 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, obtaining the heartbeat frequency curve.
The aim here is to reduce the influence of the relative position shift of the human body on the heart rate measurement. Because the heart rate is measured 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 to be within the scope of the present invention, and the technical solutions and the inventive concepts of the present invention are equivalent to or changed within the technical scope of the present invention.
Claims (10)
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 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 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 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.
2. A method of detecting a human heart rate as claimed in claim 1, wherein:
when the target is in a non-forward motion state, the FMCW radar (or a plurality of FMCW radars) adopting the MIMO antenna is started to detect so as to improve the accuracy of the detection data of the angle change of the target, echo signals in different directions are respectively obtained, and the heart rate values of different reflected waves are respectively calculated.
3. A method of detecting a human heart rate as claimed in claim 2, wherein: the method comprises the steps of adopting a time division multiplexing mode to transmit signals to a target, simultaneously adopting multiple ADC modules to collect data, obtaining echo signals of different time intervals, carrying out echo signal processing based on the echo signals of different angles, and obtaining heart rate data through calculation.
4. A method of detecting a human heart rate as claimed in claim 3, wherein: 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.
5. The method for detecting the heart rate of the human body as claimed in claim 4, wherein: 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.
6. The method for detecting the heart rate of the human body as claimed in claim 5, 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.
7. The method for detecting the heart rate of the human body as claimed in claim 6, wherein: 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.
8. A method of detecting a human heart rate as claimed in claim 6 or 7, 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, feature extraction and feature fusion are carried out on the echo signal data to obtain a heart rate value, and the number of the receiving and filtering ADCs is twice of the number of the MIMO antennas.
9. A method of detecting a human heart rate as claimed in claim 8, wherein: 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.
10. A method of detecting a human heart rate as claimed in claim 8, 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 adopted to calculate and obtain the heart rate, the echo signals of all the states are superposed according to instantaneous data to obtain an instantaneous average heart rate, and finally the average heart rate is obtained through weighting.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117179716A (en) * | 2023-09-13 | 2023-12-08 | 深圳市震有智联科技有限公司 | Vital sign detection method and system based on radar |
| CN117958792A (en) * | 2023-09-26 | 2024-05-03 | 延边大学 | Self-adaptive Kalman filtering respiratory frequency calculation method based on mobile windowing method |
| CN117179716B (en) * | 2023-09-13 | 2024-06-28 | 深圳市震有智联科技有限公司 | Vital sign detection method and system based on radar |
Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080082003A1 (en) * | 2006-08-28 | 2008-04-03 | Shenzhen Mindray Bio-Medical Electronics Co., Ltd. | Method and apparatus for detecting respiratory rate |
| US20100130873A1 (en) * | 2008-04-03 | 2010-05-27 | Kai Sensors, Inc. | Non-contact physiologic motion sensors and methods for use |
| CN106175723A (en) * | 2016-06-27 | 2016-12-07 | 中国人民解放军第三军医大学第附属医院 | A kind of many life monitoring systems based on FMCW wideband radar |
| CN106546979A (en) * | 2016-10-08 | 2017-03-29 | 中国人民解放军第四军医大学 | It is a kind of that detection method is strengthened based on the ultra-wide spectrum radar type human body respiration that multi-antenna data merges |
| KR20180007563A (en) * | 2016-07-13 | 2018-01-23 | 비아이에스웍스 주식회사 | Apparatus and method for measuring heart rate through non-contact |
| CN109521422A (en) * | 2018-10-15 | 2019-03-26 | 中国人民解放军第四军医大学 | A kind of multiple target life detection method and detection radar based on radar signal |
| CN110192850A (en) * | 2019-05-31 | 2019-09-03 | 湖南省顺鸿智能科技有限公司 | Extracting method and system based on heartbeat signal under radar return strong noise background |
| CN110448290A (en) * | 2019-08-19 | 2019-11-15 | 中电科仪器仪表有限公司 | A kind of remote personnel's heart rate detection method, apparatus and system based on Terahertz through-wall radar |
| CN110477895A (en) * | 2019-07-24 | 2019-11-22 | 苏州国科医疗科技发展有限公司 | The continuous method for measuring heart rate of multiple light courcess detector based on volumetric blood wave |
| JP2019213772A (en) * | 2018-06-14 | 2019-12-19 | 公立大学法人公立諏訪東京理科大学 | Heart beat measurement method and heart beat measurement device |
| CN111938623A (en) * | 2020-08-25 | 2020-11-17 | 成都宋元科技有限公司 | Respiratory heart rate dynamic measurement method and device based on UWB positioning guidance |
| WO2021015559A1 (en) * | 2019-07-25 | 2021-01-28 | (주)비타 | Position tracking and respiration pattern measuring method and apparatus using fmcw radar |
| US20210208266A1 (en) * | 2018-05-18 | 2021-07-08 | Polyvalor, Limited Partnershi | Fundamental-and-harmonics multi-frequency doppler radar system with radar motion cancellation |
| CN113925476A (en) * | 2021-10-18 | 2022-01-14 | 谢俊 | Intelligent system for detecting human heart rate and detection method thereof |
| JP2022012646A (en) * | 2020-07-02 | 2022-01-17 | 日本無線株式会社 | Respiration and heart rate measuring apparatus and respiration and heart rate measuring program |
| CN114305355A (en) * | 2022-01-05 | 2022-04-12 | 北京科技大学 | Respiration and heartbeat detection method, system and device based on millimeter wave radar |
| WO2022095869A1 (en) * | 2020-11-04 | 2022-05-12 | 蓬托森思股份有限公司 | Contactless breathing or heartbeat detection method |
| WO2022104868A1 (en) * | 2020-11-19 | 2022-05-27 | 华中师范大学 | Millimeter wave radar-based non-contact real-time vital sign monitoring system and method |
-
2022
- 2022-06-02 CN CN202210624095.9A patent/CN114983373B/en active Active
Patent Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080082003A1 (en) * | 2006-08-28 | 2008-04-03 | Shenzhen Mindray Bio-Medical Electronics Co., Ltd. | Method and apparatus for detecting respiratory rate |
| US20100130873A1 (en) * | 2008-04-03 | 2010-05-27 | Kai Sensors, Inc. | Non-contact physiologic motion sensors and methods for use |
| CN106175723A (en) * | 2016-06-27 | 2016-12-07 | 中国人民解放军第三军医大学第附属医院 | A kind of many life monitoring systems based on FMCW wideband radar |
| KR20180007563A (en) * | 2016-07-13 | 2018-01-23 | 비아이에스웍스 주식회사 | Apparatus and method for measuring heart rate through non-contact |
| CN106546979A (en) * | 2016-10-08 | 2017-03-29 | 中国人民解放军第四军医大学 | It is a kind of that detection method is strengthened based on the ultra-wide spectrum radar type human body respiration that multi-antenna data merges |
| US20210208266A1 (en) * | 2018-05-18 | 2021-07-08 | Polyvalor, Limited Partnershi | Fundamental-and-harmonics multi-frequency doppler radar system with radar motion cancellation |
| JP2019213772A (en) * | 2018-06-14 | 2019-12-19 | 公立大学法人公立諏訪東京理科大学 | Heart beat measurement method and heart beat measurement device |
| CN109521422A (en) * | 2018-10-15 | 2019-03-26 | 中国人民解放军第四军医大学 | A kind of multiple target life detection method and detection radar based on radar signal |
| CN110192850A (en) * | 2019-05-31 | 2019-09-03 | 湖南省顺鸿智能科技有限公司 | Extracting method and system based on heartbeat signal under radar return strong noise background |
| CN110477895A (en) * | 2019-07-24 | 2019-11-22 | 苏州国科医疗科技发展有限公司 | The continuous method for measuring heart rate of multiple light courcess detector based on volumetric blood wave |
| WO2021015559A1 (en) * | 2019-07-25 | 2021-01-28 | (주)비타 | Position tracking and respiration pattern measuring method and apparatus using fmcw radar |
| CN110448290A (en) * | 2019-08-19 | 2019-11-15 | 中电科仪器仪表有限公司 | A kind of remote personnel's heart rate detection method, apparatus and system based on Terahertz through-wall radar |
| JP2022012646A (en) * | 2020-07-02 | 2022-01-17 | 日本無線株式会社 | Respiration and heart rate measuring apparatus and respiration and heart rate measuring program |
| CN111938623A (en) * | 2020-08-25 | 2020-11-17 | 成都宋元科技有限公司 | Respiratory heart rate dynamic measurement method and device based on UWB positioning guidance |
| WO2022095869A1 (en) * | 2020-11-04 | 2022-05-12 | 蓬托森思股份有限公司 | Contactless breathing or heartbeat detection method |
| WO2022104868A1 (en) * | 2020-11-19 | 2022-05-27 | 华中师范大学 | Millimeter wave radar-based non-contact real-time vital sign monitoring system and method |
| CN113925476A (en) * | 2021-10-18 | 2022-01-14 | 谢俊 | Intelligent system for detecting human heart rate and detection method thereof |
| CN114305355A (en) * | 2022-01-05 | 2022-04-12 | 北京科技大学 | Respiration and heartbeat detection method, system and device based on millimeter wave radar |
Non-Patent Citations (4)
| Title |
|---|
| KWANG JIN LEE，等: "Tracking Driver\'s Heart Rate by Continuous-Wave Doppler Radar" * |
| PENGWEI ZHENG，等: "Second Harmonic Weighted Reconstruction for Non-Contact Monitoring Heart Rate" * |
| QIWEI LIU，等: "Non-Contact Non-Invasive Heart and Respiration Rates Monitoring with MIMO Radar Sensing" * |
| 胡巍: "基于多普勒雷达的非接触式生命体征检测技术研究" * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117179716A (en) * | 2023-09-13 | 2023-12-08 | 深圳市震有智联科技有限公司 | Vital sign detection method and system based on radar |
| CN117179716B (en) * | 2023-09-13 | 2024-06-28 | 深圳市震有智联科技有限公司 | Vital sign detection method and system based on radar |
| CN117958792A (en) * | 2023-09-26 | 2024-05-03 | 延边大学 | Self-adaptive Kalman filtering respiratory frequency calculation method based on mobile windowing method |
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