CN112617748B

CN112617748B - Method and system for processing sign data based on frequency modulation continuous wave radar

Info

Publication number: CN112617748B
Application number: CN202011203014.5A
Authority: CN
Inventors: 郑春弟; 解春维; 陈荟慧; 王爱国; 谢经顺
Original assignee: Foshan University
Current assignee: Foshan University
Priority date: 2020-11-02
Filing date: 2020-11-02
Publication date: 2022-04-26
Anticipated expiration: 2040-11-02
Also published as: CN112617748A

Abstract

The invention relates to the technical field of signal processing, in particular to a sign data processing method and a system based on a frequency modulation continuous wave radar, wherein the method comprises the steps of firstly adopting the frequency modulation continuous wave radar to transmit electromagnetic wave signals to a human body to be detected so as to detect the mechanical motion signals of the chest wall of the human body to be detected and receive returned echo signals; then sampling the echo signals, processing the sampled echo signals by using a multiple signal classification algorithm to obtain a high-resolution range profile, and extracting respiratory signals and heartbeat signals according to the high-resolution range profile; finally, physical sign data of the human body to be detected are determined according to the respiration signals and the heartbeat signals, wherein the physical sign data comprise respiration rate, real-time respiration rate variability, heart rate and real-time heart rate variability; the invention can detect the vital signs of the human body to be detected more conveniently and more efficiently, realizes the high-precision real-time extraction of the respiration rate, the heart rate, the variability of the respiration rate and the variability of the heart rate, and provides accurate and clear sign data.

Description

Method and system for processing sign data based on frequency modulation continuous wave radar

Technical Field

The invention relates to the technical field of signal processing, in particular to a sign data processing method and system based on a frequency modulation continuous wave radar.

Background

Traditionally, the monitoring of physical sign data such as breathing and heartbeat is accomplished to using multi-functional monitor, but need take off the clothes and tie electrode paster or sensor on the person when its use, can't satisfy the demand of the large-traffic personnel screening in public place. In addition, the physical sign data detected by the traditional monitoring equipment is not accurate and clear enough, and real-time high-precision detection cannot be achieved.

Disclosure of Invention

The invention provides a sign data processing method and system based on frequency modulation continuous wave radar, which aim to solve one or more technical problems in the prior art and at least provide a beneficial selection or creation condition.

In order to achieve the purpose, the invention provides the following technical scheme:

a sign data processing method based on a frequency modulation continuous wave radar comprises the following steps:

s100, transmitting an electromagnetic wave signal to a human body to be detected by adopting a frequency modulation continuous wave radar so as to detect a chest wall mechanical motion signal of the human body to be detected and receive a returned echo signal;

s200, sampling the echo signals, processing the sampled echo signals by using a multiple signal classification algorithm to obtain a high-resolution range profile, and extracting respiratory signals and heartbeat signals according to the high-resolution range profile;

and S300, determining physical sign data of the human body to be detected according to the respiration signal and the heartbeat signal, wherein the physical sign data comprises respiration rate, real-time respiration rate variability, heart rate and real-time heart rate variability.

Further, the step S200 includes:

s210, constructing an observation signal of a human body to be detected, wherein the observation signal is a linear frequency modulation signal of a distance unit where the chest wall of the human body to be detected is located;

step S220, determining the frequency parameter of the signal with the strongest amplitude in the plurality of observed signals;

step S230, determining an orthogonal projection operator according to the frequency parameter of the signal with the strongest amplitude, and filtering the signal with the strongest amplitude by adopting the orthogonal projection operator to obtain a plurality of new observed signals;

step S240, repeating step S220 and step S230 for a plurality of times on the plurality of new observation signals, finally obtaining a plurality of filtered observation signals, and determining estimated values of frequency and amplitude based on the plurality of filtered observation signals;

step S250, identifying a respiratory signal and a harmonic wave of the respiratory signal according to the estimated values of the frequency and the amplitude;

step S260, constructing a projection operator according to the identified breathing signal and the harmonic wave of the breathing signal;

and step S270, filtering the respiratory signal and the harmonic wave of the respiratory signal from the chest wall motion signal by using a projection operator to finally obtain the heartbeat signal.

Further, the step S210 includes:

step S211, emitting N frames of electromagnetic wave signals to a human body to be detected, wherein each frame of electromagnetic wave signal comprises M linear frequency modulation signals to form MN linear frequency modulation signals; then sampling the received echo signals, wherein the sampling number of each echo signal is K, and constructing an initial data matrix of MN multiplied by K;

step S212, obtaining a high-resolution range profile according to the initial data matrix, and finding out a range unit where the chest wall is located from the high-resolution range profile;

step S213, rearranging MN rows of linear frequency modulation signals of the distance unit where the chest wall is located to form an N × M matrix, thereby constructing a data structure of M echo signals, and using the data structure of M echo signals as the observation signal Y.

Further, in step S212, the obtaining a high-resolution range profile according to the initial data matrix specifically includes:

and processing each frame of linear frequency modulation signal in the initial data matrix by using a multiple signal classification algorithm to obtain a high-resolution range profile.

Further, the step S300 includes: determining a respiration rate according to the respiration signal, and extracting real-time respiration rate variability according to the respiration rate; determining a heart rate according to the heartbeat signal, and extracting real-time heart rate variability according to the heart rate; and taking the respiration rate, the real-time respiration rate variability, the heart rate and the real-time heart rate variability as physical sign data of the human body to be detected.

Further, the observation signal is obtained by performing multi-snapshot sampling on the returned echo signal.

A computer-readable storage medium having stored thereon a computer program which, when being executed by a processor, carries out the steps of the method for frequency modulated continuous wave radar-based vital sign data processing according to any one of the preceding claims.

A frequency modulated continuous wave radar-based vital sign data processing system, comprising:

at least one processor;

at least one memory for storing at least one program;

when executed by the at least one processor, the at least one program causes the at least one processor to implement the method for frequency modulated continuous wave radar-based vital sign data processing as defined in any one of the above.

The invention has the beneficial effects that: the invention discloses a sign data processing method and system based on a frequency modulation continuous wave radar. The method is used for detecting the mechanical motion signal of the chest wall of a human body to be detected, receiving the returned echo signal, and realizing high-precision real-time extraction of respiration rate, heart rate, variability of respiration rate and variability of heart rate by performing parameter optimization on the echo signal, adopting signal processing and other technical approaches, thereby providing accurate and clear physical sign data.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.

Fig. 1 is a schematic flow chart of a method for processing sign data based on a frequency modulated continuous wave radar according to an embodiment of the present invention;

fig. 2 is a schematic structural diagram of an observation signal of a human body to be measured in the embodiment of the present invention.

Detailed Description

The conception, specific structure and technical effects of the present disclosure will be clearly and completely described below in conjunction with the embodiments and the accompanying drawings to fully understand the objects, aspects and effects of the present disclosure. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.

The following explains the principle of radar measurement of physical sign data (respiration rate, heart rate, respiration rate variability, and heart rate variability) of a human body:

respiratory and heartbeat movements cause small displacements of the chest wall, with respiratory-induced displacements ranging from 1mm to 12mm and heartbeat-induced displacements ranging from 0.01mm to 0.5 mm. Both the displacement caused by breathing and the displacement caused by the heartbeat are quasi-periodic mechanical movements, the frequency of breathing is typically 0.1Hz to 0.6Hz, and the frequency of heartbeat is 0.8Hz to 2.5 Hz. The small displacement of the chest wall can generate a modulation effect on the radar signal, and an echo signal generated by modulation is received by the radar and is processed.

The following is a specific technical scheme provided by the invention:

referring to fig. 1, fig. 1 shows a method for processing sign data based on frequency modulated continuous wave radar, the method includes the following steps:

among them, the Multiple-Signal-Classification-Method (MUSIC) algorithm is proposed by Schmidt et al. The basic idea of the MUSIC algorithm is to perform eigen decomposition on the covariance matrix of any array output data to obtain a signal subspace corresponding to a signal component and a noise subspace orthogonal to the signal component, and then to estimate signal parameters by using the orthogonality of the two subspaces.

In a specific embodiment, a distance unit where the chest wall is located in the high-resolution range profile, phase information of the distance unit is extracted, the phase information of the distance unit is corrected in a phase unwrapping mode, and a respiratory signal and a heartbeat signal are extracted from the corrected distance unit;

in the technical field, a High Resolution Range Profile (HRRP) is a vector sum of a projection of a complex echo of a target scattering point obtained by using a broadband radar signal on a radar ray, and provides distribution information of the target scattering point along a distance direction.

S300, determining physical sign data of a human body to be detected according to the respiration signal and the heartbeat signal;

wherein the vital sign data comprises a respiration rate, a real-time respiration rate variability, a heart rate, and a real-time heart rate variability;

specifically, the step S300 includes: determining a respiration rate according to the respiration signal, and extracting real-time respiration rate variability according to the respiration rate; determining a heart rate according to the heartbeat signal, and extracting real-time heart rate variability according to the heart rate; taking the respiration rate, the real-time respiration rate variability, the heart rate and the real-time heart rate variability as physical sign data of a human body to be detected;

it is understood that the respiration rate in this embodiment refers to the instantaneous respiration rate in a short time window, and the heart rate refers to the instantaneous heart rate in a short time window; in one embodiment, the monitoring of the physical sign parameters of the human body to be detected is realized by respectively obtaining estimated values of the instantaneous respiration rate and the instantaneous heart rate by using a sparse recovery algorithm and completing the extraction of the respiration rate variability and the heart rate variability according to the instantaneous respiration rate and the instantaneous heart rate.

In the embodiment provided by the invention, a low-power Frequency Modulated Continuous Wave Radar (FMCW) is adopted to transmit electromagnetic Wave signals to a human body to be measured, the FMCW can accurately monitor the respiration and heartbeat of the human body in a non-contact mode, so that the measured person can measure in a completely non-sensitive state, the intentional or unintentional state of illness can be avoided, the influence of external meteorological conditions is avoided, and the method is completely suitable for accurate and efficient infectious disease screening of large-flow crowds in privacy critical occasions. By selecting a large-scale commercial frequency modulation continuous wave radar on the market as a measuring platform, the vital signs of a human body to be detected can be detected more conveniently and more efficiently.

Due to the interference of the external environment, the physical sign data (respiratory rate, heart rate, respiratory rate variability and heart rate variability) detected by the radar is often not accurate and clear enough, and all characteristic data contained in the physical sign data are mutually mixed and cannot be used as effective data.

As an improvement of the above technical solution, the following further describes the separation of the respiratory signal and the heartbeat signal from the high-resolution range profile:

in the technical field, the chest wall displacement is caused by two superposed quasi-periodic mechanical motions of respiration and heartbeat, which causes that the frequency spectrum components of echo signals received by a radar are very complex, the frequency spectrum components comprise the fundamental frequency of respiration signals and the harmonic waves of the respiration signals, the fundamental frequency of heartbeat signals and the harmonic waves of the heartbeat signals, intermodulation signals of the respiration signals and the heartbeat signals, and the like, and the signals are superposed in the narrow frequency spectrum of 0.1 Hz-3 Hz, which is very unfavorable for the extraction of the heartbeat signals. Particularly, the 2 nd harmonic, the 3 rd harmonic and the 4 th harmonic of the respiration signal are similar to the fundamental frequency signal of the heartbeat signal in frequency and amplitude, which further increases the difficulty of accurately extracting the heartbeat signal. The efficient separation of the respiration signal from the heartbeat signal becomes a critical issue.

The frequency of the breathing signal is low and a long time window is required to reveal the quasiperiodic characteristic, e.g. assuming a fundamental frequency of breathing of 0.3Hz, a 2 second window length will only encompass 0.6 complete breathing cycles, whereas a 10 second window length will encompass 3 complete breathing cycles. Therefore, in order to accurately estimate the respiratory signal and the harmonic frequency thereof and better filter the respiratory signal and the harmonic signal thereof from the echo signal of the chest wall, the invention adopts the window length of about 10 seconds at the separation stage of the respiratory signal and the heartbeat signal.

Accordingly, the time window of the heart rate variability extraction phase is adaptively selected according to the average heart rate obtained in the signal separation phase, and in a specific embodiment, the window length of the heart rate variability extraction phase is 1 to 2 heartbeat intervals, so as to meet the requirement of instantaneous heart rate estimation.

However, the separation and detection of heart rate in harmonic flooding of the respiratory signal remains a difficult problem. To solve the technical problem, in a preferred embodiment, the step S200 includes:

in this embodiment, the observation signal is obtained by performing multi-snapshot sampling on a returned echo signal;

in a preferred embodiment, as shown in fig. 2, the observed signal of the human body to be measured is constructed by:

in one embodiment, a high resolution range profile is obtained by processing each frame of chirp signal in the initial data matrix using a multiple signal classification algorithm.

Step S220, determining the frequency parameter of the signal with the strongest amplitude in the plurality of observation signals Y;

in one embodiment, the plurality of observation signals Y are processed by using a low-complexity sparse recovery algorithm, and a frequency parameter of a signal with the strongest amplitude in the plurality of observation signals Y is estimated and determined as the frequency parameter of the signal with the strongest amplitude in the plurality of observation signals Y;

step S230, determining an orthogonal projection operator P according to the frequency parameter of the signal with the strongest amplitude, and filtering the signal with the strongest amplitude by adopting the orthogonal projection operator P to obtain a plurality of new observation signals PY;

step S240, repeating step S220 and step S230 for a plurality of times on the plurality of new observation signals PY to finally obtain a plurality of filtered observation signals, and determining frequency and amplitude estimation values based on the plurality of filtered observation signals;

specifically, step S250 includes: identifying the respiratory signal and the harmonic wave of the respiratory signal based on the respiratory signal and the difference of the harmonic wave of the respiratory signal and the heartbeat fundamental frequency on the spectrum characteristic;

step S260, constructing a projection operator P according to the identified breathing signal and harmonic wave of the breathing signal_r；

Step S270, using projection operator P_rAnd filtering the respiratory signal and the harmonic wave of the respiratory signal from the observation signal to finally obtain the heartbeat signal.

It can be understood that the heartbeat signal obtained at this time is a pure heartbeat signal.

According to the method, strong signals in the observation signals are filtered by adopting successive iteration of orthogonal images, weak signals in the observation signals are gradually highlighted, then the respiratory signals and the harmonic waves of the respiratory signals are identified according to the frequency spectrum characteristics, and finally the respiratory signals and the harmonic waves of the respiratory signals are filtered from the observation signals by using the projection filtering technology again, so that the heart rate signals can be removed from the false frequency pseudo signals of the respiratory harmonic waves, more accurate heartbeat signals can be obtained, and accurate extraction of the heart rate and the heart rate variability is facilitated.

In a preferred embodiment, the step S250 specifically includes:

the discrimination of respiratory and heartbeat signals is discussed based on three condition classifications.

In the first case: when the 2 nd harmonic and the 3 rd harmonic of the respiratory signal are different from the heartbeat fundamental frequency by more than 0.1Hz and the resolution ratio is more than 0.05 Hz;

in step S240, the number of times that steps S220 to S230 are repeated for a plurality of new observation signals PY is set to be 4, the breathing signal and the range of the first 3 harmonic frequencies of the breathing signal are determined according to the results of the previous 4 iterations, and then the heartbeat signal and the breathing signal are identified.

In the second case: when the difference between the 2 nd harmonic and the 3 rd harmonic of the respiratory signal and the heartbeat fundamental frequency is lower than 0.1 Hz;

in step S240, the number of times of repeating steps S220 to S230 for a plurality of new observation signals PY is increased until 2 harmonics of the heartbeat signal are estimated, then the fundamental frequency of the heartbeat signal is reversely deduced according to the 2 harmonics of the heartbeat signal, the position interval of 4 harmonics of the respiration signal is calculated by combining the fundamental frequency of the respiration signal, the 2 harmonics of the respiration signal and the 3 harmonics of the respiration signal, and finally the separation of the respiration signal and the heartbeat signal is realized.

In the third case: the 3 rd harmonic of the respiration signal or the 3 rd harmonic of the respiration signal is equal to the fundamental frequency of the heartbeat signal;

similarly to the second case, in step S240, the number of times of repeating steps S220 to S230 for a plurality of new observation signals PY is increased until the point of maximum amplitude is found within the range interval of the 2 nd harmonic of the heartbeat signal as the estimated value of the 2 nd harmonic of the heartbeat signal, and the 2 nd harmonic of the heartbeat signal is taken as the heartbeat signal.

Corresponding to the method of fig. 1, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the frequency modulated continuous wave radar-based vital sign data processing method according to any one of the embodiments described above.

Corresponding to the method in fig. 1, an embodiment of the present invention further provides a system for processing sign data based on frequency modulated continuous wave radar, including:

at least one processor;

at least one memory for storing at least one program;

when executed by the at least one processor, the at least one program causes the at least one processor to implement the method for processing vital sign data based on frequency modulated continuous wave radar as in any one of the embodiments described above.

The contents in the above method embodiments are all applicable to the present system embodiment, the functions specifically implemented by the present system embodiment are the same as those in the above method embodiment, and the beneficial effects achieved by the present system embodiment are also the same as those achieved by the above method embodiment.

The Processor may be a Central-Processing Unit (CPU), other general-purpose Processor, a Digital Signal Processor (DSP), an Application-Specific-Integrated-Circuit (ASIC), a Field-Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, a discrete hardware component, or the like. The general processor can be a microprocessor or the processor can be any conventional processor and the like, the processor is a control center of the frequency modulation continuous wave radar-based sign data processing system, and various interfaces and lines are utilized to connect various parts of the whole frequency modulation continuous wave radar-based sign data processing system operable device.

The memory can be used for storing the computer program and/or the module, and the processor can realize various functions of the vital sign data processing system based on the frequency modulation continuous wave radar by running or executing the computer program and/or the module stored in the memory and calling the data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart-Media-Card (SMC), a Secure-Digital (SD) Card, a Flash-memory Card (Flash-Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.

While the present disclosure has been described in considerable detail and with particular reference to a few illustrative embodiments thereof, it is not intended to be limited to any such details or embodiments or any particular embodiments, but it is to be construed with references to the appended claims so as to provide a broad, possibly open interpretation of such claims in view of the prior art, and to effectively encompass the intended scope of the disclosure. Furthermore, the foregoing describes the disclosure in terms of embodiments foreseen by the inventor for which an enabling description was available, notwithstanding that insubstantial modifications of the disclosure, not presently foreseen, may nonetheless represent equivalent modifications thereto.

Claims

1. A sign data processing method based on frequency modulated continuous wave radar is characterized by comprising the following steps:

step S300, determining physical sign data of a human body to be detected according to the respiration signal and the heartbeat signal, wherein the physical sign data comprise respiration rate, real-time respiration rate variability, heart rate and real-time heart rate variability;

wherein the step S200 includes:

2. The method for processing signs data based on frequency modulated continuous wave radar as claimed in claim 1, wherein the step S210 comprises:

step S213, rearranging MN rows of linear frequency modulation signals of the distance unit where the chest wall is located to form an N × M matrix, thereby constructing a data structure of M echo signals, and using the data structure of M echo signals as an observation signal.

3. The method for processing vital sign data based on frequency modulated continuous wave radar as claimed in claim 2, wherein in step S212, the obtaining of the high-resolution range profile according to the initial data matrix specifically comprises:

4. The method for processing signs data based on frequency modulated continuous wave radar as claimed in claim 3, wherein the step S300 comprises: determining a respiration rate according to the respiration signal, and extracting real-time respiration rate variability according to the respiration rate; determining a heart rate according to the heartbeat signal, and extracting real-time heart rate variability according to the heart rate; and taking the respiration rate, the real-time respiration rate variability, the heart rate and the real-time heart rate variability as physical sign data of the human body to be detected.

5. The method for processing vital sign data based on frequency modulated continuous wave radar as claimed in claim 1, wherein the observation signal is obtained by multi-snapshot sampling of the returned echo signal.

6. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, carries out the steps of the frequency modulated continuous wave radar-based vital sign data processing method according to any one of claims 1 to 5.

7. A frequency modulated continuous wave radar-based sign data processing system, comprising:

at least one processor;

at least one memory for storing at least one program;

when executed by the at least one processor, cause the at least one processor to implement a method for frequency modulated continuous wave radar-based vital signs data processing according to any one of claims 1 to 5.