Vital sign monitoring method and device based on FMCW, equipment and storage medium

Abstract

The invention discloses a vital sign monitoring method and device based on FMCW, equipment and a storage medium, and relates to the field of vital sign monitoring. According to the specific implementation scheme, the method comprises the steps that multiple frames of FMCW radar echo signals are received, processing steps are executed on the multiple frames of FMCW radar echo signals, and multiple third signals and multiple target motion phases corresponding to the third signals are obtained; determining a plurality of second signals according to the plurality of third signals and the plurality of target motion phases, further determining breathing and heartbeat frequencies, and sending the breathing and heartbeat frequencies to an upper computer so as to monitor human body vital signs; the processing step comprises the following steps: determining a target motion phase and a target distance gate according to the plurality of first signals; and determining a third signal and a phase value thereof according to the plurality of first signals and the target distance gate, the third signal being an average signal of the first signals located at the target distance gate. According to the vital sign monitoring method and device, the problem that the accuracy of vital sign monitoring is not high when the RBM of the human body is higher in speed in the prior art can be solved, and the accuracy of vital sign monitoring is improved.

Description

Technical Field

[0001] The present application relates to the technical field of vital signs monitoring, and in particular to a method, device, equipment and storage medium for vital signs monitoring based on FMCW. Background Art

[0002] In the field of human vital signs monitoring, heartbeat and breathing are key indicators for assessing human health. FMCW (Frequency-Modulated Continuous Wave) technology can be used to achieve non-contact monitoring of heartbeat and breathing.

[0003] At present, FMCW radar is used to transmit frequency modulated continuous wave signals to the human body, receive the reflected echo signals, and perform certain signal processing on the received echo signals, so as to capture the human heart rate and respiratory rate signs, and realize the monitoring of human heart rate and breathing.

[0004] However, existing methods can effectively monitor vital signs when the human body remains still or exhibits RBM (Random Body Movement) with a speed lower than 2 cm / s. However, when the human body exhibits RBM at a faster speed (such as turning around, swinging back and forth), the accuracy of vital sign monitoring is not high. Summary of the invention

[0005] The embodiments of the present application provide a FMCW-based vital signs monitoring method, device, equipment and storage medium to solve the problem that the existing technology is limited in the applicable scenarios and difficult to accurately monitor human vital signs in the faster RMM scenario, thereby expanding the applicable scenarios of vital signs monitoring and improving the accuracy of vital signs monitoring.

[0006] In a first aspect, an embodiment of the present application provides a method for monitoring vital signs based on FMCW, including: A plurality of frames of FMCW radar echo signals are received, wherein each frame of the FMCW radar echo signals includes a plurality of first signals; processing steps are respectively performed on the plurality of frames of the FMCW radar echo signals to obtain a plurality of third signals and a plurality of target motion phases corresponding to the plurality of third signals; a plurality of second signals are determined according to the plurality of third signals and the plurality of target motion phases, wherein the second signal is the third signal after the target motion phase is eliminated; a respiratory frequency and a heart rate are determined according to the plurality of second signals; the respiratory frequency and the heart rate are sent to a host computer to monitor the vital signs of a human body; wherein the processing steps include: determining a target motion phase corresponding to a human body motion and a target range gate where the human body is located according to the plurality of first signals; determining a third signal and a phase value of the third signal according to the plurality of first signals and the target range gate, wherein the third signal is an average signal of the first signals located at the target range gate.

[0007] Further, determining the target motion phase corresponding to the human body motion and the target range gate where the human body is located according to the multiple first signals includes: After performing fast Fourier transform along the distance dimension, the multiple first signals are respectively subjected to fast Fourier transform along the slow time dimension to obtain multiple Doppler-range spectra; multiple target motion speeds corresponding to human motion are determined according to the multiple Doppler-range spectra; target motion phases are determined according to the multiple target motion speeds; and target range gates are determined according to the multiple Doppler-range spectra.

[0008] Further, determining a third signal and a phase value of the third signal according to the plurality of first signals and the target range gate includes: Fast Fourier transform is performed on multiple first signals along the distance dimension, and the first signals located at the target range gate are added along the slow time dimension and then averaged to obtain a third signal; based on the third signal, inverse tangent demodulation is used to determine the phase value of the third signal.

[0009] Further, according to the multiple Doppler-range spectra, multiple target motion speeds corresponding to the human body motion are determined, including: According to multiple Doppler-distance spectra, multiple first motion speeds corresponding to human body motion are determined; according to the multiple first motion speeds and preset coefficients, a second motion speed is determined, and the second motion speed is the product of an average value of the multiple first motion speeds and the preset coefficient; according to the multiple first motion speeds and the second motion speeds, multiple target motion speeds are determined.

[0010] Further, determining the respiratory rate and the heart rate according to the plurality of second signals includes: A first-order phase difference signal is determined according to the multiple second signals; and a respiratory frequency and a heart rate frequency are determined according to the first-order phase difference signal.

[0011] Further, the respiratory rate and the heart rate are determined according to the first-order phase difference signal, including: The first-order phase difference signal is subjected to fast Fourier transform to determine the breathing frequency. The heart rate is determined based on the first-order phase difference signal through a target algorithm. The target algorithm is an adaptive noise complete set empirical mode decomposition algorithm.

[0012] Furthermore, the first signal is a linear frequency modulation signal.

[0013] In a second aspect, an embodiment of the present application provides a FMCW-based vital sign monitoring device, including: a receiving module, a processing module, a determining module and a monitoring module.

[0014] The receiving module is used to receive multiple frames of FMCW radar echo signals, wherein each frame of the FMCW radar echo signal includes multiple first signals.

[0015] The processing module is used to perform processing steps on multiple frames of FMCW radar echo signals respectively to obtain multiple third signals and multiple target motion phases corresponding to the multiple third signals.

[0016] The determination module is used to determine multiple second signals according to multiple third signals and multiple target motion phases, wherein the second signal is the third signal after eliminating the target motion phase.

[0017] The monitoring module is used to determine the respiratory rate and the heart rate according to the multiple second signals; and send the respiratory rate and the heart rate to the host computer to monitor the vital signs of the human body.

[0018] Among them, the processing steps include: determining the target motion phase corresponding to the human body movement and the target distance gate where the human body is located based on multiple first signals; determining the third signal and the phase value of the third signal based on multiple first signals and the target distance gate, and the third signal is the average signal of the first signals located at the target distance gate.

[0019] In a third aspect, an embodiment of the present application provides a device, comprising: a processor; a memory for storing processor executable instructions; and a method for implementing the first aspect or any possible implementation of the first aspect when the processor executes the executable instructions.

[0020] In a fourth aspect, an embodiment of the present application provides a non-volatile computer-readable storage medium, which includes a device for storing a computer program or instruction. When the computer program or instruction is executed, the method of the first aspect or any possible implementation method of the first aspect is implemented.

[0021] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: The embodiment of the present application obtains multiple third signals and corresponding multiple target motion phases by performing processing steps on multiple frames of FMCW radar echo signals respectively; multiple second signals are determined based on the multiple third signals and multiple target motion phases, wherein the second signal is the third signal after eliminating the target motion phase. The present application determines the respiratory rate and heart rate based on multiple second signals, and quickly and accurately determines the respiratory rate and heart rate by eliminating the second signal affected by the human body's RBM, thereby expanding the applicable scenarios of vital signs monitoring and improving the accuracy of vital signs monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0023] Figure 1 A flow chart of a FMCW-based vital signs monitoring method provided in an embodiment of the present application; Figure 2 This is a comparison chart of the effects of the present application method and the EGC method; Figure 3 This is a comparison chart of the effects of the present application method and the traditional FWCM method; Figure 4 A schematic diagram of the composition of an FMCW-based vital signs monitoring device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0024] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] The following describes some of the techniques involved in the embodiments of the present application to facilitate understanding, and they should be considered as merely exemplary. Therefore, it should be appreciated by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present application. Similarly, for the sake of clarity and conciseness, some descriptions of well-known functions and structures are omitted in the following description.

[0026] In the field of human vital signs monitoring, heartbeat and respiration are key indicators for assessing human health. FMCW technology can be used to achieve non-contact monitoring of heartbeat and respiration.

[0027] At present, FMCW radar is used to transmit frequency modulated continuous wave signals to the human body, receive the reflected echo signals, and perform certain signal processing on the received echo signals, so as to capture the human heart rate and respiratory rate signs, and realize the monitoring of human heart rate and breathing.

[0028] However, existing methods can effectively monitor vital signs when the human body remains still or has RBMs with a speed lower than 2 cm / s, but when the human body has RBMs with a faster speed, the accuracy of vital sign monitoring is not high.

[0029] Against this background, the present disclosure provides a vital sign monitoring method based on FMCW, which can improve the accuracy of vital sign monitoring.

[0030] The execution subject of the FMCW-based vital sign monitoring method provided by the embodiment of the present disclosure may be a computer or a server, or may also be other electronic devices with data processing capabilities; or, the execution subject of the method may also be a processor (such as a central processing unit (CPU)) in the above electronic device; or, the execution subject of the method may also be an application (application, APP) installed in the above electronic device that can implement the function of the method; or, the execution subject of the method may also be a functional module or unit in the above electronic device that has the function of the method, etc. There is no limitation on the execution subject of the method herein.

[0031] The FMCW-based vital sign monitoring method is exemplarily described below with reference to the accompanying drawings.

[0032] Figure 1 : is a flow chart of a FMCW-based vital signs monitoring method provided in an embodiment of the present application. Figure 1 This is only an execution order shown in the embodiment of the present application, and does not represent the only execution order of the FMCW-based vital signs monitoring method. If the final result can be achieved, Figure 1 The steps shown can be performed in parallel or in reverse. Figure 1 As shown, the method may include the following S101 to S103.

[0033] S101. Receive multiple frames of FMCW radar echo signals.

[0034] Each frame of the FMCW radar echo signal includes a plurality of first signals.

[0035] Exemplarily, the first signal may be a linear frequency modulation signal (ie, a chirp signal). Generally, each frame of the FMCW radar echo signal includes the same number of first signals.

[0036] It can be understood that the FMCW radar transmits a multi-frame radar signal, each frame of which includes a plurality of linear frequency modulation signals.

[0037] S102, performing processing steps on multiple frames of FMCW radar echo signals respectively to obtain multiple third signals and multiple target motion phases corresponding to the multiple third signals.

[0038] It can be understood that after executing the processing steps on any frame of FMCW radar echo signal, the third signal corresponding to the frame of FMCW radar echo signal and the target motion phase corresponding to the third signal can be obtained; after executing the processing steps on multiple frames of FMCW radar echo signals respectively, multiple third signals corresponding to the multiple frames of FMCW radar echo signals and multiple target motion phases corresponding to the multiple third signals can be obtained.

[0039] The processing steps include the following S201 to S202.

[0040] S201. Determine, according to a plurality of first signals, a target motion phase corresponding to a human body motion and a target range gate where the human body is located.

[0041] Specifically, S201 may include the following S301 to S304.

[0042] S301 , performing fast Fourier transform along the range dimension on a plurality of first signals respectively, and then performing fast Fourier transform along the slow time dimension to obtain a plurality of Doppler-range spectra.

[0043] S302: Determine multiple target motion speeds corresponding to human body motion according to multiple Doppler-range spectra.

[0044] In some possible implementations, for any Doppler-range spectrum, the angular frequency corresponding to the maximum peak in the Doppler-range spectrum can be determined, and then the speed corresponding to the angular frequency can be determined according to the FMCW speed measurement formula, and the speed corresponding to the angular frequency can be determined as the target movement speed corresponding to the human body movement corresponding to the Doppler-range spectrum.

[0045] For example, the FMCW speed measurement formula is shown in the following formula (1): (1) In formula (1), Indicates the speed of an object (the application scenario of this application is to determine the speed of human movement through the FMCW speed measurement formula. can represent the target movement speed corresponding to human movement). is the wavelength of the FMCW radar, is the angular frequency, is the duration of a linear frequency modulation signal.

[0046] In some other possible implementations, S302 may include the following S501 to S503.

[0047] S501 . Determine a plurality of first motion speeds corresponding to human body motion according to a plurality of Doppler-range spectra.

[0048] Exemplarily, for any Doppler-range spectrum, the angular frequency corresponding to the maximum peak in the Doppler-range spectrum can be determined, and then the speed corresponding to the angular frequency can be determined according to the FMCW speed measurement formula shown in formula (1), and the speed corresponding to the angular frequency can be determined as the first motion speed corresponding to the human body motion corresponding to the Doppler-range spectrum; after processing all Doppler-range spectra, multiple first motion speeds corresponding to the human body motion can be obtained.

[0049] S502: Determine a second movement speed according to a plurality of first movement speeds and a preset coefficient.

[0050] The second movement speed is the product of an average value of a plurality of first movement speeds and a preset coefficient.

[0051] Exemplarily, the preset coefficient may be set to 1.4.

[0052] S503: Determine a plurality of target motion speeds according to a plurality of first motion speeds and a second motion speed.

[0053] For example, the target motion speed may be determined by the following formula (2): (2) In formula (2), Indicates The target movement speed, Indicates The first movement speed, Indicates the second motion speed.

[0054] It should be noted that when hour, .

[0055] It can be understood that by executing S501 to S503 for each Doppler-range spectrum, a plurality of target movement speeds corresponding to the plurality of Doppler-range spectra can be obtained.

[0056] In this way, the movement speeds of multiple targets can be determined quickly and accurately based on multiple Doppler-range spectra.

[0057] S303: Determine the target motion phase according to multiple target motion speeds.

[0058] Exemplarily, the product of the sum of multiple target motion speeds corresponding to any frame of FMCW radar echo signal and the frame period length can be determined as the random motion of the human body in the frame of FMCW radar echo signal, and the phase value of the random motion of the human body corresponding to the frame of FMCW radar echo signal can be determined as the target motion phase corresponding to the frame of FMCW radar echo signal.

[0059] For example, the random motion of the human body can be determined by the following formula (3): (3) In formula (3), Indicates Random motion of human body in frame FMCW radar echo signal, Indicates the frame period length of the FMCW radar echo signal. Indicates The target movement speed, Indicates The number of target motion speeds in the frame FMCW radar echo signal (understandably, That is The number of Doppler-range spectra in the frame FMCW radar echo signal, the The number of first signals in the frame FMCW radar echo signal).

[0060] For example, the phase value of the random motion of the human body can be determined by the following formula (4): (4) In formula (4), Indicates Phase values ​​of random motion of human body in frame FMCW radar echo signal.

[0061] S304: Determine a target range gate according to multiple Doppler-range spectra.

[0062] Exemplarily, the range gate where the maximum peak in each Doppler-range spectrum is located can be determined as the target range gate.

[0063] In this way, the target motion phase and target range gate can be determined quickly and accurately based on the Doppler-range spectrum.

[0064] It can be understood that after S304 is executed, S202 can be continued to be executed.

[0065] S202: Determine a third signal and a phase value of the third signal according to the multiple first signals and the target range gate.

[0066] The third signal is an average signal of the first signals located at the target range gate.

[0067] Specifically, S202 may include the following S401 to S402.

[0068] S401 , performing fast Fourier transform on multiple first signals along the range dimension, adding and averaging the first signals located at the target range gate along the slow time dimension, and obtaining a third signal.

[0069] For example, the third signal may be determined by the following formula (5): (5) In formula (5), Indicates Among the distance gates, The first signal data of the slow time dimension after the fast Fourier transform of the distance dimension; The first range gate is the target range gate; Indicates the number of first signals in the FMCW radar echo signal; Indicates the third signal.

[0070] S402: Determine a phase value of the third signal by using arc tangent demodulation according to the third signal.

[0071] Exemplarily, the third signal is a complex signal, the real part and the imaginary part of the complex signal constitute the real phase information of the radar intermediate frequency signal, and the phase value of the third signal can be calculated using inverse tangent demodulation.

[0072] For example, the phase value of the third signal may be determined using the following formula (6): (6) In formula (6), represents the phase value of the third signal, is the in-phase branch of the phase signal, It is the orthogonal branch of the phase signal.

[0073] Exemplarily, the phase value of the third signal may also be determined by a DACM demodulation algorithm. The DACM demodulation algorithm is a common technical means for those skilled in the art to determine the phase value of a signal, and its calculation process is not described in detail here.

[0074] In this way, the third signal and the phase value of the third signal can be accurately determined according to the first signal and the target range gate.

[0075] S103: Determine a plurality of second signals according to a plurality of third signals and a plurality of target motion phases.

[0076] The second signal is a third signal after eliminating the target motion phase.

[0077] Exemplarily, the phase values ​​of multiple third signals can be unwrapped first, and the unwrapped phase values ​​of the multiple third signals can be subtracted from the corresponding target motion phases. The corresponding third signals can be updated according to the subtracted phase values ​​to obtain a second signal that eliminates the target motion phase.

[0078] For example, taking the reception of 10 frames of FMCW radar echo signals as an example, 10 third signals corresponding to the 10 frames of FMCW radar echo signals and 10 target motion phases can be obtained; the phase values ​​of the 10 third signals are unwrapped to obtain 10 unwrapped phase values; the 10 unwrapped phase values ​​are subtracted from the 10 target motion phases corresponding to the corresponding 10 third signals to obtain 10 subtracted phase values, and the corresponding 10 third signals are updated according to the 10 subtracted phase values ​​(that is, the phase value of the third signal is updated to the subtracted phase value) to obtain 10 second signals that eliminate the target motion phase.

[0079] S104: Determine the respiratory rate and the heart rate according to the multiple second signals.

[0080] Exemplarily, before executing S104 , the plurality of second signals may also be passed through a bandpass filter of 0.2 Hz to 3.0 Hz to filter out clutter.

[0081] Specifically, S104 may include the following S601 to S602.

[0082] S601. Determine a first-order phase difference signal according to multiple second signals.

[0083] Exemplarily, first-order phase differentials may be performed on the plurality of second signals respectively to obtain first-order phase differential signals.

[0084] S602: Determine the respiratory rate and the heart rate according to the first-order phase difference signal.

[0085] Exemplarily, the respiratory rate and the heart rate can be determined by wavelet packet transform algorithm, variational modal decomposition (VMD) algorithm, variational mode extraction (VME) algorithm. Determining the respiratory rate and the heart rate by wavelet packet transform algorithm, VMD algorithm, and VME algorithm is a conventional technical means in the art and will not be described in detail here.

[0086] In some possible implementations, S602 may include the following S701 to S702.

[0087] S701. Perform fast Fourier transform on the first-order phase difference signal to determine the respiratory frequency.

[0088] Exemplarily, the frequency corresponding to the peak value after the first-order phase difference signal is fast Fourier transformed can be determined as the respiratory frequency.

[0089] S702: Determine the heart rate frequency according to the first-order phase difference signal through a target algorithm.

[0090] Among them, the target algorithm is the Complete Ensemble Empirical Modal Decomposition with Adaptive Noise (CEEMDAN) algorithm.

[0091] It should be noted that the CEEMDAN algorithm belongs to the existing technology, and the calculation iteration process of the algorithm itself will not be described here.

[0092] It can be understood that multiple intrinsic mode functions (IMFs) can be obtained through the CEEMDAN algorithm. The IMF with a frequency between 0.7 Hz and 2 Hz and which is not a harmonic of the respiratory signal after fast Fourier transform is determined as the target IMF. The heart rate frequency can be obtained by performing peak search on the target IMF after fast Fourier transform.

[0093] In this way, the respiratory rate and the heart rate can be determined more accurately based on the multiple second signals.

[0094] S105, sending the respiratory rate and heart rate to the host computer to monitor the vital signs of the human body.

[0095] After obtaining the respiratory rate and heart rate, they can be sent to the host computer, which can then obtain the human body's respiratory rate and heart rate per minute through simple calculations to monitor the human body's vital signs. This will not be elaborated here.

[0096] The embodiment of the present application obtains multiple third signals and corresponding multiple target motion phases by respectively executing processing steps on multiple frames of FMCW radar echo signals; determines multiple second signals based on the multiple third signals and the multiple target motion phases, wherein the second signal is the third signal after eliminating the target motion phase; determines the respiratory rate and the heart rate based on the multiple second signals, and can quickly and accurately determine the respiratory rate and the heart rate through the second signal that eliminates the influence of human RBM, thereby expanding the applicable scenarios of vital signs monitoring and improving the accuracy of vital signs monitoring.

[0097] Effect verification Comparison 1: The heart rate is determined by the method of the present application and the EGC (Electrocardiogram) method. Figure 2 This is a comparison chart of the effects of the present application method and the EGC method.

[0098] refer to Figure 2 It can be seen that the heart rate determined by the method of this application (i.e. Figure 2 The frequency corresponding to the highest peak in the thick blue solid line (the thin blue dashed line is an auxiliary line) is consistent with the heart rate determined by the contact EGC method (i.e. Figure 2 The frequency corresponding to the highest peak in the thick orange dashed line (the thin orange dashed line is the auxiliary line) is very close.

[0099] Comparison 2: The heart rate is determined by the method of the present application and the traditional FWCM method. Figure 3 This is a comparison chart of the effects of the present application method and the traditional FWCM method.

[0100] refer to Figure 3 It can be seen that in multiple test groups (Group 1 to Group 5), the accuracy of the heart rate determined by the method of the present application (i.e. Figure 3 The accuracy of the heart rate determined by the traditional FWCM method (i.e. Figure 3 medium orange-red rectangular bar).

[0101] Although the present application provides method operation steps such as embodiments or flow charts, more or fewer operation steps may be included based on conventional or non-creative labor. The order of steps listed in this embodiment is only one way of executing the order of many steps and does not represent the only execution order. When the actual device or client product is executed, it can be executed in the order of the method shown in this embodiment or the accompanying drawings or in parallel (for example, in a parallel processor or multi-threaded processing environment).

[0102] like Figure 4 As shown, the embodiment of the present application further provides a vital sign monitoring device based on FMCW. The device includes: a receiving module 801, a processing module 802 and a determining module 803.

[0103] The receiving module 801 is configured to receive multiple frames of FMCW radar echo signals, wherein each frame of the FMCW radar echo signal includes multiple first signals.

[0104] The processing module 802 is used to perform processing steps on multiple frames of FMCW radar echo signals respectively to obtain multiple third signals and multiple target motion phases corresponding to the multiple third signals.

[0105] The determination module 803 is used to determine a plurality of second signals according to a plurality of third signals and a plurality of target motion phases, wherein the second signal is the third signal after the target motion phase is eliminated.

[0106] The monitoring module 804 is used to determine the respiratory rate and the heart rate according to the multiple second signals; and send the respiratory rate and the heart rate to the host computer to monitor the vital signs of the human body.

[0107] Among them, the processing steps include: determining the target motion phase corresponding to the human body movement and the target distance gate where the human body is located based on multiple first signals; determining the third signal and the phase value of the third signal based on multiple first signals and the target distance gate, and the third signal is the average signal of the first signals located at the target distance gate.

[0108] The beneficial effects and specific implementation methods of the device embodiment can be referred to the aforementioned method embodiment, and will not be described in detail here.

[0109] Some modules in the apparatus described in the present application can be described in the general context of computer executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, classes, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0110] The devices or modules described in the above application embodiments can be implemented by computer chips or entities, or by products with certain functions. For the convenience of description, the above devices are described in various modules according to their functions. When implementing the embodiments of the present application, the functions of each module can be implemented in the same or multiple software and / or hardware. Of course, the module that implements a certain function can also be implemented by combining multiple sub-modules or sub-units.

[0111] The methods, devices or modules described in this application can be implemented in the form of computer-readable program codes. The controller can be implemented in any appropriate manner. For example, the controller can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program codes (such as software or firmware) that can be executed by the (micro)processor, logic gates, switches, application-specific integrated circuits (English: Application Specific Integrated Circuit; Abbreviation: ASIC), programmable logic controllers and embedded microcontrollers. Examples of controllers include but are not limited to the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20 and Silicone Labs C8051F320. The memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art also know that in addition to implementing the controller in the form of pure computer-readable program codes, the controller can be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers and embedded microcontrollers by logically programming the method steps. Therefore, this controller can be considered as a hardware component, and the devices included in it for implementing various functions can also be regarded as structures within the hardware component. Or even, the means for realizing various functions may be regarded as both a software module for realizing the method and a structure within a hardware component.

[0112] An embodiment of the present application further provides a device, comprising: a processor; a memory for storing processor executable instructions; when the processor executes the executable instructions, the method described in the embodiment of the present application is implemented.

[0113] The embodiments of the present application also provide a non-volatile computer-readable storage medium on which a computer program or instruction is stored. When the computer program or instruction is executed, the method described in the embodiments of the present application is implemented.

[0114] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist independently, or two or more modules may be integrated into one module.

[0115] The above storage media include but are not limited to random access memory (RAM), read-only memory (ROM), cache, hard disk drive (HDD) or memory card. The memory can be used to store computer program instructions.

[0116] It can be seen from the description of the above implementation methods that those skilled in the art can clearly understand that the present application can be implemented by means of software plus necessary hardware. Based on this understanding, the technical solution of the present application can be essentially or partly reflected in the prior art in the form of a software product, or it can be reflected in the implementation process of data migration. The computer software product can be stored in a storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a mobile terminal, a server, or a network device, etc.) to execute the methods described in the various embodiments of the present application or certain parts of the embodiments.

[0117] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. All or part of this application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld devices or portable devices, tablet devices, mobile communication terminals, multi-processor systems, microprocessor-based systems, programmable electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc.

[0118] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit the present application. Although the present application has been described in detail with reference to the aforementioned embodiments, a person of ordinary skill in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some or all of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the present application.

Claims

1. A vital sign monitoring method based on FMCW, characterized in that: include: receiving a plurality of frames of FMCW radar echo signals, wherein each frame of the FMCW radar echo signal includes a plurality of first signals; Performing processing steps on the multiple frames of FMCW radar echo signals respectively to obtain multiple third signals and multiple target motion phases corresponding to the multiple third signals; Determine a plurality of second signals according to the plurality of third signals and the plurality of target motion phases, wherein the second signals are the third signals after the target motion phases are eliminated; Determine the respiratory rate and the heart rate according to the plurality of second signals; Sending the respiratory rate and the heart rate to a host computer to monitor the vital signs of the human body; The processing steps include: Determine, based on the plurality of first signals, a target motion phase corresponding to the human body motion and a target range gate where the human body is located; A third signal and a phase value of the third signal are determined according to a plurality of first signals and the target range gate, wherein the third signal is an average signal of the first signals located at the target range gate.

2. The method according to claim 1, characterized in that The step of determining the target motion phase corresponding to the human body motion and the target range gate where the human body is located according to the multiple first signals includes: After performing fast Fourier transform along the range dimension, the plurality of first signals are respectively subjected to fast Fourier transform along the slow time dimension to obtain a plurality of Doppler-range spectra; determining a plurality of target motion speeds corresponding to human motion according to the plurality of Doppler-range spectra; Determining the target motion phase according to the multiple target motion speeds; The target range gate is determined according to the multiple Doppler-range spectra.

3. The method according to claim 1, characterized in that: The determining of a third signal and a phase value of the third signal according to the plurality of first signals and the target range gate comprises: Performing fast Fourier transform on the multiple first signals along the distance dimension, adding and averaging the first signals located at the target range gate along the slow time dimension, and obtaining a third signal; According to the third signal, the phase value of the third signal is determined by using arc tangent demodulation.

4. The method according to claim 2, characterized in that: The step of determining a plurality of target motion speeds corresponding to human motion according to the plurality of Doppler-range spectra includes: Determining a plurality of first motion speeds corresponding to human body motion according to the plurality of Doppler-range spectra; Determine a second movement speed according to the plurality of first movement speeds and a preset coefficient, wherein the second movement speed is a product of an average value of the plurality of first movement speeds and the preset coefficient; The plurality of target movement speeds are determined according to the plurality of first movement speeds and the second movement speeds.

5. The method according to claim 1, characterized in that Determining the respiratory rate and the heart rate according to the plurality of second signals comprises: Determining a first-order phase difference signal according to the plurality of second signals; The breathing frequency and the heart rate are determined according to the first-order phase difference signal.

6. The method according to claim 5, characterized in that Determining the respiratory frequency and the heart rate according to the first-order phase difference signal includes: Performing a fast Fourier transform on the first-order phase difference signal to determine the respiratory frequency; According to the first-order phase difference signal, the heartbeat frequency is determined by a target algorithm; wherein the target algorithm is an adaptive noise complete set empirical mode decomposition algorithm.

7. The method according to claim 1, characterized in that The first signal is a linear frequency modulation signal.

8. A vital signs monitoring device based on FMCW, characterized in that: include: A receiving module, configured to receive a plurality of frames of FMCW radar echo signals, wherein each frame of the FMCW radar echo signal includes a plurality of first signals; A processing module, used to perform processing steps on the multiple frames of FMCW radar echo signals respectively to obtain multiple third signals and multiple target motion phases corresponding to the multiple third signals; A determination module, configured to determine a plurality of second signals according to the plurality of third signals and the plurality of target motion phases, wherein the second signal is the third signal after eliminating the target motion phase; A monitoring module, used to determine the respiratory rate and the heart rate according to the plurality of second signals; and send the respiratory rate and the heart rate to a host computer to monitor the vital signs of a human body; The processing steps include: Determine, based on the plurality of first signals, a target motion phase corresponding to the human body motion and a target range gate where the human body is located; A third signal and a phase value of the third signal are determined according to a plurality of first signals and the target range gate, wherein the third signal is an average signal of the first signals located at the target range gate.

9. A device for performing a FMCW-based vital sign monitoring method, characterized in that: include: processor; a memory for storing processor-executable instructions; When the processor executes the executable instructions, the method according to any one of claims 1 to 7 is implemented.

10. A non-volatile computer-readable storage medium, characterized in that: The device comprises a computer program or an instruction for storing the computer program or the instruction, which, when executed, enables the method according to any one of claims 1 to 7 to be implemented.

Images