Vital sign evaluation method and system based on data analysis

Abstract

The invention discloses a vital sign evaluation method and system based on data analysis, and relates to the technical field of vital sign monitoring. According to the specific scheme, the method comprises the following steps: mixing echo signals from a target area to obtain two paths of intermediate frequency signals, and amplifying the intermediate frequency signals to obtain a first signal and a second signal; then respiratory filtering and heartbeat filtering are carried out to obtain a third signal and a fourth signal, then the respiratory frequency and the heartbeat frequency are determined, and then respiratory filtering parameters and heartbeat filtering parameters are updated; and acquiring the respiratory rate, the heartbeat rate, a plurality of historical respiratory rates and a plurality of historical heartbeat rates at the current moment, determining the heart rate variability and the respiratory depth change corresponding to the current moment, and further determining a vital sign evaluation result based on a vital sign evaluation score formula. The problem that in the prior art, due to the fact that filtering processing cannot follow the frequency change of the vital sign signals in real time, vital sign data are inaccurate can be solved, and the accuracy of the vital sign evaluation result is improved.

Description

Technical Field

[0001] The present application relates to the technical field of vital sign monitoring, and in particular to a method and system for evaluating vital signs based on data analysis. Background Art

[0002] The collection of non-contact vital signs data (such as respiratory rate, heart rate, etc.) is done by processing the echo signal reflected by the human body to obtain the vital signs data. Since the frequency range of the vital signs signal is narrow, filtering is also required in an interference environment. After obtaining the vital signs data, it is necessary to analyze and process the vital signs data to obtain the vital signs evaluation results.

[0003] However, the existing filtering processing cannot follow the frequency changes of vital sign signals in real time, resulting in inaccurate vital sign data, which leads to poor accuracy of vital sign evaluation results and little reference value of the evaluation results. Summary of the invention

[0004] The embodiments of the present application provide a method and system for evaluating vital signs based on data analysis, thereby solving the problem in the prior art that filtering processing cannot follow the frequency changes of vital sign signals in real time, resulting in inaccurate vital sign data, and improving the accuracy of vital sign evaluation results.

[0005] In a first aspect, an embodiment of the present application provides a method for evaluating vital signs based on data analysis, comprising: Acquire the echo signal from the target area, perform mixing processing on the echo signal, and obtain two intermediate frequency signals, wherein the target area is the area where the human body is located, and the echo signal is the reflection signal of the radar signal emitted to the target area; perform intermediate frequency amplification processing on the two intermediate frequency signals to obtain a first signal and a second signal; perform respiratory filtering processing and heartbeat filtering processing according to the first signal and the second signal, respectively, to obtain a third signal and a fourth signal, wherein the first filtering parameter of the respiratory filtering processing is different from the second filtering parameter of the heartbeat filtering processing, and the first filtering parameter and the second filtering parameter both include corresponding filter control voltages and filter bandwidths; determine the respiratory frequency and the heartbeat frequency according to the third signal and the fourth signal, respectively, and store them in a vital sign database; update the first signal and the fourth signal according to the respiratory frequency and the heartbeat frequency, respectively. filtering parameters, second filtering parameters; obtaining the respiratory frequency at the current moment, multiple first historical respiratory frequencies within a first preset time period before the current moment, and the heart rate at the current moment, multiple first historical heart rates within a first preset time period before the current moment from the vital signs database, and determining the heart rate variability corresponding to the current moment and the change in breathing depth corresponding to the current moment according to the respiratory frequency at the current moment, multiple first historical respiratory frequencies, the heart rate at the current moment, and multiple first historical heart rates; determining the vital signs evaluation score based on the vital signs evaluation score formula according to the respiratory frequency at the current moment, the heart rate frequency at the current moment, the heart rate variability corresponding to the current moment, and the change in breathing depth corresponding to the current moment; determining the vital signs evaluation result according to the vital signs evaluation score and the preset evaluation threshold.

[0006] Further, the first filter parameter and the second filter parameter are updated respectively according to the respiratory frequency and the heart rate, including: According to the breathing frequency and the heart rate, based on the control voltage adjustment formula, the filter control voltage corresponding to the first filter parameter and the filter control voltage corresponding to the second filter parameter are updated; according to the power of the third signal corresponding to the breathing frequency and the power of the fourth signal corresponding to the heart rate, based on the bandwidth adjustment formula, the filter bandwidth corresponding to the first filter parameter and the filter bandwidth corresponding to the second filter parameter are updated.

[0007] The control voltage adjustment formula is shown in formula (1): (1) In formula (1), represents the filter control voltage, represents the proportional gain coefficient, Indicates breathing rate or heart rate, represents the filter center frequency corresponding to the breathing frequency or heart rate, represents the integral gain coefficient, represents the duration of the integration time window, represents the integration variable.

[0008] The bandwidth adjustment formula is shown in formula (2): (2) In formula (3), represents the filter bandwidth, represents the minimum bandwidth of the filter, represents the instantaneous adjustment coefficient, Indicates taking the maximum value, represents the power of the third signal corresponding to the respiratory frequency or the power of the fourth signal corresponding to the heart rate, Indicates the preset power threshold, Indicates the preset dead zone width.

[0009] Further, according to the current respiratory frequency, the current heart rate, the heart rate variability corresponding to the current moment, and the change in breathing depth corresponding to the current moment, based on the vital sign evaluation score formula, the vital sign evaluation score is determined, including: According to the current respiratory rate, based on the respiratory evaluation score formula, determine the respiratory evaluation score; according to the current heart rate, based on the heartbeat evaluation score formula, determine the heartbeat evaluation score; according to the heart rate variability corresponding to the current moment, determine the heart rate variability evaluation score; according to the breathing depth change corresponding to the current moment, determine the breathing depth change evaluation score; according to the respiratory frequency evaluation score, heart rate frequency evaluation score, heart rate variability evaluation score, breathing depth change evaluation score, based on the vital signs evaluation score formula, determine the vital signs evaluation score.

[0010] The breathing evaluation score formula is shown in formula (3): (3) In formula (3), represents the respiratory evaluation score, Respiratory rate, represents the optimal breathing rate, Indicates taking the maximum value, Indicates tachypnea frequency, Indicates bradypnea rate.

[0011] The heartbeat evaluation score formula is shown in formula (4): (4) In formula (4), Indicates the heartbeat evaluation score, Indicates the heart rate, represents the optimal heart rate, Indicates taking the maximum value, Indicates the heart rate. Indicates a slow heartbeat rate.

[0012] Further, determining the respiratory rate and the heart rate according to the third signal and the fourth signal respectively includes: The frequency determination step is performed on the third signal and the fourth signal respectively to obtain the respiratory frequency and the heart rate; the frequency determination step includes: determining multiple observation samples according to the third signal or the fourth signal; determining the autocorrelation matrix according to the multiple observation samples; performing eigenvalue decomposition on the autocorrelation matrix to obtain multiple noise subspace basis vectors; constructing a target spectrum according to the multiple noise subspace basis vectors; performing peak search on the target spectrum, and determining the frequency corresponding to the peak as the respiratory frequency or the heart rate.

[0013] Furthermore, the target spectrum is a MUSIC spectrum, and the target spectrum is constructed according to a plurality of noise subspace basis vectors, including: According to multiple noise subspace basis vectors and the target spectrum determination formula, a MUSIC spectrum is constructed.

[0014] The target spectrum determination formula is shown in formula (5): (5) In formula (5), Indicates the frequency The signal strength at represents the order of the autocorrelation matrix, represents the number of observed samples, Indicates frequency The corresponding direction vector, Represents the noise subspace matrix corresponding to multiple noise subspace basis vectors, express The index number of the column vector in .

[0015] Furthermore, the vital sign evaluation score formula is shown in formula (6): (6) In formula (6), represents the vital signs assessment score, represents the respiratory evaluation score, Indicates the heartbeat evaluation score, represents the heart rate variability evaluation score, Indicates the breathing depth change evaluation score, , , , They respectively represent the weight of the respiration evaluation score, the weight of the heartbeat evaluation score, the weight of the heart rate variability evaluation score, and the weight of the breathing depth change evaluation score.

[0016] Furthermore, the method further comprises: According to multiple historical breathing evaluation scores, multiple historical heartbeat evaluation scores, multiple historical heart rate variability evaluation scores, and multiple historical breathing depth change evaluation scores within a second preset time period before the current moment, the weight of the breathing evaluation score, the weight of the heartbeat evaluation score, the weight of the heart rate variability evaluation score, and the weight of the breathing depth change evaluation score are updated respectively.

[0017] In a second aspect, an embodiment of the present application provides a vital sign evaluation system based on data analysis, comprising: A front-end radar module, an intermediate frequency processing module, a control processing module, and a vital sign evaluation module. The intermediate frequency processing module includes a front-end circuit module, a first adaptive filtering module, and a second adaptive filtering module. The front-end radar module is used to transmit a radar signal to a target area, and receive an echo signal from the target area, perform frequency mixing on the echo signal, obtain two intermediate frequency signals, and send them to the front-end circuit module. The target area is the area where the human body is located, and the echo signal is a reflection signal of the radar signal transmitted to the target area. The front-end circuit module is used to perform intermediate frequency amplification on the two intermediate frequency signals to obtain a first signal and a second signal. The first adaptive filtering module is used to perform respiratory filtering according to the first signal and the second signal to obtain a third signal. The second adaptive filtering module is used to perform heartbeat filtering according to the first signal and the second signal to obtain a fourth signal. The first filtering parameter of the respiratory filtering process is different from the second filtering parameter of the heartbeat filtering process, and the first filtering parameter and the second filtering parameter both include the corresponding filter control voltage and filter bandwidth. ; A control processing module, used to determine the respiratory rate and the heart rate according to the third signal and the fourth signal respectively, and store them in the vital signs database; and also used to update the first filter parameter and the second filter parameter according to the respiratory rate and the heart rate respectively; a vital signs evaluation module, used to obtain the respiratory rate at the current moment, a plurality of first historical respiratory rates within a first preset time period before the current moment, and the heart rate at the current moment, and a plurality of first historical heart rates within a first preset time period before the current moment from the vital signs database, and determine the heart rate variability corresponding to the current moment and the change in breathing depth corresponding to the current moment according to the respiratory rate at the current moment, the plurality of first historical respiratory rates, the heart rate at the current moment, and the plurality of first historical heart rates; determine the vital signs evaluation score based on the vital signs evaluation score formula according to the respiratory rate at the current moment, the heart rate at the current moment, the heart rate variability corresponding to the current moment, and the change in breathing depth corresponding to the current moment; and determine the vital signs evaluation result according to the vital signs evaluation score and the preset evaluation threshold.

[0018] Furthermore, the front-stage circuit module includes a front-stage amplifier circuit; the front-stage amplifier circuit includes: A first capacitor C1, one end of the first capacitor C1 is connected to the negative polarity input terminal, and the other end is connected to the first resistor R1; the other end of the first resistor R1 is respectively connected to one end of the third capacitor C3, one end of the third resistor R3, and the negative input terminal of the first operational amplifier OP1; a second capacitor C2, one end of the second capacitor C2 is connected to the positive polarity input terminal, and the other end is connected to the second resistor R2; the other end of the second resistor R2 is respectively connected to one end of the fourth capacitor C4, one end of the fourth resistor R4, and the positive input terminal of the first operational amplifier OP1; the other ends of the fourth capacitor C4 and the fourth resistor R4 are both connected to the reference voltage terminal; the reference voltage terminal is also respectively It is connected to one end of the fifth resistor R5 and one end of the sixth resistor R6; the output end of the first operational amplifier OP1 is respectively connected to the other end of the third capacitor C3, the other end of the third resistor R3, one end of the fifth capacitor C5, and the negative polarity output end; the other end of the fifth resistor R5 is respectively connected to one end of the seventh resistor R7, one end of the sixth capacitor C6, and the negative input end of the second operational amplifier OP2; the other end of the sixth resistor R6 is respectively connected to the other end of the fifth capacitor C5 and the positive input end of the second operational amplifier OP2; the output end of the second operational amplifier OP2 is respectively connected to the other end of the seventh resistor R7, the other end of the sixth capacitor C6, and the positive polarity output end.

[0019] Furthermore, the first adaptive filtering module and the second adaptive filtering module both include an adaptive filtering circuit; the adaptive filtering circuit includes: An eighth resistor R8, one end of the eighth resistor R8 is connected to the intermediate frequency signal input end, and the other end is connected to one end of the ninth resistor R9, one end of the seventh capacitor C7, and an input end of the transconductance operational amplifier OTA; the other ends of the ninth resistor R9 and the seventh capacitor C7 are both grounded; the positive power supply end of the transconductance operational amplifier OTA is respectively connected to the positive working power supply, the collector of the first NPN transistor Q1, and the collector of the second NPN transistor Q2, and the negative power supply end of the transconductance operational amplifier OTA is connected to the negative working power supply; the output end of the transconductance operational amplifier OTA is respectively connected to one end of the tenth resistor R10, one end of the eighth capacitor C8, and the base of the first NPN transistor Q1; the first NPN transistor Q The emitter of the second NPN transistor Q2 is connected to the base of the second NPN transistor Q2, the other end of the eighth capacitor C8 is grounded, the other end of the tenth resistor R10 is respectively connected to one end of the ninth capacitor C9 and the control voltage input end, and the other end of the ninth capacitor C9 is grounded; the emitter of the second NPN transistor Q2 is respectively connected to the intermediate frequency signal output end, one end of the tenth capacitor C10, one end of the eleventh resistor R11, and one end of the twelfth resistor R12; the other end of the tenth capacitor C10 is grounded, and the other end of the eleventh resistor R11 is connected to the negative working power supply; the other end of the twelfth resistor R12 is respectively connected to the bias current input end of the transconductance operational amplifier OTA and one end of the thirteenth resistor R13, and the other end of the thirteenth resistor R13 is grounded.

[0020] 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.

[0021] 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.

[0022] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: In the embodiment of the present application, the first signal and the second signal are obtained by processing the echo signal from the target area, and then the third signal and the fourth signal are obtained by performing respiratory filtering and heartbeat filtering respectively. The respiratory frequency and the heartbeat frequency are determined according to the third signal and the fourth signal, and the results are stored in the vital sign database. The first filtering parameter when performing respiratory filtering and the second filtering parameter when performing heartbeat filtering are updated according to the respiratory frequency and the heartbeat frequency, so as to solve the problem that the filtering processing in the prior art cannot follow the frequency change of the vital sign signal in real time, resulting in inaccurate vital sign data, thereby improving the accuracy of the respiratory frequency and the heartbeat frequency obtained subsequently. Then, according to the respiratory frequency and the heartbeat frequency at the current moment, and the multiple first historical respiratory frequencies and the multiple first historical heartbeat frequencies before the current moment, the heart rate variability corresponding to the current moment and the breathing depth change corresponding to the current moment are determined. According to the respiratory frequency at the current moment, the heartbeat frequency at the current moment, the heart rate variability corresponding to the current moment, and the breathing depth change corresponding to the current moment, the vital sign evaluation score is determined based on the vital sign evaluation score formula. According to the vital sign evaluation score and the preset evaluation threshold, the vital sign evaluation result is accurately determined. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] 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.

[0024] Figure 1 A schematic diagram of a flow chart of a method for evaluating vital signs based on data analysis provided in an embodiment of the present application; Figure 2 A schematic diagram of the composition of a vital sign evaluation system based on data analysis provided in an embodiment of the present application; Figure 3 A circuit diagram of a pre-amplifier circuit provided in an embodiment of the present application; Figure 4 A circuit diagram of an adaptive filtering circuit provided in an embodiment of the present application. DETAILED DESCRIPTION

[0025] 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.

[0026] 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.

[0027] The collection of non-contact vital signs data (such as respiratory rate, heart rate, etc.) is done by processing the echo signal reflected by the human body to obtain the vital signs data. Since the frequency range of the vital signs signal is narrow, filtering is also required in an interference environment. After obtaining the vital signs data, it is necessary to analyze and process the vital signs data to obtain the vital signs evaluation results.

[0028] However, the existing filtering processing cannot follow the frequency changes of vital sign signals in real time, resulting in inaccurate vital sign data, which leads to poor accuracy of vital sign evaluation results and little reference value of the evaluation results.

[0029] For bandpass filters, since the frequency of vital sign signals may drift due to individual differences or changes in physiological state (such as exercise and emotional fluctuations), fixed bandpass filters cannot follow the frequency changes of vital sign signals in real time, which may cause key signals to be attenuated or even lost.

[0030] For the notch filter, if the frequency of the vital sign signal is close to the notch frequency, there is a risk of losing the vital sign signal.

[0031] For designs using Kalman filters, since Kalman filters require preset motion models, but vital signs signals are complex and changeable, the error in the preset motion model will lead to estimation bias, reducing the accuracy of vital sign data extracted from vital sign signals. In addition, the Kalman filter has a large amount of calculations, which will lead to a decrease in real-time performance in multi-target monitoring scenarios.

[0032] Against this background technology, the present disclosure provides a vital sign evaluation method based on data analysis, which can solve the problem in the prior art that filtering processing cannot follow the frequency changes of vital sign signals in real time, resulting in inaccurate vital sign data, and improve the accuracy of vital sign evaluation results.

[0033] The execution subject of the vital sign evaluation method based on data analysis 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 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.

[0034] The method for evaluating vital signs based on data analysis is exemplarily described below with reference to the accompanying drawings.

[0035] Figure 1 : is a flow chart of a method for evaluating vital signs based on data analysis 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 vital sign evaluation method based on data analysis. In the case that 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: S101, acquiring echo signals from a target area, performing mixing processing on the echo signals, and obtaining two intermediate frequency signals.

[0036] The target area is the area where the human body is located, and the echo signal is the reflection signal of the radar signal emitted to the target area.

[0037] For example, a radar sensor may transmit a millimeter wave signal to a target area, and receive an echo signal of the millimeter wave signal in the target area.

[0038] Exemplarily, the radar sensor may be configured with an update frequency of 16 Hz to 20 Hz to meet vital sign detection requirements.

[0039] Exemplarily, after the echo signal is acquired, the echo signal may be mixed with a local oscillator signal to obtain two orthogonal intermediate frequency signals.

[0040] S102 , performing intermediate frequency amplification processing on the two intermediate frequency signals to obtain a first signal and a second signal.

[0041] For example, a voltage follower can be constructed using a high input impedance, low noise operational amplifier to achieve impedance decoupling and shift the two intermediate frequency signals into a processable range by applying a bias voltage.

[0042] S103 . Perform breathing filtering processing and heartbeat filtering processing on the first signal and the second signal, respectively, to obtain a third signal and a fourth signal, respectively.

[0043] The first filter parameter of the respiratory filter processing is different from the second filter parameter of the heartbeat filter processing, and both the first filter parameter and the second filter parameter include a corresponding filter control voltage and a filter bandwidth.

[0044] Exemplarily, the first signal and the second signal can be filtered separately by two bandpass filters, and different filter parameters (i.e., first filtering parameters or second filtering parameters) can be set for the two bandpass filters according to filtering requirements (i.e., whether to perform breathing filtering or heartbeat filtering); the filtering parameters can also include a center frequency.

[0045] It can be understood that the third signal obtained by performing breathing filtering processing corresponds to the breathing of the human body, and the fourth signal obtained by performing heartbeat filtering processing corresponds to the heartbeat of the human body.

[0046] S104. Determine the respiratory rate and the heart rate according to the third signal and the fourth signal respectively, and store them in a vital sign database.

[0047] It can be understood that after obtaining the third signal and the fourth signal, since the third signal and the fourth signal are intermediate frequency signals, the third signal and the fourth signal can be demodulated and baseband processed (analog-to-digital conversion and orthogonal demodulation of the intermediate frequency signal, etc.).

[0048] Exemplarily, the third signal and the fourth signal may be processed according to a vital sign data extraction algorithm to obtain a respiratory frequency and a heart rate, respectively.

[0049] For example, the vital sign data extraction algorithm may include an empirical mode decomposition (EMD) algorithm, a variational mode decomposition (VMD) algorithm, a wavelet transform algorithm, etc., without limitation thereto.

[0050] Exemplarily, the vital signs database can be arranged locally or in the cloud, and the obtained breathing rate and heart rate are matched with the detected person, and are encrypted using the AES-256 (Advanced Encryption Standard-256bit) encryption algorithm and recorded and stored.

[0051] In some implementations, determining the respiratory rate and the heart rate based on the third signal and the fourth signal, respectively, includes: The frequency determination step is performed on the third signal and the fourth signal respectively to obtain the breathing frequency and the heart rate frequency.

[0052] The frequency determination step includes: Determine multiple observation samples based on the third signal or the fourth signal; determine an autocorrelation matrix based on the multiple observation samples; perform eigenvalue decomposition on the autocorrelation matrix to obtain multiple noise subspace basis vectors; construct a target spectrum based on the multiple noise subspace basis vectors; perform peak search on the target spectrum, and determine the frequency corresponding to the peak as the respiratory frequency or the heart rate.

[0053] Exemplarily, one-dimensional fast Fourier transform processing may be performed on the third signal or the fourth signal to obtain a plurality of observation samples.

[0054] For example, assume that the order of the autocorrelation matrix is , the number of observed samples is , then The observed samples can be expressed as .

[0055] Autocorrelation matrix It can be expressed as:

[0056] in, express The conjugate transpose of express The conjugation of.

[0057] For the autocorrelation matrix Perform eigenvalue decomposition to obtain the noise subspace basis vectors. The normalized eigenvector corresponding to the minimum eigenvalue is a set of noise subspace basis vectors. Indicates the number of radar targets.

[0058] Furthermore, the target spectrum is a MUSIC spectrum, and the target spectrum is constructed according to a plurality of noise subspace basis vectors, including: According to multiple noise subspace basis vectors, the MUSIC spectrum is constructed based on the target spectrum determination formula; the target spectrum determination formula is shown in formula (5): (5) In formula (5), Indicates frequency The signal strength at represents the order of the autocorrelation matrix, represents the number of observed samples, Indicates frequency The corresponding direction vector, Represents the noise subspace matrix corresponding to multiple noise subspace basis vectors, express The index number of the column vector in .

[0059] In this way, the respiratory rate and heart rate can be obtained quickly and accurately.

[0060] S105. Update the first filter parameter and the second filter parameter according to the respiratory frequency and the heart rate respectively.

[0061] Exemplarily, the obtained respiratory frequency and heart rate can be used to update parameters such as filter control voltage and filter bandwidth, reduce the offset between filter parameters and vital signs data, avoid signal loss, and thus improve the accuracy of subsequently obtained respiratory frequency and heart rate.

[0062] Specifically, S105 may include S201 and S202.

[0063] S201. Update a filter control voltage corresponding to a first filter parameter and a filter control voltage corresponding to a second filter parameter according to a respiratory frequency and a heart rate based on a control voltage adjustment formula.

[0064] The control voltage adjustment formula is shown in formula (1): (1) In formula (1), represents the filter control voltage, represents the proportional gain coefficient, Indicates breathing rate or heart rate, represents the filter center frequency corresponding to the breathing frequency or heart rate, represents the integral gain coefficient, represents the duration of the integration time window, represents the integration variable.

[0065] For example, considering adjusting the speed while avoiding oscillation, the proportional gain coefficient can be taken as 0.8 , the integral gain coefficient can be set to 0.05 ; In order to avoid errors caused by infinite accumulation of integral terms, the duration of the integral time window is set to 5 seconds.

[0066] Exemplarily, after obtaining the filter control voltage corresponding to the respiratory frequency, the filter control voltage for respiratory filtering processing can be adjusted; after obtaining the filter control voltage corresponding to the heartbeat frequency, the filter control voltage for heartbeat filtering processing can be adjusted.

[0067] S202. Update the filter bandwidth corresponding to the first filter parameter and the filter bandwidth corresponding to the second filter parameter based on a bandwidth adjustment formula according to the power of the third signal corresponding to the respiratory frequency and the power of the fourth signal corresponding to the heart rate frequency.

[0068] The bandwidth adjustment formula is shown in formula (2): (2) In formula (3), represents the filter bandwidth, represents the minimum bandwidth of the filter, represents the instantaneous adjustment coefficient, Indicates taking the maximum value, represents the power of the third signal corresponding to the respiratory frequency or the power of the fourth signal corresponding to the heart rate, Indicates the preset power threshold, Indicates the preset dead zone width.

[0069] For example, the minimum bandwidth of the filter can be 3 ; Considering the control response speed, the instantaneous adjustment coefficient can be taken as 0.15 ; The preset power threshold can be -40 ; To avoid unnecessary frequent adjustments, the preset dead zone width can be set to 0.15 , that is, only in The filter bandwidth is adjusted accordingly.

[0070] Exemplarily, the power of the third signal or the fourth signal may be determined by spectrum analyzer measurement, fast Fourier transform, or the like, without limitation thereto.

[0071] S106. Obtain the respiratory frequency at the current moment, multiple first historical respiratory frequencies within a first preset time period before the current moment, and the heart rate at the current moment, and multiple first historical heart rates within a first preset time period before the current moment from the vital signs database; determine the heart rate variability corresponding to the current moment and the change in breathing depth corresponding to the current moment based on the respiratory frequency at the current moment, the multiple first historical respiratory frequencies, the heart rate at the current moment, and the multiple first historical heart rates.

[0072] Exemplarily, the first preset duration may be 5 minutes or 10 minutes, without limitation.

[0073] For example, the heart rate variability corresponding to the current moment can be determined based on the heart rate frequency at the current moment and a plurality of first historical heart rate frequencies and the heart rate variability calculation formula. The heart rate variability calculation formula is shown in formula (7): (7) In formula (7), Indicates the heart rate variability corresponding to the current moment, represents the sum of the number of first historical heartbeat frequencies and the heartbeat frequency at the current moment (for example, if the number of first historical heartbeat frequencies is 9, then ), express The first of the heart rate Heart rate, express The average heart rate.

[0074] For example, the breathing depth change corresponding to the current moment can be determined based on the breathing frequency at the current moment and the first plurality of historical breathing frequencies and the breathing depth change calculation formula. The breathing depth change calculation formula is shown in formula (8): (8) In formula (8), Indicates the change in breathing depth corresponding to the current moment. represents the sum of the number of first historical respiratory frequencies and the respiratory frequency at the current moment (for example, if the number of first historical respiratory frequencies is 9, then ), express The respiratory rate of Respiratory rate, express The average breathing rate.

[0075] S107. Determine a vital sign evaluation score based on the vital sign evaluation score formula according to the current respiratory frequency, the current heart rate, the heart rate variability corresponding to the current moment, and the change in breathing depth corresponding to the current moment.

[0076] Specifically, S107 may include S301 to S305.

[0077] S301 . Determine a breathing evaluation score according to the current breathing frequency and based on a breathing evaluation score formula.

[0078] The breathing evaluation score formula is shown in formula (3): (3) In formula (3), represents the respiratory evaluation score, Respiratory rate, represents the optimal breathing rate, Indicates taking the maximum value, Indicates tachypnea frequency, Indicates bradypnea rate.

[0079] For example, the optimal breathing rate may be determined based on the age of the detected person.

[0080] S302: Determine a heartbeat evaluation score according to the current heartbeat frequency and the heartbeat evaluation score formula.

[0081] The heartbeat evaluation score formula is shown in formula (4): (4) In formula (4), Indicates the heartbeat evaluation score, Indicates the heart rate, represents the optimal heart rate, Indicates taking the maximum value, Indicates the heart rate. Indicates a slow heartbeat rate.

[0082] For example, the optimal heart rate may be determined based on the age of the person being detected.

[0083] S303: Determine a heart rate variability evaluation score according to the heart rate variability corresponding to the current moment.

[0084] For example, the heart rate variability corresponding to the current moment may be determined as the heart rate variability evaluation score.

[0085] S304: Determine a breathing depth change evaluation score according to the breathing depth change corresponding to the current moment.

[0086] For example, the breathing depth change corresponding to the current moment may be determined as the breathing depth change evaluation score.

[0087] S305. Determine a vital sign evaluation score based on the vital sign evaluation score formula according to the respiratory rate evaluation score, the heart rate evaluation score, the heart rate variability evaluation score, and the respiratory depth change evaluation score.

[0088] Exemplarily, the vital sign evaluation score formula may be a model for calculating the sum of a respiratory rate evaluation score, a heart rate evaluation score, a heart rate variability evaluation score, and a respiratory depth change evaluation score, and there is no limitation to this.

[0089] In some embodiments, the vital sign evaluation score formula may be as shown in formula (6): (6) In formula (6), represents the vital signs assessment score, represents the respiratory evaluation score, Indicates the heartbeat evaluation score, represents the heart rate variability evaluation score, Indicates the breathing depth change evaluation score, , , , They respectively represent the weight of the respiration evaluation score, the weight of the heartbeat evaluation score, the weight of the heart rate variability evaluation score, and the weight of the breathing depth change evaluation score.

[0090] For example, the weight of the breathing evaluation score, the weight of the heartbeat evaluation score, the weight of the heart rate variability evaluation score, and the weight of the breathing depth change evaluation score can be preset according to the age, disease status, etc. of the person being tested, and there is no restriction on this.

[0091] It can be understood that the vital sign evaluation score is between 0 and 1, and the larger the vital sign evaluation score is, the better the health status is.

[0092] Furthermore, the weight of the breathing evaluation score, the weight of the heartbeat evaluation score, the weight of the heart rate variability evaluation score, and the weight of the breathing depth change evaluation score can be updated respectively based on multiple historical breathing evaluation scores, multiple historical heartbeat evaluation scores, multiple historical heart rate variability evaluation scores, and multiple historical breathing depth change evaluation scores within a second preset time period before the current moment.

[0093] Exemplarily, the means and standard deviations of multiple historical breathing evaluation scores, multiple historical heartbeat evaluation scores, multiple historical heart rate variability evaluation scores, and multiple historical breathing depth change evaluation scores can be calculated respectively. When the fluctuation of a certain evaluation score is large, its corresponding weight can be increased to increase its influence on the vital signs evaluation results. Otherwise, the weight can be reduced, so that the vital signs evaluation results can better reflect the situation of unstable factors and improve the accuracy of the vital signs evaluation results.

[0094] In some possible embodiments, the weight of the breathing evaluation score, the weight of the heartbeat evaluation score, the weight of the heart rate variability evaluation score, and the weight of the breathing depth change evaluation score can also be updated separately according to the age, illness or exercise status of the person being tested.

[0095] S108. Determine the vital sign evaluation result according to the vital sign evaluation score and the preset evaluation threshold.

[0096] Continuing with the above example, the preset evaluation thresholds may include (0, 0.5), [0.5, 0.65) poor, [0.65, 0.75) fair, and [0.75, 1) good, and the corresponding vital sign evaluation results are critical, poor, fair, and good, respectively.

[0097] In the embodiment of the present application, the first signal and the second signal are obtained by processing the echo signal from the target area, and then the third signal and the fourth signal are obtained by performing respiratory filtering and heartbeat filtering respectively. The respiratory frequency and the heartbeat frequency are determined according to the third signal and the fourth signal, and the results are stored in the vital sign database. The first filtering parameter when performing respiratory filtering and the second filtering parameter when performing heartbeat filtering are updated according to the respiratory frequency and the heartbeat frequency, so as to solve the problem that the filtering processing in the prior art cannot follow the frequency change of the vital sign signal in real time, resulting in inaccurate vital sign data, thereby improving the accuracy of the respiratory frequency and the heartbeat frequency obtained subsequently. Then, according to the respiratory frequency and the heartbeat frequency at the current moment, and the multiple first historical respiratory frequencies and the multiple first historical heartbeat frequencies before the current moment, the heart rate variability corresponding to the current moment and the breathing depth change corresponding to the current moment are determined. According to the respiratory frequency at the current moment, the heartbeat frequency at the current moment, the heart rate variability corresponding to the current moment, and the breathing depth change corresponding to the current moment, the vital sign evaluation score is determined based on the vital sign evaluation score formula. According to the vital sign evaluation score and the preset evaluation threshold, the vital sign evaluation result is accurately determined.

[0098] 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).

[0099] like Figure 2 As shown, the embodiment of the present application also provides a vital sign evaluation system based on data analysis. The system includes: Front-end radar module 410, intermediate frequency processing module 420, control processing module 430, vital sign evaluation module 440, intermediate frequency processing module 420 includes front-stage circuit module 421, first adaptive filtering module 422, second adaptive filtering module 423; The front-end radar module 410 is used to transmit a radar signal to a target area, receive an echo signal from the target area, perform frequency mixing on the echo signal, obtain two intermediate frequency signals, and send them to the front-end circuit module; wherein the target area is the area where the human body is located, and the echo signal is a reflection signal of the radar signal transmitted to the target area; The front-stage circuit module 421 is used to perform intermediate frequency amplification processing on the two intermediate frequency signals to obtain a first signal and a second signal; A first adaptive filtering module 422 is used to perform respiratory filtering processing according to the first signal and the second signal to obtain a third signal; a second adaptive filtering module 423 is used to perform heartbeat filtering processing according to the first signal and the second signal to obtain a fourth signal; wherein the first filtering parameter of the respiratory filtering processing is different from the second filtering parameter of the heartbeat filtering processing, and the first filtering parameter and the second filtering parameter both include a corresponding filter control voltage and a filter bandwidth; The control processing module 430 is used to determine the respiratory rate and the heart rate according to the third signal and the fourth signal respectively, and store them in the vital sign database; and is also used to update the first filter parameter and the second filter parameter according to the respiratory rate and the heart rate respectively; The vital signs evaluation module 440 is used to obtain the respiratory frequency at the current moment, multiple first historical respiratory frequencies within a first preset time period before the current moment, and the heart rate at the current moment, and multiple first historical heart rates within a first preset time period before the current moment from the vital signs database; determine the heart rate variability corresponding to the current moment and the change in breathing depth corresponding to the current moment based on the respiratory frequency at the current moment, the multiple first historical respiratory frequencies, the heart rate at the current moment, and the multiple first historical heart rates; determine the vital signs evaluation score based on the vital signs evaluation score formula based on the respiratory frequency at the current moment, the heart rate variability corresponding to the current moment, and the change in breathing depth corresponding to the current moment; determine the vital signs evaluation result based on the vital signs evaluation score and the preset evaluation threshold.

[0100] Further, Figure 3 The circuit diagram of the preamplifier circuit provided in the embodiment of the present application is shown in FIG. Figure 3 The front-stage circuit module 421 includes a front-stage amplifier circuit; the front-stage amplifier circuit includes: The first capacitor C1 has one end connected to the negative input end (i.e. Figure 3The other end of the first resistor R1 is connected to one end of the third capacitor C3, one end of the third resistor R3, and the negative input terminal of the first operational amplifier OP1 respectively.

[0101] The second capacitor C2 has one end connected to the positive input end (i.e. Figure 3 IF_P in the figure), and the other end is connected to the second resistor R2; the other end of the second resistor R2 is respectively connected to one end of the fourth capacitor C4, one end of the fourth resistor R4, and the positive input terminal of the first operational amplifier OP1; the other ends of the fourth capacitor C4 and the fourth resistor R4 are both connected to the reference voltage terminal (i.e. Figure 3 The reference voltage terminal is also connected to one end of the fifth resistor R5 and one end of the sixth resistor R6 respectively.

[0102] The output terminal of the first operational amplifier OP1 is respectively connected to the other end of the third capacitor C3, the other end of the third resistor R3, one end of the fifth capacitor C5, and the negative polarity output terminal (i.e. Figure 3 IF_L) connection in.

[0103] The other end of the fifth resistor R5 is respectively connected to one end of the seventh resistor R7, one end of the sixth capacitor C6, and the negative input end of the second operational amplifier OP2; the other end of the sixth resistor R6 is respectively connected to the other end of the fifth capacitor C5 and the positive input end of the second operational amplifier OP2.

[0104] The output end of the second operational amplifier OP2 is connected to the other end of the seventh resistor R7, the other end of the sixth capacitor C6, and the positive output end (i.e. Figure 3 IF_H) connection in.

[0105] Exemplarily, a dual-channel operational amplifier may be used to implement the first operational amplifier OP1 and the second operational amplifier OP2 .

[0106] The preamplifier circuit is used for impedance matching, signal isolation and amplitude conditioning. The present invention uses a high input impedance, low noise operational amplifier to build a voltage follower, realizes impedance decoupling and translates the bipolar signal into a range that can be processed by the analog-to-digital converter by adding a bias voltage.

[0107] Furthermore, the first adaptive filtering module and the second adaptive filtering module both include an adaptive filtering circuit. Figure 4 A schematic diagram of a circuit of an adaptive filtering circuit provided in an embodiment of the present application. Figure 4 , the adaptive filtering circuit includes: An eighth resistor R8, one end of which is connected to the intermediate frequency signal input end (i.e. Figure 4The other end of the ninth resistor R9 and the seventh capacitor C7 are connected to ground.

[0108] The positive power supply terminal of the transconductance operational amplifier OTA is connected to the positive working power supply (i.e. Figure 4 The negative power supply terminal of the transconductance operational amplifier OTA is connected to the negative working power supply (i.e. Figure 4 -VCC) connection in the

[0109] The output end of the transconductance operational amplifier OTA is respectively connected to one end of the tenth resistor R10, one end of the eighth capacitor C8, and the base of the first NPN transistor Q1; the emitter of the first NPN transistor Q1 is connected to the base of the second NPN transistor Q2, the other end of the eighth capacitor C8 is grounded, and the other end of the tenth resistor R10 is respectively connected to one end of the ninth capacitor C9 and the control voltage input end (i.e. Figure 4 The other end of the ninth capacitor C9 is grounded.

[0110] The emitter of the second NPN transistor Q2 is connected to the intermediate frequency signal output terminal (i.e. Figure 4 IF_OUT in the figure), one end of the tenth capacitor C10, one end of the eleventh resistor R11, and one end of the twelfth resistor R12 are connected; the other end of the tenth capacitor C10 is grounded, and the other end of the eleventh resistor R11 is connected to the negative working power supply (i.e. Figure 4 -VCC) connection in the

[0111] The other end of the twelfth resistor R12 is respectively connected to the bias current input end of the transconductance operational amplifier OTA and one end of the thirteenth resistor R13, and the other end of the thirteenth resistor R13 is grounded.

[0112] It can be understood that the other input terminal of the transconductance operational amplifier OTA is not connected to other components or ports.

[0113] The beneficial effects and specific implementation methods of the system embodiment can be referred to the aforementioned method embodiment, and will not be described in detail here.

[0114] Some modules in the system 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.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] 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.

[0122] 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.

[0123] 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 method for evaluating vital signs based on data analysis, characterized in that: include: Acquire an echo signal from a target area, perform frequency mixing on the echo signal, and obtain two intermediate frequency signals, wherein the target area is an area where a human body is located, and the echo signal is a reflection signal of a radar signal emitted to the target area; Performing intermediate frequency amplification processing on the two intermediate frequency signals to obtain a first signal and a second signal; According to the first signal and the second signal, respectively, a breathing filter process and a heartbeat filter process are performed to obtain a third signal and a fourth signal, respectively, wherein a first filter parameter of the breathing filter process is different from a second filter parameter of the heartbeat filter process, and both the first filter parameter and the second filter parameter include a corresponding filter control voltage and a filter bandwidth; Determine the respiratory rate and the heart rate according to the third signal and the fourth signal respectively, and store them in a vital sign database; updating the first filtering parameter and the second filtering parameter respectively according to the breathing frequency and the heart rate; Obtaining from the vital signs database the respiratory frequency at the current moment, a plurality of first historical respiratory frequencies within a first preset time period before the current moment, and the heart rate at the current moment, and a plurality of first historical heart rates within a first preset time period before the current moment, and determining the heart rate variability corresponding to the current moment and the breathing depth change corresponding to the current moment according to the respiratory frequency at the current moment, the plurality of first historical respiratory frequencies, the heart rate at the current moment, and the plurality of first historical heart rates; According to the current respiratory rate, the current heart rate, the heart rate variability corresponding to the current moment, and the change in breathing depth corresponding to the current moment, based on the vital sign evaluation score formula, a vital sign evaluation score is determined; A vital sign evaluation result is determined according to the vital sign evaluation score and a preset evaluation threshold.

2. The method according to claim 1, characterized in that The updating of the first filtering parameter and the second filtering parameter respectively according to the breathing frequency and the heart rate comprises: According to the respiratory frequency and the heart rate, based on a control voltage adjustment formula, updating the filter control voltage corresponding to the first filter parameter and the filter control voltage corresponding to the second filter parameter; updating the filter bandwidth corresponding to the first filter parameter and the filter bandwidth corresponding to the second filter parameter based on a bandwidth adjustment formula according to the power of the third signal corresponding to the respiratory frequency and the power of the fourth signal corresponding to the heartbeat frequency; The control voltage adjustment formula is shown in formula (1): （1） In formula (1), represents the filter control voltage, represents the proportional gain coefficient, Indicates breathing rate or heart rate, represents the filter center frequency corresponding to the breathing frequency or heart rate, represents the integral gain coefficient, represents the duration of the integration time window, represents the integral variable; The bandwidth adjustment formula is shown in formula (2): （2） In formula (3), represents the filter bandwidth, represents the minimum bandwidth of the filter, represents the instantaneous adjustment coefficient, Indicates taking the maximum value, represents the power of the third signal corresponding to the respiratory frequency or the power of the fourth signal corresponding to the heart rate, Indicates the preset power threshold, Indicates the preset dead zone width.

3. The method according to claim 1, characterized in that: The method of determining the vital sign evaluation score based on the current respiratory frequency, the current heart rate, the heart rate variability corresponding to the current moment, and the breathing depth change corresponding to the current moment, based on the vital sign evaluation score formula, includes: According to the current respiratory frequency, based on the respiratory evaluation score formula, determine the respiratory evaluation score; According to the current heart rate, a heart rate evaluation score is determined based on the heart rate evaluation score formula; Determine a heart rate variability evaluation score according to the heart rate variability corresponding to the current moment; Determine a breathing depth change evaluation score according to the breathing depth change corresponding to the current moment; Determine a vital sign evaluation score based on the vital sign evaluation score formula according to the respiratory rate evaluation score, the heart rate evaluation score, the heart rate variability evaluation score, and the respiratory depth change evaluation score; The breathing evaluation score formula is shown in formula (3): （3） In formula (3), represents the respiratory evaluation score, Respiratory rate, represents the optimal breathing rate, Indicates taking the maximum value, Indicates tachypnea frequency, Indicates bradypnea rate; The heartbeat evaluation score formula is shown in formula (4): （4） In formula (4), Indicates the heartbeat evaluation score, Indicates the heart rate, represents the optimal heart rate, Indicates taking the maximum value, Indicates the heart rate. Indicates a slow heartbeat rate.

4. The method according to claim 1, characterized in that The step of determining the respiratory rate and the heart rate according to the third signal and the fourth signal respectively includes: Performing frequency determination steps on the third signal and the fourth signal respectively to obtain the breathing frequency and the heart rate frequency; The frequency determination step comprises: Determining a plurality of observation samples according to the third signal or the fourth signal; Determining an autocorrelation matrix based on the multiple observation samples; Performing eigenvalue decomposition on the autocorrelation matrix to obtain a plurality of noise subspace basis vectors; constructing a target spectrum according to the multiple noise subspace basis vectors; A peak search is performed on the target frequency spectrum, and the frequency corresponding to the peak is determined as the respiratory frequency or the heart rate frequency.

5. The method according to claim 4, characterized in that The target spectrum is a MUSIC spectrum, and constructing the target spectrum according to the multiple noise subspace basis vectors includes: According to the multiple noise subspace basis vectors, based on a target spectrum determination formula, construct a MUSIC spectrum; The target spectrum determination formula is shown in formula (5): （5） In formula (5), Indicates the frequency The signal strength at represents the order of the autocorrelation matrix, represents the number of observed samples, Indicates frequency The corresponding direction vector, represents the noise subspace matrix corresponding to the multiple noise subspace basis vectors, express The index number of the column vector in .

6. The method according to claim 3, characterized in that The vital sign evaluation score formula is shown in formula (6): （6） In formula (6), represents the vital signs assessment score, represents the respiratory evaluation score, represents the heartbeat evaluation score, represents the heart rate variability evaluation score, represents the breathing depth change evaluation score, , , , They respectively represent the weight of the respiration evaluation score, the weight of the heartbeat evaluation score, the weight of the heart rate variability evaluation score, and the weight of the breathing depth change evaluation score.

7. The method according to claim 6, characterized in that The method further comprises: According to multiple historical breathing evaluation scores, multiple historical heartbeat evaluation scores, multiple historical heart rate variability evaluation scores, and multiple historical breathing depth change evaluation scores within a second preset time period before the current moment, the weights of the breathing evaluation scores, the weights of the heartbeat evaluation scores, the weights of the heart rate variability evaluation scores, and the weights of the breathing depth change evaluation scores are updated respectively.

8. A vital sign evaluation system based on data analysis, characterized in that: include: A front-end radar module, an intermediate frequency processing module, a control processing module, and a vital sign evaluation module, wherein the intermediate frequency processing module includes a front-stage circuit module, a first adaptive filtering module, and a second adaptive filtering module; The front-end radar module is used to transmit a radar signal to a target area, receive an echo signal from the target area, perform frequency mixing on the echo signal, obtain two intermediate frequency signals, and send them to the front-stage circuit module; wherein the target area is an area where a human body is located, and the echo signal is a reflection signal of the radar signal transmitted to the target area; The front-stage circuit module is used to perform intermediate frequency amplification processing on the two intermediate frequency signals to obtain a first signal and a second signal; The first adaptive filtering module is used to perform respiratory filtering processing according to the first signal and the second signal to obtain a third signal; the second adaptive filtering module is used to perform heartbeat filtering processing according to the first signal and the second signal to obtain a fourth signal; wherein the first filtering parameter of the respiratory filtering processing is different from the second filtering parameter of the heartbeat filtering processing, and the first filtering parameter and the second filtering parameter both include a corresponding filter control voltage and a filter bandwidth; The control processing module is used to determine the respiratory rate and the heart rate according to the third signal and the fourth signal respectively, and store them in the vital signs database; and is also used to update the first filtering parameter and the second filtering parameter according to the respiratory rate and the heart rate respectively; The vital signs evaluation module is used to obtain the respiratory frequency at the current moment, multiple first historical respiratory frequencies within a first preset time period before the current moment, and the heart rate at the current moment, and multiple first historical heart rates within a first preset time period before the current moment from the vital signs database; determine the heart rate variability corresponding to the current moment and the breathing depth change corresponding to the current moment according to the respiratory frequency at the current moment, the multiple first historical respiratory frequencies, the heart rate at the current moment, and the multiple first historical heart rates; determine the vital signs evaluation score based on the vital signs evaluation score formula according to the respiratory frequency at the current moment, the heart rate variability corresponding to the current moment, and the breathing depth change corresponding to the current moment; and determine the vital signs evaluation result according to the vital signs evaluation score and a preset evaluation threshold.

9. The system according to claim 8, characterized in that The front-stage circuit module includes a front-stage amplifier circuit; the front-stage amplifier circuit includes: A first capacitor C1, one end of the first capacitor C1 is connected to the negative polarity input terminal, and the other end is connected to the first resistor R1; the other end of the first resistor R1 is respectively connected to one end of the third capacitor C3, one end of the third resistor R3, and the negative input terminal of the first operational amplifier OP1; A second capacitor C2, one end of the second capacitor C2 is connected to the positive polarity input terminal, and the other end is connected to the second resistor R2; the other end of the second resistor R2 is respectively connected to one end of the fourth capacitor C4, one end of the fourth resistor R4, and the positive input terminal of the first operational amplifier OP1; the other ends of the fourth capacitor C4 and the fourth resistor R4 are both connected to the reference voltage terminal; the reference voltage terminal is also respectively connected to one end of the fifth resistor R5 and one end of the sixth resistor R6; The output end of the first operational amplifier OP1 is respectively connected to the other end of the third capacitor C3, the other end of the third resistor R3, one end of the fifth capacitor C5, and the negative polarity output end; The other end of the fifth resistor R5 is respectively connected to one end of the seventh resistor R7, one end of the sixth capacitor C6, and the negative input end of the second operational amplifier OP2; the other end of the sixth resistor R6 is respectively connected to the other end of the fifth capacitor C5 and the positive input end of the second operational amplifier OP2; The output end of the second operational amplifier OP2 is connected to the other end of the seventh resistor R7, the other end of the sixth capacitor C6, and the positive output end respectively.

10. The system according to claim 8, characterized in that The first adaptive filtering module and the second adaptive filtering module both include an adaptive filtering circuit; the adaptive filtering circuit includes: an eighth resistor R8, one end of the eighth resistor R8 is connected to the intermediate frequency signal input end, and the other end is connected to one end of a ninth resistor R9, one end of a seventh capacitor C7, and an input end of a transconductance operational amplifier OTA; the other ends of the ninth resistor R9 and the seventh capacitor C7 are both grounded; The positive power supply terminal of the transconductance operational amplifier OTA is respectively connected to the positive working power supply, the collector of the first NPN transistor Q1, and the collector of the second NPN transistor Q2, and the negative power supply terminal of the transconductance operational amplifier OTA is connected to the negative working power supply; The output end of the transconductance operational amplifier OTA is respectively connected to one end of the tenth resistor R10, one end of the eighth capacitor C8, and the base of the first NPN transistor Q1; the emitter of the first NPN transistor Q1 is connected to the base of the second NPN transistor Q2, the other end of the eighth capacitor C8 is grounded, the other end of the tenth resistor R10 is respectively connected to one end of the ninth capacitor C9 and the control voltage input end, and the other end of the ninth capacitor C9 is grounded; The emitter of the second NPN transistor Q2 is respectively connected to the intermediate frequency signal output terminal, one end of the tenth capacitor C10, one end of the eleventh resistor R11, and one end of the twelfth resistor R12; the other end of the tenth capacitor C10 is grounded, and the other end of the eleventh resistor R11 is connected to the negative working power supply; The other end of the twelfth resistor R12 is respectively connected to the bias current input end of the transconductance operational amplifier OTA and one end of the thirteenth resistor R13, and the other end of the thirteenth resistor R13 is grounded.

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