Heart rate and breath collecting device based on microwave radar technology

Abstract

The invention relates to the technical field of medicine, in particular to a heart rate and breath acquisition device based on microwave radar technology, which comprises a signal acquisition module, a data processing module, a vital sign extraction module and an output module, the signal acquisition module is used for transmitting a microwave signal and receiving an echo signal reflected by the chest of a human body; the data processing module is used for digitalizing and preprocessing the echo signals and generating a distance-time phase matrix containing human chest micro-motion information; the vital sign extraction module is used for positioning the position of a target thoracic cavity from the distance-time phase matrix, extracting a thoracic cavity micro-displacement signal and separating a respiration signal component and a heartbeat signal component; and the output module is used for calculating and outputting the respiratory rate and the heart rate according to the separated signal components. Therefore, the technical problem that weak heartbeat signals are difficult to accurately separate from strong breathing interference due to overlapping of breathing harmonics and heartbeat frequency bands in the prior art is solved.

Description

Technical Field

[0001] This invention relates to the field of medical technology, and in particular to a heart rate and respiration acquisition device based on microwave radar technology. Background Technology

[0002] In recent years, non-contact vital sign monitoring technology based on microwave radar has been widely used in fields such as sleep monitoring and infant monitoring due to its advantages such as being non-contact and penetrating obstructions. Its basic principle is: the radar emits electromagnetic waves to irradiate the human chest cavity. Due to the periodic micro-movements of the chest wall caused by breathing and heartbeat, the phase of the reflected echo is modulated. By demodulating the phase signal, the breathing and heartbeat waveforms can be extracted.

[0003] However, existing technologies have serious shortcomings in signal separation: respiration causes significant chest wall displacement (up to 4-12 mm), while heartbeat displacement is only 0.1-0.5 mm, a stark difference in amplitude. More importantly, the higher harmonics of the respiratory signal often overlap with the heartbeat frequency band (0.8-3 Hz). Traditional bandpass filters or simple frequency domain filtering methods are insufficient to effectively separate the heartbeat signal obscured by respiratory harmonics. Especially when breathing is irregular or there is slight body movement, the heartbeat signal is often completely submerged or suffers from severe mode aliasing, leading to decreased accuracy or even failure of heart rate monitoring.

[0004] Therefore, there is an urgent need for a microwave radar heart rate and respiration acquisition device that can accurately separate weak heartbeat signals from strong respiratory interference. Summary of the Invention

[0005] The purpose of this invention is to provide a heart rate and respiration acquisition device based on microwave radar technology, which aims to solve the technical problem in the prior art that it is difficult to accurately separate weak heartbeat signals from strong respiratory interference due to the overlap of respiratory harmonics and heartbeat frequency bands.

[0006] To achieve the above objectives, the present invention provides a heart rate and respiration acquisition device based on microwave radar technology, comprising a signal acquisition module, a data processing module, a vital signs extraction module, and an output module; the signal acquisition module, the data processing module, the vital signs extraction module, and the output module are connected in sequence. The signal acquisition module is used to transmit microwave signals and receive echo signals reflected from the human chest cavity; The data processing module is used to digitize and preprocess the echo signal to generate a distance-time phase matrix containing micro-movement information of the human chest cavity; The vital signs extraction module is used to locate the target chest cavity from the distance-time phase matrix, extract the chest cavity micro-displacement signal, and separate the respiratory signal component and the heartbeat signal component. The output module is used to calculate and output the respiratory rate and heart rate based on the separated signal components.

[0007] The signal acquisition module includes a radar front-end unit and a radio frequency transceiver unit; the radio frequency transceiver unit is connected to the radar front-end unit. The radar front-end unit includes at least one transmitting antenna and multiple receiving antennas arranged in an array, for transmitting frequency-modulated continuous wave radar signals to the target under test and receiving echo signals modulated by thoracic cavity micro-motion. The radio frequency transceiver unit is used to perform frequency mixing and down-conversion processing on the echo signal and output an intermediate frequency analog signal.

[0008] The data processing module includes an analog-to-digital conversion unit, a range-dimensional transformation unit, and a static clutter suppression unit; the analog-to-digital conversion unit, the range-dimensional transformation unit, and the static clutter suppression unit are connected in sequence. The analog-to-digital converter unit is used to convert intermediate frequency analog signals into intermediate frequency digital signals; The distance-dimensional transformation unit is used to perform a distance-dimensional fast Fourier transform on the intermediate frequency digital signal to generate a distance-time phase matrix. The static clutter suppression unit is used to perform moving target display filtering on the range-time phase matrix to filter out clutter from stationary background objects.

[0009] The vital signs extraction module includes a target localization unit, a phase demodulation unit, and a signal separation unit; the target localization unit, the phase demodulation unit, and the signal separation unit are connected in sequence. The target positioning unit is used to locate the target distance index of the chest cavity of the target under test according to the spatial distribution of energy in the distance-time phase matrix. The phase demodulation unit is used to extract the phase information of the slow-time signal corresponding to the target distance index and perform phase unwinding processing to obtain the original thoracic cavity micro-displacement signal. The signal separation unit is used to separate the respiratory signal component and the heartbeat signal component from the original chest cavity micro-displacement signal through an adaptive nonlinear non-stationary signal decomposition algorithm.

[0010] The target positioning unit includes an energy peak search subunit and a dynamic tracking subunit; the dynamic tracking subunit is connected to the energy peak search subunit. The energy peak search subunit is used to search for the distance index corresponding to the maximum energy value in the distance dimension data of each frame; The dynamic tracking subunit is used to establish the target trajectory within a continuous time frame, adaptively update the target distance index when the target under test is displaced, and output the updated target distance index to the phase demodulation unit.

[0011] The phase demodulation unit includes an orthogonal demodulation subunit and a phase expansion subunit; the phase expansion subunit is connected to the orthogonal demodulation subunit. The orthogonal demodulation subunit is used to calculate the instantaneous phase based on the in-phase component and the orthogonal component corresponding to the target distance index; The phase expansion subunit is used to detect and correct the jump points in the instantaneous phase and restore the continuous thoracic displacement trajectory.

[0012] The signal separation unit includes a preprocessing subunit, a baseline drift suppression subunit, an adaptive decomposition subunit, and a mode reconstruction subunit; the preprocessing subunit, the baseline drift suppression subunit, the adaptive decomposition subunit, and the mode reconstruction subunit are connected in sequence. The preprocessing subunit is used to remove the mean and trend term from the original thoracic cavity micro-displacement signal. The baseline drift suppression subunit is used to filter out low-frequency interference caused by large-amplitude movement of the main body; The adaptive decomposition subunit uses an adaptive decomposition algorithm to decompose the signal into multiple intrinsic mode functions. The modal reconstruction subunit is used to reconstruct the respiratory signal component and the heartbeat signal component respectively based on the frequency characteristics of each intrinsic mode function.

[0013] The adaptive decomposition algorithm used in the adaptive decomposition subunit is a variational mode decomposition algorithm, and the number of modes K is adaptively determined by the center frequency observation method: the center frequency of each mode is calculated sequentially when K takes different values. When the difference between the center frequency of the newly added mode and the center frequency of the existing mode is less than a preset threshold, it is determined that over-decomposition has occurred, and the previous K value is taken as the optimal number of modes.

[0014] The heart rate and respiration acquisition device based on microwave radar technology also includes a motion artifact processing module, which is connected to the vital signs extraction module and the output module.

[0015] The motion artifact processing module is used to monitor and respond to motion interference.

[0016] The motion artifact processing module includes a mutation detection unit and a data preservation unit; the data preservation unit is connected to the mutation detection unit. The mutation detection unit is used to monitor amplitude mutations in the original thoracic cavity micro-movement displacement signal. When the mutation amplitude exceeds a preset threshold, it is determined to be a body motion interference. The data holding unit is used to pause the output of heart rate and respiratory values ​​during body movement disturbances and retain the last valid data until the signal returns to a stable state.

[0017] This invention discloses a heart rate and respiration acquisition device based on microwave radar technology, comprising a signal acquisition module, a data processing module, a vital sign extraction module, and an output module. The signal acquisition module transmits microwave signals and receives echo signals reflected from the human chest cavity. The data processing module digitizes and preprocesses the echo signals to generate a range-time phase matrix containing information on the micro-movements of the human chest cavity. The vital sign extraction module locates the target chest cavity position from the range-time phase matrix, extracts the chest cavity micro-movement displacement signal, and separates the respiratory signal component and the heartbeat signal component. The output module calculates and outputs the respiratory rate and heart rate based on the separated signal components. This solves the technical problem in existing technologies where it is difficult to accurately separate weak heartbeat signals from strong respiratory interference due to the overlap of respiratory harmonics and heartbeat frequency bands. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below.

[0019] Figure 1 This is a schematic diagram of the structure of a heart rate and respiration acquisition device based on microwave radar technology according to the present invention.

[0020] Figure 2 This is a schematic diagram of the signal acquisition module of the present invention.

[0021] Figure 3 This is a schematic diagram of the data processing module of the present invention.

[0022] Figure 4 This is a schematic diagram of the vital signs extraction module of the present invention.

[0023] Figure 5 This is a schematic diagram of the target positioning unit of the present invention.

[0024] Figure 6 This is a schematic diagram of the phase demodulation unit of the present invention.

[0025] Figure 7 This is a schematic diagram of the signal separation unit of the present invention.

[0026] Figure 8 This is a schematic diagram of the motion artifact processing module of the present invention.

[0027] 1-Signal Acquisition Module, 2-Data Processing Module, 3-Vital Sign Extraction Module, 4-Output Module, 5-Motion Artifact Processing Module, 101-Radar Front-End Unit, 102-RF Transceiver Unit, 201-Analog-to-Digital Conversion Unit, 202-Range Dimension Transformation Unit, 203-Static Clutter Suppression Unit, 301-Target Localization Unit, 302-Phase Demodulation Unit, 303-Signal Separation Unit, 30101-Energy Peak Search Subunit, 30102-Dynamic Tracking Subunit, 30201-Orthogonal Demodulation Subunit, 30202-Phase Unfolding Subunit, 30301-Preprocessing Subunit, 30302-Baseline Drift Suppression Subunit, 30303-Adaptive Decomposition Subunit, 30304-Mode Reconstruction Subunit, 501-Sudden Change Detection Unit, 502-Data Holding Unit. Detailed Implementation

[0028] Please see Figures 1-8 ,in, Figure 1 This is a schematic diagram of the structure of a heart rate and respiration acquisition device based on microwave radar technology according to the present invention. Figure 2 This is a schematic diagram of the signal acquisition module of the present invention. Figure 3 This is a schematic diagram of the data processing module of the present invention. Figure 4 This is a schematic diagram of the vital signs extraction module of the present invention. Figure 5 This is a schematic diagram of the target positioning unit of the present invention. Figure 6 This is a schematic diagram of the phase demodulation unit of the present invention. Figure 7 This is a schematic diagram of the signal separation unit of the present invention. Figure 8 This is a schematic diagram of the motion artifact processing module of the present invention.

[0029] This invention provides a heart rate and respiration acquisition device based on microwave radar technology: comprising a signal acquisition module 1, a data processing module 2, a vital signs extraction module 3, and an output module 4; the signal acquisition module 1 includes a radar front-end unit 101 and a radio frequency transceiver unit 102; the data processing module 2 includes an analog-to-digital conversion unit 201, a range dimension transformation unit 202, and a static clutter suppression unit 203; the vital signs extraction module 3 includes a target positioning unit 301, a phase demodulation unit 302, and a signal separation unit 303; the target positioning unit 301 includes an energy peak search subunit 30101 and a dynamic tracking subunit 30102; The phase demodulation unit 302 includes an orthogonal demodulation subunit 30201 and a phase expansion subunit 30202; the signal separation unit 303 includes a preprocessing subunit 30301, a baseline drift suppression subunit 30302, an adaptive decomposition subunit 30303, and a mode reconstruction subunit 30304; the heart rate and respiration acquisition device based on microwave radar technology also includes a motion artifact processing module 5; the motion artifact processing module 5 includes a mutation detection unit 501 and a data holding unit 502; the aforementioned solution solves the technical problem in the prior art that it is difficult to accurately separate weak heartbeat signals from strong respiratory interference due to the overlap of respiratory harmonics and heartbeat frequency bands.

[0030] Furthermore, the signal acquisition module 1, the data processing module 2, the vital signs extraction module 3, and the output module 4 are connected in sequence; The signal acquisition module 1 is used to transmit microwave signals and receive echo signals reflected from the human chest cavity; The data processing module 2 is used to digitize and preprocess the echo signal to generate a distance-time phase matrix containing micro-movement information of the human chest cavity. The vital signs extraction module 3 is used to locate the target chest cavity from the distance-time phase matrix, extract the chest cavity micro-displacement signal, and separate the respiratory signal component and the heartbeat signal component. The output module 4 is used to calculate and output the respiratory rate and heart rate based on the separated signal components.

[0031] In this embodiment, the signal acquisition module 1 transmits a microwave signal to the target through a transmitting antenna. This signal is reflected by the human chest cavity and received by a receiving antenna, forming a raw echo signal. This raw echo signal carries phase modulation information caused by slight chest cavity movements. The data processing module 2 receives this raw echo signal and first converts the analog echo signal into a digital intermediate frequency (IF) signal through analog-to-digital conversion. Then, it performs a distance-dimensional transformation on the digital IF signal—mapping the echo data at each sampling moment to the distance dimension using a fast Fourier transform, thereby generating a distance-time phase matrix. Each row of this matrix corresponds to a different distance unit, and each row represents the change of the echo signal at a specific distance over time (i.e., a slow-time signal). Each matrix element contains the phase information of that distance unit at that moment. Through this transformation, object echoes at different distances are separated into different distance units, allowing the target chest cavity signal to be distinguished from interference signals at other distances in the environment. The vital signs extraction module 3 further processes the matrix: First, by detecting the energy distribution of each distance unit, the distance unit with the highest energy is determined as the target distance index, which corresponds to the location of the chest cavity; then, the slow-time signal corresponding to this index is extracted, and the phase information is demodulated from it—since chest cavity micro-movements cause echo phase changes, and these phase changes are proportional to chest cavity displacement, the original chest cavity micro-movement displacement signal is obtained through phase demodulation, which is a mixed displacement waveform caused by respiration and heartbeat; finally, the mixed displacement signal is processed by signal separation, utilizing the statistical characteristics of respiration and heartbeat signals in the frequency band (e.g., respiration is concentrated in the low frequency band, and heartbeat is in the high frequency band) to decompose it into independent respiration signal components and heartbeat signal components. The output module 4 receives the separated respiration signal components and heartbeat signal components, calculates their periods or frequencies respectively, obtains the respiratory rate and heart rate, and outputs them through a display or communication interface; thereby solving the technical problem in the prior art that it is difficult to accurately separate weak heartbeat signals from strong respiratory interference due to the overlap of respiratory harmonics and heartbeat frequency bands.

[0032] Furthermore, the radio frequency transceiver unit 102 is connected to the radar front-end unit 101; The radar front-end unit 101 includes at least one transmitting antenna and multiple receiving antennas arranged in an array, for transmitting frequency-modulated continuous wave radar signals to the target under test and receiving echo signals modulated by chest cavity micro-motion. The radio frequency transceiver unit 102 is used to perform frequency mixing and down-conversion processing on the echo signal and output an intermediate frequency analog signal.

[0033] In this embodiment, the radar front-end unit 101 adopts an array antenna design, with multiple receiving antennas arranged in an array. This hardware structure provides the foundation for subsequent spatial filtering. By acquiring the spatial phase difference of the echo signal through multiple receiving channels, the device is able to distinguish targets from interference from different directions, laying the hardware foundation for extracting clean chest cavity signals from strong interference. The radio frequency transceiver unit 102 performs high-frequency signal mixing and down-conversion, converting the millimeter-wave band echo signal into an intermediate-frequency analog signal that can be processed subsequently. This achieves frequency down-conversion from high frequency to intermediate frequency, facilitating subsequent digital processing.

[0034] Furthermore, the analog-to-digital conversion unit 201, the distance dimension transformation unit 202, and the static clutter suppression unit 203 are connected in sequence; The analog-to-digital conversion unit 201 is used to convert intermediate frequency analog signals into intermediate frequency digital signals; The distance-dimensional transformation unit 202 is used to perform a distance-dimensional fast Fourier transform on the intermediate frequency digital signal to generate a distance-time phase matrix; The static clutter suppression unit 203 is used to perform moving target display filtering on the range-time phase matrix to filter out clutter from stationary background objects.

[0035] In this embodiment, the analog-to-digital conversion unit 201 converts analog signals into digital signals, serving as the starting point for digital signal processing. The distance-dimensional transformation unit 202 maps the time-domain signal to the distance dimension using a fast Fourier transform, generating a distance-time phase matrix—this matrix is ​​the core data structure of the invention, with its vertical axis representing distance units and its horizontal axis representing time frames. Each element contains the amplitude and phase information of the echo in that distance unit, providing a foundation for subsequent target chest cavity location. The static clutter suppression unit 203 employs moving target display filtering technology, filtering out background clutter generated by stationary objects such as walls and furniture through adjacent period cancellation, retaining only the signal from the moving target (human chest cavity), effectively improving the signal-to-noise ratio and ensuring that subsequent signal separation is based on high-quality input.

[0036] Furthermore, the target positioning unit 301, the phase demodulation unit 302, and the signal separation unit 303 are connected in sequence; The target positioning unit 301 is used to locate the target distance index of the chest cavity of the target under test according to the spatial distribution of energy in the distance-time phase matrix. The phase demodulation unit 302 is used to extract the phase information of the slow-time signal corresponding to the target distance index and perform phase unwinding processing to obtain the original thoracic cavity micro-displacement signal. The signal separation unit 303 is used to separate the respiratory signal component and the heartbeat signal component from the original chest cavity micro-displacement signal through an adaptive nonlinear non-stationary signal decomposition algorithm.

[0037] In this embodiment, the target localization unit 301 searches for energy peaks in the distance-time phase matrix in real time to determine the target distance index where the chest cavity is located. This step ensures that subsequent processing always focuses on the correct spatial location, eliminating interference from other distances at the source. The phase demodulation unit 302 extracts the corresponding slow-time signal according to the index and recovers the physical displacement waveform of the chest cavity's micro-movements through orthogonal demodulation and phase expansion. This is the original signal of the mixture of respiration and heartbeat. The signal separation unit 303 uses an adaptive nonlinear non-stationary signal decomposition algorithm to separate the respiration and heartbeat components from the overlapping frequency bands, directly solving the core problem in the background art of difficulty in separating weak heartbeat signals due to the overlap of respiratory harmonics and heartbeat frequency bands.

[0038] Furthermore, the dynamic tracking subunit 30102 is connected to the energy peak search subunit 30101; The energy peak search subunit 30101 is used to search for the distance index corresponding to the maximum energy value in the distance dimension data of each frame; The dynamic tracking subunit 30102 is used to establish the target trajectory within a continuous time frame, adaptively update the target distance index when the target under test is displaced, and output the updated target distance index to the phase demodulation unit 302.

[0039] In this embodiment, the energy peak search subunit 30101 independently searches for the distance index with the strongest current energy in each frame of data to obtain the instantaneous position of the current frame. The dynamic tracking subunit 30102 connects the information of the previous and next frames to establish the target motion trajectory within consecutive time frames. When the change in the target distance index between adjacent frames is small, it is determined to be the same target and a filtering algorithm is used for smooth tracking; when a jump in the target distance index is detected, it is determined that the target has moved and the target distance index is updated adaptively. This mechanism enables the device to continuously lock the chest cavity position, ensuring that the phase demodulation unit 302 always extracts signals based on the correct target distance index, avoiding signal loss caused by the target moving out of the fixed distance threshold, and providing a guarantee for continuous and stable signal separation.

[0040] Furthermore, the phase expansion subunit 30202 is connected to the orthogonal demodulation subunit 30201; The quadrature demodulation subunit 30201 is used to calculate the instantaneous phase based on the in-phase component and quadrature component corresponding to the target distance index; The phase unfolding subunit 30202 is used to detect and correct the jump points in the instantaneous phase and restore the continuous thoracic displacement trajectory.

[0041] In this embodiment, the quadrature demodulation subunit 30201 uses the in-phase and quadrature components corresponding to the target distance index to calculate the instantaneous phase value through arctangent operation. Since the result of the arctangent operation is limited to the interval [-π, π], a jump will occur when the actual phase crosses this boundary. The phase expansion subunit 30202 detects these jump points and recovers the continuous phase curve by adding or subtracting 2π, finally obtaining the original thoracic cavity micro-displacement signal that is proportional to the actual micro-displacement of the thoracic cavity, providing accurate input for subsequent signal separation.

[0042] Furthermore, the preprocessing subunit 30301, the baseline drift suppression subunit 30302, the adaptive decomposition subunit 30303, and the modal reconstruction subunit 30304 are connected in sequence; The preprocessing subunit 30301 is used to perform mean removal and trend removal processing on the original thoracic cavity micro-displacement signal. The baseline drift suppression subunit 30302 is used to filter out low-frequency interference caused by large-amplitude movement of the main body; The adaptive decomposition subunit 30303 uses an adaptive decomposition algorithm to decompose the signal into multiple intrinsic mode functions. The modal reconstruction subunit 30304 is used to reconstruct the respiratory signal component and the heartbeat signal component respectively based on the frequency characteristics of each intrinsic mode function.

[0043] In this embodiment, the preprocessing subunit 30301 first eliminates the DC component and linear trend in the signal, providing a clean signal with zero mean for subsequent processing. The baseline drift suppression subunit 30302 uses a high-pass filter to filter out ultra-low frequency interference (typically below 0.1Hz) caused by large movements such as rolling over and limb movement. The adaptive decomposition subunit 30303 is the core processing stage, using an adaptive decomposition algorithm to decompose the signal into multiple intrinsic mode functions, each mode corresponding to a different frequency center. The mode reconstruction subunit 30304 performs frequency analysis on each mode, and its frequency band division criteria are as follows: Respiratory frequency band classification criteria: The normal respiratory rate of an adult at rest is 12-20 breaths per minute, corresponding to a frequency band of 0.2-0.33 Hz. Considering individual differences and different physiological states (such as after exercise or during sleep), the respiratory frequency band is appropriately broadened to 0.1-0.5 Hz. Components below 0.1 Hz are usually classified as baseline drift or body motion interference, while components above 0.5 Hz may contain respiratory harmonics or heartbeat signals. In specific judgment, if the center frequency of a certain mode is within the range of 0.1-0.5 Hz, and its waveform characteristics show periodic fluctuations with large amplitude (usually corresponding to a chest displacement of 4-12 mm), it is determined to be a respiratory signal mode. Heart rate frequency band classification standard: The normal resting heart rate range for adults is 60-100 beats per minute, corresponding to a frequency band of 1.0-1.67 Hz. Considering individual differences (e.g., children's heart rates can be faster, reaching over 120 beats per minute, while athletes' resting heart rates can be as low as 40 beats per minute) and different physiological states, the heart rate frequency band is appropriately widened to 0.8-3.0 Hz. Specifically, the 0.8-1.0 Hz range corresponds to very low heart rates (48-60 beats per minute), 1.0-1.67 Hz is the normal range for adults, and 1.67-3.0 Hz corresponds to relatively fast heart rates (100-180 beats per minute). In specific judgment, if the center frequency of a certain mode is within the 0.8-3.0 Hz range, and its waveform characteristics show regular pulsations with small amplitude (usually corresponding to a chest cavity displacement of 0.1-0.5 mm), it is determined to be a heart rate signal mode. Overlapping frequency band processing: Higher harmonics (second and third harmonics) of respiratory signals may fall within the 0.8-3.0Hz range, overlapping with the heartbeat frequency band. For modes with center frequencies in the 0.8-1.5Hz range, it is necessary to further determine whether they are respiratory second harmonics or the fundamental frequency of the heartbeat: If the frequency of this mode is an integer multiple of the fundamental frequency of the respiratory signal (the main mode within 0.1-0.5Hz) (e.g., 2 or 3 times), and its amplitude decreases with increasing harmonic order, it is determined to be a respiratory harmonic and is removed; if the frequency of this mode is not significantly an integer multiple of the fundamental frequency of the respiratory signal, and its amplitude is relatively stable, it is determined to be a heartbeat signal and is retained. Using the above-mentioned frequency band division standard and overlapping frequency band processing strategy, the mode reconstruction subunit 30304 reconstructs the modes located in the respiratory frequency band into respiratory signals, and reconstructs the modes located in the heartbeat frequency band and which are not respiratory harmonics into heartbeat signals, and finally outputs pure respiratory signal components and heartbeat signal components, directly solving the separation problem caused by the overlap of respiratory harmonics and heartbeat frequency bands.

[0044] Furthermore, the adaptive decomposition algorithm used in the adaptive decomposition subunit 30303 is a variational mode decomposition algorithm, and the number of modes K is adaptively determined by the center frequency observation method: the center frequency of each mode is calculated sequentially when K takes different values, and when the difference between the center frequency of the newly added mode and the center frequency of the existing mode is less than a preset threshold, it is determined that over-decomposition has occurred, and the previous K value is taken as the optimal number of modes.

[0045] In this embodiment, to address the difficulty in determining the number of modes K in the variational mode decomposition algorithm, the center frequency observation method provides an adaptive optimization scheme. The calculation starts with K=2 and increments incrementally, observing the center frequency of each mode after each decomposition. When the center frequency of the newly added mode is very close to the center frequency of the existing modes, it indicates over-decomposition, meaning the algorithm forcibly splits a physical signal component into two modes. In this case, the previous K value is taken as the optimal number of modes. This method avoids the subjectivity of traditional empirically determining the K value, and can adaptively select the optimal decomposition scale based on the frequency band characteristics of the signal itself, ensuring that respiratory and heartbeat signals are completely allocated to different modes without being over-splitled or merged, further improving separation accuracy.

[0046] Furthermore, the motion artifact processing module 5 is connected to the vital signs extraction module 3 and the output module 4, respectively.

[0047] The motion artifact processing module 5 is used to monitor and respond to motion interference.

[0048] In this embodiment, the motion artifact processing module 5 serves as an independent control module, simultaneously connected to the vital signs extraction module 3 and the output module 4, forming an intelligent intervention mechanism for the output results. It acquires the original chest cavity micro-displacement signal from the vital signs extraction module 3 and monitors the signal status in real time. When body motion interference is detected, it intervenes in the output behavior by sending a control command to the output module 4. This design separates signal processing from output control, enabling the device to intelligently manage the reliability of the output results while maintaining normal signal processing flow, avoiding erroneous heart rate and respiratory values ​​output due to body motion interference.

[0049] Furthermore, the data holding unit 502 is connected to the mutation detection unit 501; The mutation detection unit 501 is used to monitor amplitude mutations in the original thoracic cavity micro-movement displacement signal. When the mutation amplitude exceeds a preset threshold, it is determined to be a body motion interference. The data holding unit 502 is used to pause the output of heart rate and respiratory values ​​during body movement disturbances and hold the last valid data until the signal returns to a stable state.

[0050] In this embodiment, the mutation detection unit 501 is connected to the output of the phase demodulation unit 302, continuously monitoring the amplitude changes of the original thoracic cavity micro-motion displacement signal. When the signal undergoes a sudden change exceeding a preset threshold within a short period, it is determined to be body motion interference. The data holding unit 502 is connected to both the mutation detection unit 501 and the output module 4. Upon receiving a body motion interference signal, it sends a pause command to the output module 4. In response to this command, the output module 4 pauses the output of new heart rate and respiratory values, while maintaining the display of the previous valid data. When the signal stabilizes, the mutation detection unit 501 de-interferences, and the data holding unit 502 sends a recovery command to the output module 4, which then resumes normal output. This mechanism effectively avoids erroneous data output caused by body motion interference, improving the reliability of the monitoring results.

[0051] This embodiment describes a heart rate and respiration acquisition device based on microwave radar technology. A complete technical link is constructed through the sequentially connected signal acquisition module 1, data processing module 2, vital sign extraction module 3, and output module 4. The signal acquisition module 1 uses an array antenna to transmit microwaves and receive echo signals. The data processing module 2 generates a distance-time phase matrix and separates the target from interference in the distance dimension. The vital sign extraction module 3 uses the target positioning unit 301 to track the chest cavity position in real time, the phase demodulation unit 302 to extract mixed displacement signals, and the signal separation unit 303 to accurately separate the respiratory and heartbeat components from the frequency band overlap using variational mode decomposition and center frequency observation. Simultaneously, the motion artifact processing module 5 monitors body motion interference and controls the output module 4 to retain the previous valid data during interference periods. This systematically solves the technical problem of accurately separating weak heartbeat signals from strong respiratory interference due to the overlap of respiratory harmonics and heartbeat frequency bands, achieving high-precision, anti-interference, and dynamically trackable non-contact vital sign monitoring.

[0052] The above-disclosed embodiments are merely one or more preferred embodiments of this application and should not be construed as limiting the scope of this application. Those skilled in the art can understand that all or part of the processes for implementing the above embodiments and equivalent changes made in accordance with the claims of this application still fall within the scope of this application.

Claims

1. A heart rate and respiration acquisition device based on microwave radar technology, characterized in that, It includes a signal acquisition module, a data processing module, a vital signs extraction module, and an output module; the signal acquisition module, the data processing module, the vital signs extraction module, and the output module are connected in sequence. The signal acquisition module is used to transmit microwave signals and receive echo signals reflected from the human chest cavity; The data processing module is used to digitize and preprocess the echo signal to generate a distance-time phase matrix containing micro-movement information of the human chest cavity; The vital signs extraction module is used to locate the target chest cavity from the distance-time phase matrix, extract the chest cavity micro-displacement signal, and separate the respiratory signal component and the heartbeat signal component. The output module is used to calculate and output the respiratory rate and heart rate based on the separated signal components.

2. The heart rate and respiration acquisition device based on microwave radar technology as described in claim 1, characterized in that, The signal acquisition module includes a radar front-end unit and a radio frequency transceiver unit; the radio frequency transceiver unit is connected to the radar front-end unit. The radar front-end unit includes at least one transmitting antenna and multiple receiving antennas arranged in an array, for transmitting frequency-modulated continuous wave radar signals to the target under test and receiving echo signals modulated by thoracic cavity micro-motion. The radio frequency transceiver unit is used to perform frequency mixing and down-conversion processing on the echo signal and output an intermediate frequency analog signal.

3. The heart rate and respiration acquisition device based on microwave radar technology as described in claim 2, characterized in that, The data processing module includes an analog-to-digital conversion unit, a range-dimensional transformation unit, and a static clutter suppression unit; the analog-to-digital conversion unit, the range-dimensional transformation unit, and the static clutter suppression unit are connected in sequence. The analog-to-digital converter unit is used to convert intermediate frequency analog signals into intermediate frequency digital signals; The distance-dimensional transformation unit is used to perform a distance-dimensional fast Fourier transform on the intermediate frequency digital signal to generate a distance-time phase matrix. The static clutter suppression unit is used to perform moving target display filtering on the range-time phase matrix to filter out clutter from stationary background objects.

4. The heart rate and respiration acquisition device based on microwave radar technology as described in claim 3, characterized in that, The vital signs extraction module includes a target localization unit, a phase demodulation unit, and a signal separation unit; the target localization unit, the phase demodulation unit, and the signal separation unit are connected in sequence. The target positioning unit is used to locate the target distance index of the chest cavity of the target under test according to the spatial distribution of energy in the distance-time phase matrix. The phase demodulation unit is used to extract the phase information of the slow-time signal corresponding to the target distance index and perform phase unwinding processing to obtain the original thoracic cavity micro-displacement signal. The signal separation unit is used to separate the respiratory signal component and the heartbeat signal component from the original chest cavity micro-displacement signal through an adaptive nonlinear non-stationary signal decomposition algorithm.

5. The heart rate and respiration acquisition device based on microwave radar technology as described in claim 4, characterized in that, The target positioning unit includes an energy peak search subunit and a dynamic tracking subunit; the dynamic tracking subunit is connected to the energy peak search subunit. The energy peak search subunit is used to search for the distance index corresponding to the maximum energy value in the distance dimension data of each frame; The dynamic tracking subunit is used to establish the target trajectory within a continuous time frame, adaptively update the target distance index when the target under test is displaced, and output the updated target distance index to the phase demodulation unit.

6. The heart rate and respiration acquisition device based on microwave radar technology as described in claim 5, characterized in that, The phase demodulation unit includes an orthogonal demodulation subunit and a phase expansion subunit; the phase expansion subunit is connected to the orthogonal demodulation unit. The orthogonal demodulation subunit is used to calculate the instantaneous phase based on the in-phase component and the orthogonal component corresponding to the target distance index; The phase expansion subunit is used to detect and correct the jump points in the instantaneous phase and restore the continuous thoracic displacement trajectory.

7. The heart rate and respiration acquisition device based on microwave radar technology as described in claim 6, characterized in that, The signal separation unit includes a preprocessing subunit, a baseline drift suppression subunit, an adaptive decomposition subunit, and a mode reconstruction subunit; the preprocessing subunit, the baseline drift suppression subunit, the adaptive decomposition subunit, and the mode reconstruction subunit are connected in sequence; The preprocessing subunit is used to remove the mean and trend term from the original thoracic cavity micro-displacement signal. The baseline drift suppression subunit is used to filter out low-frequency interference caused by large-amplitude movement of the main body; The adaptive decomposition subunit uses an adaptive decomposition algorithm to decompose the signal into multiple intrinsic mode functions. The modal reconstruction subunit is used to reconstruct the respiratory signal component and the heartbeat signal component respectively based on the frequency characteristics of each intrinsic mode function.

8. The heart rate and respiration acquisition device based on microwave radar technology as described in claim 7, characterized in that, The adaptive decomposition algorithm used in the adaptive decomposition subunit is a variational mode decomposition algorithm, and the number of modes K is adaptively determined by the center frequency observation method: the center frequency of each mode is calculated sequentially when K takes different values. When the difference between the center frequency of the newly added mode and the center frequency of the existing mode is less than a preset threshold, it is determined that over-decomposition has occurred, and the previous K value is taken as the optimal number of modes.

9. The heart rate and respiration acquisition device based on microwave radar technology as described in claim 8, characterized in that, The heart rate and respiration acquisition device based on microwave radar technology also includes a motion artifact processing module, which is connected to the vital signs extraction module and the output module respectively. The motion artifact processing module is used to monitor and respond to motion interference.

10. The heart rate and respiration acquisition device based on microwave radar technology as described in claim 9, characterized in that, The motion artifact processing module includes a mutation detection unit and a data preservation unit; the data preservation unit is connected to the mutation detection unit. The mutation detection unit is used to monitor amplitude mutations in the original thoracic cavity micro-movement displacement signal. When the mutation amplitude exceeds a preset threshold, it is determined to be a body motion interference. The data holding unit is used to pause the output of heart rate and respiratory values ​​during body movement disturbances and retain the last valid data until the signal returns to a stable state.

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