CN114587318A - Respiration and heart rate monitoring method and system and storage medium - Google Patents
Respiration and heart rate monitoring method and system and storage medium Download PDFInfo
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- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
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Abstract
The invention discloses a method, a system and a storage medium for monitoring a respiratory heart rate, wherein the method for monitoring the respiratory heart rate comprises the steps of transmitting wireless waves to a target object and receiving echo signals; confirming a target echo signal of the target object from the echo signal; phase unwrapping and phase difference calculation are carried out on the target echo signal to obtain a difference value; filtering the difference value to obtain a respiration signal and a heartbeat signal; estimating the respiratory signal spectrum to obtain respiratory frequency; eliminating the occupied segment of the heartbeat signal movement to obtain an elimination signal, and estimating the spectrum of the elimination signal to obtain the heartbeat frequency; the interference can be effectively removed, and the detection accuracy of the heartbeat frequency and the respiratory frequency is improved.
Description
Technical Field
The invention relates to the field of physical sign detection, in particular to a method and a system for monitoring respiratory heart rate and a storage medium.
Background
The living body sign detection method comprises a non-contact mode and a contact mode. The contact type living body sign detection method requires that a sensor is in close contact with a human body, and has certain limitation on part of application scenes. The non-contact living body sign detection method is easily influenced by external environment, interference signals are redundant, and detection precision is greatly reduced.
Disclosure of Invention
The present invention at least solves one of the technical problems in the prior art, and provides a method, a system and a storage medium for monitoring a respiratory heart rate.
The technical scheme adopted by the invention for solving the problems is as follows:
in a first aspect of the invention, a method of respiratory heart rate monitoring comprises:
transmitting wireless waves to a target object and receiving echo signals corresponding to the wireless waves;
confirming a target echo signal of the target object from the echo signals;
phase unwrapping and phase difference calculation are carried out on the target echo signal to obtain a difference value;
filtering the differential value to obtain a respiration signal and a heartbeat signal;
carrying out spectrum estimation on the respiratory signal to obtain respiratory frequency;
and eliminating the motion occupying segment of the heartbeat signal to obtain an elimination signal, and performing spectrum estimation on the elimination signal to obtain the heartbeat frequency.
According to the first aspect of the present invention, after obtaining the respiration signal and the heartbeat signal, the respiration heart rate monitoring method further comprises the steps of:
carrying out short-term analysis on the respiratory signal to obtain first analysis data;
carrying out short-term analysis on the heartbeat signal to obtain second analysis data;
performing data comparison analysis on the respiratory signal and cloud long-term data to obtain third analysis data;
performing data comparison analysis on the heartbeat signal and cloud long-term data to obtain fourth analysis data;
and judging the body abnormal condition of the target object according to the first analysis data, the second analysis data, the third analysis data and the fourth analysis data.
According to a first aspect of the present invention, the transmitting of the radio wave to the target object includes:
and adopting a time division multiplexing mode to send wireless waves of different channels to the target object at different time intervals.
According to a first aspect of the present invention, the confirming a target echo signal of the target object from the echo signals includes:
carrying out short-time Fourier transform on the echo signal to obtain distance information of the target object;
and dynamically detecting the echo signal according to the distance information, and taking the echo signal with the maximum relative amplitude as the target echo signal.
According to the first aspect of the present invention, the filtering the differential value to obtain a respiration signal and a heartbeat signal includes:
inputting the differential value into a first band-pass filter with a first filtering frequency for filtering to obtain the respiratory signal;
and inputting the differential value into a second band-pass filter with a second filtering frequency for filtering to obtain the heartbeat signal.
According to the first aspect of the present invention, the removing the motion occupying segment of the heartbeat signal to obtain a removed signal, and performing spectrum estimation on the removed signal to obtain a heartbeat frequency includes:
segmenting the heartbeat signal into a plurality of data segments;
determining a first classified data segment and a second classified data segment from the plurality of data segments according to energy values, wherein the energy value of the first classified data segment is greater than a preset energy threshold value, and the energy value of the second classified data segment is less than or equal to the preset energy threshold value;
discarding all of the first classified data segments from the time-domain cardiac waveform and all of the second classified data segments as cancellation signals;
and carrying out spectrum estimation on the elimination signal to obtain the heartbeat frequency.
According to the first aspect of the present invention, the removing the motion occupying segment of the heartbeat signal to obtain a removed signal, and performing spectrum estimation on the removed signal to obtain a heartbeat frequency includes:
segmenting the heartbeat signal into a plurality of data segments;
determining a first classified data segment and a second classified data segment from the plurality of data segments according to energy values, wherein the energy value of the first classified data segment is greater than a preset energy threshold value, and the energy value of the second classified data segment is less than or equal to the preset energy threshold value; scaling the first classified data segment to obtain a scaling signal;
taking all the scaled signals and all the second classified data segments as cancellation signals;
and carrying out spectrum estimation on the elimination signal to obtain the heartbeat frequency.
According to a first aspect of the invention, the spectral estimation comprises peak interval estimation using fast fourier transform, autocorrelation or time-frequency waveform.
In a second aspect of the invention, a respiratory heart rate monitoring system comprises:
the wave transmitting and receiving module is used for transmitting wireless waves to a target object and receiving echo signals corresponding to the wireless waves;
the target confirmation module is used for confirming a target echo signal of the target object from the echo signal;
the difference value calculation module is used for carrying out phase unwrapping and phase difference calculation on the target echo signal to obtain a difference value;
the filtering module is used for filtering the differential value to obtain a respiration signal and a heartbeat signal;
the first frequency analysis module is used for carrying out spectrum estimation on the respiratory signal to obtain respiratory frequency;
and the second frequency analysis module is used for eliminating the motion occupying segment of the heartbeat signal to obtain an elimination signal and carrying out spectrum estimation on the elimination signal to obtain the heartbeat frequency.
In a third aspect of the invention, a storage medium stores a computer program for executing the method of monitoring a respiratory heart rate according to the first aspect of the invention.
The scheme at least has the following beneficial effects: the non-contact detection method of the living body characteristics is realized through wireless wave measurement; interference signals are removed through target confirmation, phase unwrapping, phase difference calculation and filtering, respiration signals and heartbeat signals are highlighted, specific numerical values of respiration frequency and heartbeat frequency are determined through spectrum estimation, and detection accuracy of the heartbeat frequency and the respiration frequency is improved.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The invention is further illustrated with reference to the following figures and examples.
FIG. 1 is a step diagram of a method of respiratory heart rate monitoring according to an embodiment of the present invention;
FIG. 2 is a step diagram of one aspect of step S600 in FIG. 1;
FIG. 3 is a step diagram of another aspect of step S600 in FIG. 1;
fig. 4 is a structural view of a millimeter wave radar;
fig. 5 is a block diagram of a respiratory heart rate monitoring system according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to the present preferred embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to like elements throughout.
In the description of the present invention, it should be understood that the orientation or positional relationship referred to in the description of the orientation, such as upper, lower, front, rear, left, right, etc., is based on the orientation or positional relationship shown in the drawings only for the convenience of description of the present invention and simplification of the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus, should not be construed as limiting the present invention.
In the description of the present invention, the meaning of a plurality of means is one or more, the meaning of a plurality of means is two or more, and larger, smaller, larger, etc. are understood as excluding the number, and larger, smaller, inner, etc. are understood as including the number. If the first and second are described for the purpose of distinguishing technical features, they are not to be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated or implicitly indicating the precedence of the technical features indicated.
In the description of the present invention, unless otherwise explicitly limited, terms such as arrangement, installation, connection and the like should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above terms in the present invention in combination with the specific contents of the technical solutions.
Referring to fig. 1, an embodiment of a first aspect of the invention provides a respiratory heart rate monitoring method.
The respiratory heart rate monitoring method comprises the following steps:
step S100, transmitting wireless waves to a target object and receiving echo signals corresponding to the wireless waves;
step S200, confirming a target echo signal of a target object from the echo signal;
step S300, phase unwrapping and phase difference calculation are carried out on the target echo signal to obtain a difference value;
s400, filtering the difference value to obtain a respiration signal and a heartbeat signal;
s500, performing spectrum estimation on the respiratory signal to obtain respiratory frequency;
and S600, eliminating the motion occupying segments of the heartbeat signal to obtain an elimination signal, and performing spectrum estimation on the elimination signal to obtain the heartbeat frequency.
In the embodiment, a non-contact detection method of the living body characteristics is realized through wireless wave measurement; interference signals are removed through target confirmation, phase unwrapping, phase difference calculation and filtering, respiration signals and heartbeat signals are highlighted, specific numerical values of respiration frequency and heartbeat frequency are determined through spectrum estimation, and detection accuracy of the heartbeat frequency and the respiration frequency is improved.
In certain embodiments of the first aspect of the present invention, for step S100, wireless millimeter waves, specifically, chirp continuous waves, are transmitted to the target living body by a millimeter wave radar having a carrier frequency of 77 GHz. And receiving echo signals obtained by reflection of the target living body through a wave receiver.
24GHz and 77GHz are two more commonly used FMCW millimeter wave frequency bands. The 24GHz band is a narrow band with a bandwidth of 250 MHz. While the 77GHz band can provide a wide bandwidth of up to 4GHz, the 77GHz band performs better in terms of range resolution and accuracy than the 24GHz band since range resolution and accuracy are inversely proportional to scan bandwidth. An FMCW millimeter wave radar system with an operating frequency of 77GHz is capable of transmitting electromagnetic waves with a wavelength of 4mm, which makes it possible to detect relatively small position changes.
In addition, the millimeter wave with the frequency of 77GHz has the advantages of high sensitivity, simple structure, small volume, low cost and low power consumption, can detect the movement of micro-to-several-tenths of millimeters, can be used for measuring micro-vibration generated by respiration and heartbeat of a human body, and improves the detection precision.
Meanwhile, relevant components of the radar corresponding to the millimeter wave with the frequency of 77GHz have smaller volume and lower power consumption, and are suitable for daily and civil use.
Referring to fig. 4, the invention adopts 2-transmitter 3-receiver frequency modulation continuous wave millimeter wave radar sensor, and the millimeter wave radar sensor can be placed on a table top to realize long-term sedentary monitoring. The millimeter wave radar sensor uses an STM32 microprocessor as a processing chip, the antenna module adopts two transmitting antennas and three receiving antennas, and processed data can be sent to an upper computer PC through a serial port and can also be sent to a mobile device through a WIFI module.
The working process of the millimeter wave radar sensor is as follows: firstly, a wave transmitter of the radar generates a signal of a specific frequency band, the signal is transmitted by a transmitting antenna (TX), and wireless waves of different channels are transmitted to a target object at different time intervals by adopting a time division multiplexing mode, namely, an FMCW signal of a channel 1 is transmitted firstly, and then an FMCW signal of a channel 2 is transmitted. The signal encounters an object during propagation to produce an echo, which is received by a receiving antenna (RX). The transmit signal is then mixed with the echo signal by a mixer to produce an intermediate frequency signal. The intermediate frequency signal is AD converted. And performing one-dimensional FFT (fast Fourier transform) on the data received by each receiving channel, and accumulating the one-dimensional FFT results of the virtual 6 channels to improve the signal-to-noise ratio.
The frequency modulation signal transmitted by the radar waveform transmitter is as follows:
reflected from the targetThe echo signals are:
the mixer mixes the frequency modulation signal and the echo signal to obtain an intermediate frequency signal, wherein the intermediate frequency signal is as follows:
wherein, td＝2R/c，λf0C, intermediate frequency signal frequency fb2BR/cT with a phase of
Wherein R is the target distance and c is the speed of light.
Certain embodiments of the first aspect of the present invention, for step S200, identifying a target echo signal of a target object from echo signals, comprise: carrying out short-time Fourier transform on the echo signal to obtain distance information of a target object; and dynamically detecting the echo signal according to the distance information, and taking the echo signal with the maximum relative amplitude as a target echo signal.
Namely, the range of the target is set through the approximate range of the radar and the target, and the range unit corresponding to the maximum amplitude value in the range of the target is selected as the target range unit, namely, one range unit is selected at each slow time.
In some embodiments of the first aspect of the present invention, for step S300, phase unwrapping and phase difference calculation are performed on the target echo signal to obtain a difference value.
The echo signal after fourier transform is a complex signal, and it is necessary to obtain phase information of the target object by using an arctan function. For the arctangent function, the phenomenon that the angle jumps at pi, jumps from minus pi to 2 pi, and the jump amplitude is 2 pi exists, and the function becomes phase winding.
The phase value of the object in each frame period is extracted.
The phase value is extracted by means of an arctangent function of
The phase can be obtained as
Suppose that the motion distance of the thoracic cavity is Delta R and the phase difference is
Calculating the phase difference between two measurements
The phase value is not a true value due to the use of the arctan function when extracting the phase value, so that unwrapping is required to obtain a true phase offset value.
The phase unwrapping is realized according to the phase difference value, 2 pi is required to be added when the continuous phase difference value is larger than pi, and 2 pi is required to be subtracted when the continuous phase difference value is smaller than-pi, and finally continuously-changed phase information is obtained.
The process of unwrapping the phase of the echo signal is as follows:
let the phase at the current time be thetan and the phase at the next time be thetan + 1. When the absolute value theta n + 1-theta n is larger than pi, the phase jumps at the moment and needs phase processing; when theta n + 1-theta n is larger than pi, then theta n +1 is equal to theta n + 1-2 pi; when θ n + 1- θ n < — pi, then θ n +1 ═ θ n +1+2 pi.
And carrying out phase difference calculation on the phase value obtained by phase unwrapping of the echo signal to obtain a difference value.
The phase difference operation is performed by subtracting successive phases after unwrapping, the former being said to lead the latter when the phase difference is greater than zero and lagging the latter when less than zero. When the two physical quantities are zero or even multiples of pi, the two physical quantities are in phase; an odd multiple of pi is called inversion. This operation can increase the strength of the heartbeat signal and eliminate any phase drift.
Certain embodiments of the first aspect of the present invention, for step S400, the filtering the difference value to obtain a respiration signal and a heartbeat signal, includes:
inputting the difference value into a first band-pass filter with a first filtering frequency for filtering to obtain a respiratory signal;
and inputting the difference value into a second band-pass filter with a second filtering frequency for filtering to obtain the heartbeat signal.
Specifically, the first filtering frequency ranges from 0.1Hz to 0.5 Hz; the second filtering frequency is in the range of 0.8Hz to 2.0 Hz. The frequency of the respiration signal is mainly 0.1 Hz-0.5 Hz, and the amplitude is 1 mm-12 mm; the frequency of the heartbeat signal is mainly 0.8 Hz-2 Hz, and the amplitude is 0.1 mm-0.5 mm. The phase difference signal is subjected to band-pass filtering through the band-pass filter, so that the respiratory signal and the heartbeat signal of the target object can be accurately distinguished.
Certain embodiments of the first aspect of the present invention, for step S500, a spectral estimation is performed to obtain a respiratory rate.
The spectral estimation includes peak interval estimation using fast fourier transform, autocorrelation, or time frequency waveforms.
Referring to fig. 2, for step S600, in an aspect, certain embodiments of the first aspect of the present invention perform motion occupying segment elimination on the heartbeat signal to obtain an elimination signal, perform spectrum estimation on the elimination signal to obtain a heartbeat frequency, including:
step S611, dividing the heartbeat signal into a plurality of data segments;
step S612, determining a first classified data segment and a second classified data segment from the plurality of data segments according to the energy values, wherein the energy value of the first classified data segment is greater than a preset energy threshold value, and the energy value of the second classified data segment is less than or equal to the preset energy threshold value;
step S613, discarding all first classified data segments from the time-domain cardiac waveform, and taking all second classified data segments as cancellation signals;
and step S614, performing spectrum estimation on the elimination signal to obtain the heartbeat frequency.
Referring to fig. 3, certain embodiments of the first aspect of the present invention, regarding step S600, in another aspect, performing motion occupying segment elimination on the heartbeat signal to obtain an elimination signal, and performing spectrum estimation on the elimination signal to obtain a heartbeat frequency, include:
step S621, dividing the heartbeat signal into a plurality of data segments;
step S622, determining a first classified data segment and a second classified data segment from the plurality of data segments according to the energy values, wherein the energy value of the first classified data segment is greater than a preset energy threshold value, and the energy value of the second classified data segment is less than or equal to the preset energy threshold value;
step S623, scaling the first classified data segment according to a proportion to obtain a scaling signal;
step S624, using all the scaling signals and all the second classified data segments as cancellation signals;
step S625, perform spectrum estimation on the cancellation signal to obtain the heartbeat frequency.
Likewise, the spectral estimation of the canceled signal corresponding to a heartbeat includes peak interval estimation using fast fourier transform, autocorrelation, or time-frequency waveform.
The heartbeat signal is divided into a plurality of data segments, for example, the heartbeat signal may be equally divided into n data segments, and each data segment corresponds to 1 second.
Energy threshold of EthThe energy threshold is a value that is artificially preset according to the history data.
The scaling is specifically set in this embodiment
Of course, in other embodiments, the scaling ratio may be set to other values according to actual production requirements.
In certain embodiments of the first aspect of the present invention, after obtaining the respiration signal and the heartbeat signal, the respiration heart rate monitoring method further comprises the steps of:
carrying out short-term analysis on the respiratory signal to obtain first analysis data;
carrying out short-term analysis on the heartbeat signal to obtain second analysis data;
carrying out data comparison analysis on the respiratory signals and the cloud long-term data to obtain third analysis data;
carrying out data comparison analysis on the heartbeat signals and the cloud long-term data to obtain fourth analysis data;
and judging the body abnormal condition of the target object according to the first analysis data, the second analysis data, the third analysis data and the fourth analysis data.
Short-term analysis refers to analysis of data over a short period of time (e.g., one minute). When the data is found to have large fluctuations in a short time, i.e. the fluctuation span exceeds a preset threshold, an alarm is issued.
The long-term data comparison analysis is to compare the data with historical data for years or months, and whether significant changes exist or not is analyzed, so that potential disease threats can be found in time. Meanwhile, long-term data is sent to the user side in a chart mode, so that the user can know the body change of the user more intuitively.
When the user sits for a long time, the breathing frequency and the heartbeat frequency of the user can be maintained in a stable state for a long time. When the respiratory rate monitoring system monitors that the respiratory rate and the heartbeat rate of the user can be maintained in a stable state for a long time, the user is judged to be in a sedentary state, a prompt is sent to the user side to prompt the user to move properly, and harm caused by sedentary is prevented.
When it is determined that the body abnormality of the target object is abnormal, the abnormal condition is notified through the user app of the mobile terminal.
Referring to fig. 5, an embodiment of a second aspect of the invention provides a respiratory heart rate monitoring system.
The respiratory heart rate monitoring system includes a wave transceiver module 100, a target confirmation module 200, a differential value calculation module 300, a filtering module 400, a first frequency analysis module 500, and a second frequency analysis module 600.
The wave transmitting and receiving module 100 is configured to transmit a wireless wave to a target object and receive an echo signal corresponding to the wireless wave; the target confirmation module 200 is configured to confirm a target echo signal of the target object from the echo signal; the difference value calculating module 300 is configured to perform phase unwrapping and phase difference calculation on the target echo signal to obtain a difference value; the filtering module 400 filters the difference value to obtain a respiration signal and a heartbeat signal; the first frequency analysis module 500 is configured to perform spectrum estimation on the respiratory signal to obtain a respiratory frequency; the second frequency analysis module 600 is configured to perform motion occupying segment elimination on the heartbeat signal to obtain an elimination signal, and perform spectrum estimation on the elimination signal to obtain a heartbeat frequency.
The wave transceiver module is a millimeter wave radar sensor with a frequency of 77 GHz. The millimeter wave radar sensor transmits data to the computer end through the serial port, transmits the data to the mobile end through the wireless network, the computer end interacts the data with the cloud end through the wired network, and the mobile end interacts with the cloud end through the wireless network.
In the embodiment, the respiration heart rate monitoring system realizes a non-contact detection method of living body characteristics through wireless wave measurement; by target confirmation, phase unwrapping, phase difference calculation and filtering, interference signals are removed, respiration signals and heartbeat signals are highlighted, and detection accuracy of heartbeat frequency and respiration frequency is improved.
It should be noted that, each module of the respiratory heart rate monitoring system corresponds to each step of the respiratory heart rate monitoring method, and has the same technical scheme, so that the same technical problems are solved, the same technical effects are brought, and detailed description is omitted here.
In an embodiment of a third aspect of the invention, a storage medium is provided. The storage medium stores a computer program for performing a method of respiratory heart rate monitoring as an embodiment of the first aspect of the present invention.
One of ordinary skill in the art will appreciate that all or some of the steps, systems, and methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as is well known to those skilled in the art.
The above is only a preferred embodiment of the present invention, and the present invention is not limited to the above embodiments, and the present invention shall fall within the protection scope of the present invention as long as the technical effects of the present invention are achieved by the same means.
Claims (10)
1. A method of respiratory heart rate monitoring, comprising:
transmitting a wireless wave to a target object and receiving an echo signal corresponding to the wireless wave;
confirming a target echo signal of the target object from the echo signals;
phase unwrapping and phase difference calculation are carried out on the target echo signal to obtain a difference value;
filtering the differential value to obtain a respiration signal and a heartbeat signal;
carrying out spectrum estimation on the respiratory signal to obtain respiratory frequency;
and eliminating the motion occupying segment of the heartbeat signal to obtain an elimination signal, and performing spectrum estimation on the elimination signal to obtain the heartbeat frequency.
2. A method of respiratory heart rate monitoring according to claim 1, wherein after obtaining the respiratory signal and the heartbeat signal, the method further comprises the steps of:
carrying out short-term analysis on the respiratory signal to obtain first analysis data;
carrying out short-term analysis on the heartbeat signal to obtain second analysis data;
performing data comparison analysis on the respiratory signal and cloud long-term data to obtain third analysis data;
performing data comparison analysis on the heartbeat signal and cloud long-term data to obtain fourth analysis data;
and judging the abnormal condition of the body of the target object according to the first analysis data, the second analysis data, the third analysis data and the fourth analysis data.
3. The method for monitoring respiratory heart rate according to claim 1, wherein the emitting wireless waves to the target object comprises:
and adopting a time division multiplexing mode to send wireless waves of different channels to the target object at different time intervals.
4. The method according to claim 1, wherein the identifying a target echo signal of the target object from the echo signals comprises:
carrying out short-time Fourier transform on the echo signal to obtain distance information of the target object;
and dynamically detecting the echo signal according to the distance information, and taking the echo signal with the maximum relative amplitude as the target echo signal.
5. The method for monitoring respiratory heart rate according to claim 1, wherein the filtering the differential value to obtain a respiratory signal and a heartbeat signal comprises:
inputting the differential value into a first band-pass filter with a first filtering frequency for filtering to obtain the respiratory signal;
and inputting the differential value into a second band-pass filter with a second filtering frequency for filtering to obtain the heartbeat signal.
6. The respiratory heart rate monitoring method according to claim 1, wherein the performing motion occupying segment cancellation on the heartbeat signal to obtain a cancellation signal, and performing spectrum estimation on the cancellation signal to obtain a heartbeat frequency comprises:
segmenting the heartbeat signal into a plurality of data segments;
determining a first classified data segment and a second classified data segment from the plurality of data segments according to energy values, wherein the energy value of the first classified data segment is greater than a preset energy threshold value, and the energy value of the second classified data segment is less than or equal to the preset energy threshold value; discarding all of the first classified data segments from the time-domain cardiac waveform and all of the second classified data segments as cancellation signals;
and carrying out spectrum estimation on the elimination signal to obtain the heartbeat frequency.
7. The respiratory heart rate monitoring method according to claim 1, wherein the performing motion occupying segment cancellation on the heartbeat signal to obtain a cancellation signal, and performing spectrum estimation on the cancellation signal to obtain a heartbeat frequency comprises:
segmenting the heartbeat signal into a plurality of data segments;
determining a first classified data segment and a second classified data segment from the plurality of data segments according to energy values, wherein the energy value of the first classified data segment is greater than a preset energy threshold value, and the energy value of the second classified data segment is less than or equal to the preset energy threshold value;
scaling the first classified data segment to obtain a scaling signal;
taking all the scaled signals and all the second classified data segments as cancellation signals;
and carrying out spectrum estimation on the elimination signal to obtain the heartbeat frequency.
8. A method of respiratory heart rate monitoring according to claim 1, wherein the spectral estimation comprises peak interval estimation using fast fourier transform, autocorrelation or time-frequency waveform.
9. A respiratory heart rate monitoring system, comprising:
the wave transmitting and receiving module is used for transmitting wireless waves to a target object and receiving echo signals corresponding to the wireless waves;
the target confirmation module is used for confirming a target echo signal of the target object from the echo signal;
the difference value calculation module is used for carrying out phase unwrapping and phase difference calculation on the target echo signal to obtain a difference value;
the filtering module is used for filtering the differential value to obtain a respiration signal and a heartbeat signal;
the first frequency analysis module is used for carrying out spectrum estimation on the respiratory signal to obtain respiratory frequency;
and the second frequency analysis module is used for eliminating the motion occupying segments of the heartbeat signal to obtain an elimination signal and carrying out spectrum estimation on the elimination signal to obtain the heartbeat frequency.
10. A storage medium, characterized in that a computer program is stored for performing the method of respiratory heart rate monitoring according to any one of claims 1 to 8.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114366051A (en) * | 2021-12-10 | 2022-04-19 | 五邑大学 | Non-contact type living body sign detection method, device, equipment and storage medium |
| CN114947754A (en) * | 2022-06-30 | 2022-08-30 | 北京京东拓先科技有限公司 | Method and apparatus for determining sleep data |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114366051A (en) * | 2021-12-10 | 2022-04-19 | 五邑大学 | Non-contact type living body sign detection method, device, equipment and storage medium |
| CN114947754A (en) * | 2022-06-30 | 2022-08-30 | 北京京东拓先科技有限公司 | Method and apparatus for determining sleep data |
| CN114947754B (en) * | 2022-06-30 | 2024-08-16 | 北京京东拓先科技有限公司 | Method and apparatus for determining sleep data |
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