CN114366051A - Non-contact type living body sign detection method, device, equipment and storage medium - Google Patents
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Abstract
The invention discloses a non-contact type living body sign detection method, a device, equipment and a storage medium, wherein the method comprises the steps of transmitting wireless waves to a target object and receiving echo signals; confirming a target echo signal of a 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 difference value to obtain a respiration signal and a heartbeat signal; carrying out frequency analysis on the respiration signal and the heartbeat signal to obtain the respiration frequency and the heartbeat frequency; by wireless wave measurement, a non-contact detection method of living body characteristics is realized; 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.
Description
Technical Field
The invention relates to the field of physical sign detection, in particular to a non-contact living body physical sign detection method, a non-contact living body physical sign detection device, non-contact living body physical sign detection equipment 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 is directed to solve at least one of the problems of the prior art, and provides a method, an apparatus, a device and a storage medium for contactless vital sign detection.
The technical scheme adopted by the invention for solving the problems is as follows:
in a first aspect of the invention, a method for contactless detection of vital signs comprises:
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;
and carrying out frequency analysis on the respiration signal to obtain the respiration frequency, and carrying out frequency analysis on the heartbeat signal to obtain the heartbeat frequency.
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 short-time fourier transform corresponds to the following equation:
wherein, f [ n ]]Is the echo signal, w [ n ]]Is the window function of the short-time fourier transform, m is the magnitude of the distance of each sliding of the window function, and w is the angular frequency.
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 invention, the first filtering frequency is in the range of 0.1Hz to 0.5 Hz; the second filtering frequency is in the range of 0.8Hz to 2.0 Hz.
According to a first aspect of the invention, the frequency analyzing the respiration signal to obtain a respiration frequency comprises:
performing wavelet transformation on the respiration signal to obtain a first respiration processing signal;
performing multi-resolution analysis on the first respiration processing signal to obtain a second respiration processing signal;
performing weighting processing on the second respiration processing signal to obtain a third respiration processing signal;
and performing frequency spectrum estimation on the third respiration processing signal to obtain the respiration frequency.
According to the first aspect of the present invention, the frequency analyzing the heartbeat signal to obtain the heartbeat frequency includes:
performing wavelet transformation on the heartbeat signal to obtain a first heartbeat processing signal;
performing multi-resolution analysis on the first heartbeat processing signal to obtain a second heartbeat processing signal;
weighting the second heartbeat processing signal to obtain a third heartbeat processing signal;
and performing frequency spectrum estimation on the third heartbeat processing signal to obtain the respiratory frequency.
In a second aspect of the invention, a contactless vital signs detection device 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;
and the frequency analysis module is used for carrying out frequency analysis on the respiration signal to obtain the respiration frequency and carrying out frequency analysis on the heartbeat signal to obtain the heartbeat frequency.
In a third aspect of the invention, a contactless vital signs detection device comprises: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the contactless vital sign detection method according to the first aspect of the invention when executing the computer program.
In a fourth aspect of the present invention, a storage medium stores a computer program for executing the contactless vital sign detection method according to the first aspect of the present invention.
The scheme at least has the following beneficial effects: by wireless wave measurement, a non-contact detection method of living body characteristics is realized; 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.
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.
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The invention is further illustrated with reference to the following figures and examples.
FIG. 1 is a step diagram of a method for contactless vital sign detection according to an embodiment of the present invention;
fig. 2 is a step diagram of step S200;
FIG. 3 is a schematic diagram of the filtering of the difference value to obtain a respiration signal and a heartbeat signal;
FIG. 4 is a schematic diagram of a respiratory signal frequency analysis to obtain respiratory frequency;
FIG. 5 is a schematic diagram of a heartbeat signal frequency analysis to obtain a heartbeat frequency;
fig. 6 is a block diagram of a contactless vital sign detection device 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 the upper, lower, front, rear, left, right, etc., is based on the orientation or positional relationship shown in the drawings, and is only for convenience of description and simplification of 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 contactless vital sign detection method.
The non-contact type living body sign detection 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;
and S500, carrying out frequency analysis on the respiration signal to obtain the respiration frequency, and carrying out frequency analysis on the heartbeat 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; 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.
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 transmitting radar having a carrier frequency of 77 GHz. And receiving echo signals obtained by reflection of the target living body through a wave receiver.
It should be noted that the millimeter wave with a 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 the micro-vibration generated by human respiration and heartbeat, and improves the detection precision.
Referring to fig. 2, 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, include:
step S210, carrying out short-time Fourier transform on the echo signal to obtain distance information of a target object;
and step S220, 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.
In step S210, the echo signal is subjected to one-dimensional short-time fourier transform according to the chirp period of the chirped continuous wave, and a position corresponding to the distance fourier transform map of the signal of the target object has a signal peak which is obvious compared with the background signal. The actual distance information of the target object can be calculated from the signal peak.
Note that, the short-time fourier transform corresponds to the following equation:
wherein, f [ n ]]Is an echo signal, w [ n ]]Is a window function of the short-time fourier transform, m is the magnitude of the distance of each sliding of the window function, and w is the angular frequency.
The distribution of the signals on a frequency domain is obtained by performing Fourier transform on the signals in the window, and the distance information of the target object can be obtained through the distance spectrogram.
In step S220, the target object and the background object may shake or swing, which may cause the echo signal to carry an interference signal.
Since the distance information of the target object is already obtained, the interference signal corresponding to the background object can be excluded according to the distance information.
In addition, the body swing frame can be identified through a deep learning network and other modes, body swing parameters are calculated through an auxiliary sensor, and the echo signals are compensated to eliminate interference signals corresponding to target object shaking or swinging. And finally, taking the echo signal with the maximum relative amplitude as a target echo signal.
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 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.
Referring to fig. 3, certain embodiments of the first aspect of the present invention, for step S400, filtering the differential value to obtain a respiration signal and a heartbeat signal, include: inputting the difference value into a first band-pass filter 101 with a first filtering frequency for filtering to obtain a respiratory signal; and inputting the difference value into a second band-pass filter 102 with a second filtering frequency for filtering to obtain a 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.
Referring to fig. 4 and 5, certain embodiments of the first aspect of the present invention, frequency analyzing the respiration signal to obtain a respiration frequency, comprise:
performing wavelet transformation on the respiration signal to obtain a first respiration processing signal;
performing multi-resolution analysis on the first respiration processing signal to obtain a second respiration processing signal;
performing weighting processing on the second respiration processing signal to obtain a third respiration processing signal;
and performing frequency spectrum estimation on the third respiration processing signal to obtain the respiration frequency.
Certain embodiments of the first aspect of the present invention provide a method for obtaining a heartbeat frequency by performing a frequency analysis on a heartbeat signal, comprising:
performing wavelet transformation on the heartbeat signal to obtain a first heartbeat processing signal;
performing multi-resolution analysis on the first heartbeat processing signal to obtain a second heartbeat processing signal;
weighting the second heartbeat processing signal to obtain a third heartbeat processing signal;
and performing frequency spectrum estimation on the third heartbeat processing signal to obtain the respiratory frequency.
It should be noted that, the wavelet transform is a Coiflet wavelet transform, and the maximum overlapping discrete wavelet transform is performed on the phase, and the wavelet transform belongs to linear transform, and the process meets the energy conservation law.
The result obtained after wavelet processing is a coefficient matrix. The wavelet coefficients of the sub-bands have energy dimensions, the energy on different sub-bands is different, and the size of the energy can reflect the frequency band of the original signal transmission distribution.
The weighting process is specifically a process of weighting the coefficient matrix according to the energy magnitude, and the process can further highlight the frequency band in which the second harmonic signal may appear.
The frequency spectrum estimation specifically comprises the steps of carrying out fast Fourier transform on signals, classifying the signals by using an SVM classifier, selecting possible values of peak values from the signals in the same time interval, and obtaining the optimal value of the peak value from the possible values of the peak values by using a genetic algorithm. The optimal value corresponding to the respiration signal is the respiration frequency, and the optimal value corresponding to the heartbeat signal is the heartbeat frequency.
The Cioflet wavelet processing and weighting process further improves the accuracy of signal identification.
Referring to fig. 6, an embodiment of a second aspect of the invention provides a contactless vital signs detection device.
The non-contact type living body sign detection device comprises a wave transmitting and receiving module 10, a target confirming module 20, a difference value calculating module 30, a filtering module 40 and a frequency analyzing module 50.
The wave transmitting and receiving module 10 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 20 is configured to confirm a target echo signal of the target object from the echo signals; the difference value calculation module 30 is configured to perform phase unwrapping and phase difference calculation on the target echo signal to obtain a difference value; the filtering module 40 is configured to filter the difference value to obtain a respiration signal and a heartbeat signal; the frequency analysis module 50 is configured to perform frequency analysis on the respiration signal to obtain a respiration frequency, and perform frequency analysis on the heartbeat signal to obtain a heartbeat frequency.
In this embodiment, the contactless vital sign detection device realizes a contactless detection method of vital signs 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 contactless vital sign detection device corresponds to each step of the contactless vital sign detection method, and has the same technical solution, so that the same technical problems are solved, and the same technical effects are brought, which are not described in detail herein.
Embodiments of a third aspect of the invention provide a contactless vital signs detection device. Contactless vital signs detection device comprises: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the contactless vital sign detection method according to the first aspect of the invention when executing the computer program.
The processor and memory may be connected by a bus or other means.
The memory, which is a non-transitory computer readable storage medium, may be used to store non-transitory software programs as well as non-transitory computer executable programs. Further, the memory may include high speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory optionally includes memory located remotely from the processor, and these remote memories may be connected to the processor through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The above described node embodiments are merely illustrative, wherein the units illustrated as separate components may or may not be physically separate, i.e. may be located in one place, or may also be distributed over a plurality of network elements. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
An embodiment of a fourth aspect of the invention provides a storage medium. The storage medium stores a computer program for performing the contactless vital signs detection method according to the first aspect of the 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 known to those skilled in the art.
The above description is only a preferred embodiment of the present invention, and the present invention is not limited to the above embodiment, 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 for contactless detection of vital signs, 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;
and carrying out frequency analysis on the respiration signal to obtain the respiration frequency, and carrying out frequency analysis on the heartbeat signal to obtain the heartbeat frequency.
2. The contactless vital sign detection method according to claim 1, wherein the confirming a target echo signal of the target subject from the echo signal 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.
3. The contactless vital sign detection method according to claim 2, wherein the short-time fourier transform corresponds to an equation:
where f [ n ] is the echo signal, w [ n ] is the window function of the short-time Fourier transform, m is the distance size of each sliding of the window function, and w is the angular frequency.
4. The method according to claim 1, wherein the filtering the differential value to obtain a respiration 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.
5. The contactless vital sign detection method of claim 4, wherein 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.
6. The method of claim 1, wherein the frequency analyzing the respiration signal to obtain a respiration frequency comprises:
performing wavelet transformation on the respiration signal to obtain a first respiration processing signal;
performing multi-resolution analysis on the first respiration processing signal to obtain a second respiration processing signal;
performing weighting processing on the second respiration processing signal to obtain a third respiration processing signal;
and performing frequency spectrum estimation on the third respiration processing signal to obtain the respiration frequency.
7. The method for contactless vital sign detection according to claim 1, wherein the frequency analysis of the heartbeat signal to obtain a heartbeat frequency comprises:
performing wavelet transformation on the heartbeat signal to obtain a first heartbeat processing signal;
performing multi-resolution analysis on the first heartbeat processing signal to obtain a second heartbeat processing signal;
weighting the second heartbeat processing signal to obtain a third heartbeat processing signal;
and performing frequency spectrum estimation on the third heartbeat processing signal to obtain the respiratory frequency.
8. Contactless vital sign detection device, its characterized in that includes:
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;
and the frequency analysis module is used for carrying out frequency analysis on the respiration signal to obtain the respiration frequency and carrying out frequency analysis on the heartbeat signal to obtain the heartbeat frequency.
9. Contactless living body sign detection device, comprising: memory, processor and computer program stored on the memory and executable on the processor, characterized in that the processor implements the contactless vital sign detection method according to any of claims 1 to 7 when executing the computer program.
10. Storage medium, characterized in that a computer program is stored for performing the contactless vital sign detection method according to any of claims 1 to 7.
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