CN113633271B - Human body activity state detection method, device, equipment and storage medium - Google Patents

Human body activity state detection method, device, equipment and storage medium Download PDF

Info

Publication number
CN113633271B
CN113633271B CN202111207305.6A CN202111207305A CN113633271B CN 113633271 B CN113633271 B CN 113633271B CN 202111207305 A CN202111207305 A CN 202111207305A CN 113633271 B CN113633271 B CN 113633271B
Authority
CN
China
Prior art keywords
state
human body
frame
voltage value
preset
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202111207305.6A
Other languages
Chinese (zh)
Other versions
CN113633271A (en
Inventor
何至军
曹丽娜
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beijing Longzhi Digital Technology Service Co Ltd
Original Assignee
Shanghai Zhuohan Technology Co ltd
Beijing Zhuojianzhihan Technology Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Shanghai Zhuohan Technology Co ltd, Beijing Zhuojianzhihan Technology Co ltd filed Critical Shanghai Zhuohan Technology Co ltd
Priority to CN202111207305.6A priority Critical patent/CN113633271B/en
Publication of CN113633271A publication Critical patent/CN113633271A/en
Application granted granted Critical
Publication of CN113633271B publication Critical patent/CN113633271B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves 
    • A61B5/0507—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves  using microwaves or terahertz waves
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7203—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
    • A61B5/7207—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal of noise induced by motion artifacts

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Public Health (AREA)
  • Molecular Biology (AREA)
  • Veterinary Medicine (AREA)
  • Signal Processing (AREA)
  • Physics & Mathematics (AREA)
  • General Health & Medical Sciences (AREA)
  • Biophysics (AREA)
  • Pathology (AREA)
  • Biomedical Technology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Medical Informatics (AREA)
  • Animal Behavior & Ethology (AREA)
  • Surgery (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Artificial Intelligence (AREA)
  • Psychiatry (AREA)
  • Physiology (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Radiology & Medical Imaging (AREA)
  • Radar Systems Or Details Thereof (AREA)
  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)

Abstract

The disclosure relates to the technical field of human body detection of electromagnetic waves, and provides a human body activity state detection method, a human body activity state detection device, human body activity state detection equipment and a storage medium. The method comprises the following steps: acquiring echo signals generated in continuous frames, analyzing to obtain voltage values of the echo signals, and determining a state decision weight corresponding to a signal wave of each frame according to the voltage values of the echo signals and the voltage value of the spatial noise; calculating a state value corresponding to each frame according to the state decision weight and the voltage value of the echo signal, comparing the state value corresponding to each frame with a standard value of a preset human body state, and determining the human body state corresponding to each frame according to a comparison result; and detecting the activity state of the human body according to the human body state corresponding to the continuous frames in the preset time and a preset decision rule. The method and the device can realize the recognition of the human body state based on the microwave signal, thereby accurately judging the activity state of the human body and improving the application range of detecting the vital signs of the human body by utilizing the microwave.

Description

Human body activity state detection method, device, equipment and storage medium
Technical Field
The present disclosure relates to the field of electromagnetic wave human body detection technologies, and in particular, to a method, an apparatus, a device, and a storage medium for detecting a human body activity state.
Background
The microwave radar is a novel non-contact physiological signal monitoring method for monitoring physiological parameters of human bodies. The microwave radar transmits radio frequency waves with a certain frequency, the radio frequency waves generate reflected waves after contacting a human body, so that the fluctuation of the respiration and heartbeat of the human body is induced, and the frequency information of the respiration and heartbeat can be obtained by performing phase demodulation on the reflected waves.
In the prior art, although phase demodulation can be performed on a reflected signal of a microwave radar, frequency information of respiration and heartbeat can be obtained, and non-contact detection of a vital sign is realized based on the frequency information of the respiration and the heartbeat. However, in such a detection method of collecting microwave signals reflected by a detection object by using a microwave radar to perform respiration and heartbeat, it is impossible to sense and detect different activity states of a human body, i.e., it is impossible to distinguish and judge different activity states of a human body, and it is impossible to achieve the purpose of judging the activity state of a human body based on the activity state of a human body for a certain period of time, and therefore, it is impossible to accurately judge the activity state of a human body.
Disclosure of Invention
In view of this, embodiments of the present disclosure provide a method, an apparatus, a device and a storage medium for detecting a human activity state, so as to solve the problem that in the prior art, different human activity states cannot be distinguished and determined, and the human activity state cannot be accurately determined.
In a first aspect of the embodiments of the present disclosure, a method for detecting a human activity state is provided, including: acquiring echo signals generated in preset continuous frames, wherein the echo signals are signal waves reflected back after microwave is emitted into a preset space by using a microwave antenna, and the continuous frames represent a plurality of continuous time intervals; analyzing a plurality of echo signals generated in each frame to obtain a voltage value corresponding to each echo signal, and determining a state decision weight corresponding to a signal wave of each frame according to the voltage value corresponding to the echo signal and the voltage value corresponding to the spatial noise; calculating to obtain a state value corresponding to each frame according to the state decision weight and a voltage value corresponding to the echo signal, comparing the state value corresponding to each frame with a standard value of a preset human body state, and determining the human body state corresponding to each frame according to a comparison result; and detecting the activity state of the human body according to the human body state corresponding to the continuous frames in the preset time and a preset decision rule.
In a second aspect of the embodiments of the present disclosure, there is provided a human activity state detection apparatus, including: the device comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is configured to acquire echo signals generated in preset continuous frames, the echo signals are signal waves reflected back after microwave is emitted into a preset space by using a microwave antenna, and the continuous frames represent a plurality of continuous time intervals; the analysis module is configured to analyze a plurality of echo signals generated in each frame to obtain a voltage value corresponding to each echo signal, and determine a state decision weight corresponding to a signal wave of each frame according to the voltage value corresponding to the echo signal and the voltage value corresponding to the spatial noise; the comparison module is configured to calculate a state value corresponding to each frame according to the state decision weight and the voltage value corresponding to the echo signal, compare the state value corresponding to each frame with a standard value of a preset human body state, and determine the human body state corresponding to each frame according to a comparison result; and the judging module is configured to detect the activity state of the human body according to the human body state corresponding to the continuous frames in the preset time and a preset decision rule.
In a third aspect of the embodiments of the present disclosure, an electronic device is provided, which includes a memory, a processor and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the method when executing the program.
In a fourth aspect of the embodiments of the present disclosure, a computer-readable storage medium is provided, which stores a computer program, which when executed by a processor, implements the steps of the above-mentioned method.
The embodiment of the present disclosure adopts at least one technical scheme that can achieve the following beneficial effects:
acquiring echo signals generated in preset continuous frames, wherein the echo signals are signal waves reflected back after microwaves are transmitted into a preset space by using a microwave antenna, and the continuous frames represent a plurality of continuous time intervals; analyzing a plurality of echo signals generated in each frame to obtain a voltage value corresponding to each echo signal, and determining a state decision weight corresponding to a signal wave of each frame according to the voltage value corresponding to the echo signal and the voltage value corresponding to the spatial noise; calculating to obtain a state value corresponding to each frame according to the state decision weight and a voltage value corresponding to the echo signal, comparing the state value corresponding to each frame with a standard value of a preset human body state, and determining the human body state corresponding to each frame according to a comparison result; and detecting the activity state of the human body according to the human body state corresponding to the continuous frames in the preset time and a preset decision rule. According to the method and the device, the human body states corresponding to different frames can be judged based on the analysis of the voltage value of the echo signal of the microwave antenna, and the detection of the human body activity state is realized based on the human body states corresponding to continuous frames, so that different human body activity states can be accurately identified, and the application range of the microwave to the detection of human body vital signs is expanded.
Drawings
To more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings needed for the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without inventive efforts.
FIG. 1 is a schematic diagram of the overall architecture of a system involved in an actual application scenario in accordance with an embodiment of the present disclosure;
fig. 2 is a schematic flow chart of a human activity state detection method provided by an embodiment of the present disclosure;
FIG. 3 is a waveform diagram illustrating the generation of average voltage values within a frame in a practical application scenario according to an embodiment of the present disclosure;
FIG. 4 is a schematic diagram of a digital square wave corresponding to a code of a body motion state provided by an embodiment of the present disclosure;
FIG. 5 is a schematic diagram of a digital square wave corresponding to the encoding of the activity state of the thoracic cavity provided by the embodiment of the present disclosure;
FIG. 6 is a schematic diagram of a digital square wave encoded in response to an activity state of a heart rhythm provided by an embodiment of the present disclosure;
fig. 7 is a schematic diagram of a digital square wave of human body state coding corresponding to consecutive frames within a preset time according to an embodiment of the present disclosure;
fig. 8 is a schematic structural diagram of a human activity state detection device provided in an embodiment of the present disclosure;
fig. 9 is a schematic structural diagram of an electronic device provided in an embodiment of the present disclosure.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the disclosed embodiments. However, it will be apparent to one skilled in the art that the present disclosure may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present disclosure with unnecessary detail.
The microwave radar is used for emitting microwaves with a certain frequency to a space, the emitted microwaves directly irradiate a human body, the respiration and heartbeat of the human body can cause expansion change of the chest and the lung, corresponding reflected waves can be generated due to the change of the micro dynamic state of the human body, the frequency information of the respiration and the heartbeat can be obtained by performing phase demodulation on the radar reflected waves, and the non-contact detection of vital signs is realized. The detection of human vital signs based on the microwave radar has wide application in the fields of health care, intelligent home and the like. In the prior art, microwave signals are transmitted to a human body through a microwave radar, the microwave signals reflected from the human body contain information of thoracic cavity vibration of the human body, information of respiratory and heartbeat frequencies of the human body and the like can be extracted from the microwave signals through a certain signal processing method, and the information can be used for daily basic physiological sign detection and health monitoring. The technology of sensing the respiratory and heartbeat frequencies of the human body using microwave radar is relatively mature and will not be described in detail here.
However, in the prior art, the frequency information of respiration and heartbeat can be obtained by performing phase demodulation on the reflected signal of the microwave radar, and the non-contact detection of the vital sign is realized based on the frequency information of respiration and heartbeat. However, in such a detection method of collecting microwave signals reflected by a detection object by using a microwave radar to perform respiration and heartbeat, it is impossible to sense and detect different activity states of a human body, i.e., it is impossible to distinguish and judge different activity states of a human body, and it is impossible to achieve the purpose of judging the activity state of a human body based on the activity state of a human body for a certain period of time, and therefore, it is impossible to accurately judge the activity state of a human body.
In addition, in some practical application scenarios, the microwave radar is required to be capable of detecting the expansion change of the chest and the lung of the human body and the change of a small body movement (such as finger movement, four-limb movement and the like) of the human body so as to acquire more accurate echo signals, and accurate and stable state analysis is realized based on the echo signals obtained by reflecting the small body movement change, so that the human body activity condition in a certain space can be accurately judged. However, the existing microwave radar is applied to sensing a large dynamic range of a human body, for example, the large dynamic range is sensed to determine whether a person exists in a certain space, so that the detection of a small dynamic range (such as chest expansion, small body movement, etc.) of the human body in the certain space cannot be accurately and stably performed, that is, the accurate detection of the small dynamic range of the human body cannot be realized.
In view of the above problems in the prior art, it is desirable to provide a detection scheme capable of distinguishing and determining different human activity states based on analysis of an echo signal of a microwave antenna, so as to detect a small dynamic state of a human body in a certain space, thereby determining a human activity state more accurately. The overall architecture of the system according to the embodiment of the present disclosure is described below with reference to the accompanying drawings, and fig. 1 is a schematic diagram of the overall architecture of the system according to the embodiment of the present disclosure in an actual application scenario. As shown in fig. 1, the overall architecture of the system related to the general diagram generation scheme may specifically include:
the system overall architecture related to the embodiment of the disclosure comprises a radar module and a processing module, wherein the radar module comprises a microwave antenna unit, a signal gain unit and a signal analysis unit, and the processing module comprises a temporary storage unit, a core processing unit and a communication unit; the radar module and the processing module are connected in a wired or wireless mode,
in practical applications, the radar module and the processing module may be specific physical unit modules, which are integrated in the same device, for example, all the unit modules may be configured in a microwave radar, or the processing module may be configured as a single physical unit module, and the radar module and the processing module are connected through wireless communication. Of course, it is understood that some units in the radar module and the processing module may be virtual unit modules, and the functions of these virtual unit modules may be implemented by an algorithm, in this case, some functions in the radar module and the processing module may be implemented based on independent background servers.
Furthermore, in the radar module, the antenna unit may be composed of several groups of microwave antennas, the microwave antennas integrate power transmission and reception, and the space scanning is realized by transmitting microwave signals into the space and by reflection and scattering; because the energy of the returned echo signal may not satisfy the analysis condition, a signal gain unit is required to perform signal amplification and noise filtering processing on the echo signal received by the antenna unit, and the signal gain unit may include a microwave amplifier and a microwave filter; and the linear wave pattern of the microwave signal processed by the signal gain unit is subjected to digital processing by using a signal analysis unit, and a decision signal is generated.
In the processing module, a temporary storage module is used for storing and sorting decision signals generated by the radar module in continuous time intervals, and all decision signals obtained by sorting in preset time are sent to a core processing unit; and analyzing the decision signal by using the core processing unit, judging the decision signal continuously generated in the preset time by using a preset decision rule so as to determine the human activity state of the detected object in the time, carrying out data coding on the judgment result and sending out the information through the communication unit.
It should be noted that, in order to receive the echo signal more accurately and avoid the interference of excessive noise on the determination result in practical applications, the apparatus composed of the radar module and the processing module (for example, the apparatus is integrated into a radar apparatus having the above function) may be placed near the object to be detected, for example, below or around the bed. The following embodiments of the present disclosure are described with reference to detecting a human activity state of a subject during a sleep process as an example, however, the embodiments of the present disclosure are not limited to detecting a human activity state during a sleep process, and the detection of a human activity state in other application scenarios is also applicable to the present solution, for example, the detection of a human activity state in a rescue environment, and the application scenarios of the embodiments of the present disclosure do not constitute a limitation to the present technical solution.
Fig. 2 is a schematic flow chart of a human activity state detection method provided by the embodiment of the disclosure. The human activity state detection method of fig. 2 may be performed by the microwave radar alone or the microwave radar in combination with the server. As shown in fig. 2, the method for detecting a human activity state may specifically include:
s201, acquiring echo signals generated in preset continuous frames, wherein the echo signals are signal waves reflected back after microwave is emitted into a preset space by using a microwave antenna, and the continuous frames represent a plurality of continuous time intervals;
s202, analyzing a plurality of echo signals generated in each frame to obtain a voltage value corresponding to each echo signal, and determining a state decision weight corresponding to a signal wave of each frame according to the voltage value corresponding to the echo signal and the voltage value corresponding to the spatial noise;
s203, calculating to obtain a state value corresponding to each frame according to the state decision weight and the voltage value corresponding to the echo signal, comparing the state value corresponding to each frame with a standard value of a preset human body state, and determining the human body state corresponding to each frame according to the comparison result;
and S204, detecting the activity state of the human body according to the human body state corresponding to the continuous frames in the preset time and a preset decision rule.
Specifically, the frames in the embodiment of the present disclosure are not image frames in the conventional sense, but a process of transmitting electromagnetic waves to the space by the microwave antenna and receiving echo signals in a certain time interval is referred to as a frame, and therefore, the time interval corresponding to a frame may be customized, for example, a microwave transmission and recovery process in 0.1s time is regarded as a frame. The microwave antenna receives an echo signal once every time it transmits an electromagnetic wave, and the returned echo signal may be a wave-type signal, that is, the microwave signal is wave-type data having a certain wave crest, wavelength and frequency, wherein the wave crest corresponds to a voltage value of each microwave signal.
Further, the spatial noise is multipath noise or gaussian noise generated by electromagnetic waves emitted into the space by the microwave antenna and ejected in the space, for example, gaussian noise generated by mutual interference between the antennas, and the spatial noise is reflected as some burrs or oscillations in the waveform in the echo signal, so the spatial noise returned to the microwave antenna can also be regarded as some voltage values.
Further, the preset standard value of the human body state refers to a standard voltage value corresponding to the preset human body state, and the closer the state value corresponding to the waveform of each frame is to the standard voltage value, the closer the frame is to a certain human body state, for example, the standard voltage value of the human body state is 5V, and the calculated state value of a certain frame is 4.9V, so that the human body state corresponding to the frame can be considered as the human body state. In practical applications, the preset human body state includes, but is not limited to, the following states: body motion state, thoracic activity state, cardiac rhythm activity state, and the like.
Here, the embodiment of the present disclosure is to analyze and process the echo signal in units of frames, and multiple echo signals may be received within one frame, for example, a time interval of one echo is 0.01s, and a time interval of one frame is 0.1s, so that 10 echo signals are received by the microwave antenna within one frame. Meanwhile, the embodiment of the present disclosure may include multiple groups of microwave antennas, and therefore, each group of microwave antennas may receive the echo signal, that is, multiple echoes may be generated in each frame, each echo corresponds to the echo signal of the multiple groups of antennas, and after the echo signal generated by each echo is analyzed, a voltage value matrix may be obtained, where the voltage value matrix includes voltage values corresponding to the echo signals of the multiple groups of microwave antennas, respectively.
According to the technical scheme provided by the embodiment of the disclosure, the echo signal generated in each frame is obtained, the voltage value matrix generated by multiple echoes in each frame is based on, wherein each echo corresponds to one voltage value matrix, and the average voltage value in each echo is determined according to the voltage value matrix; calculating a state decision weight corresponding to each frame based on the average voltage values corresponding to all echoes and the voltage values corresponding to the spatial noise, determining the state value of each frame according to the state decision weight and the average voltage values, and comparing the state value of each frame with a standard value of a preset human body state so as to output the human body state corresponding to each frame; and finally, detecting the human body activity state by utilizing a pre-configured decision rule according to a series of human body states generated in a preset time. According to the method and the device, the human body states corresponding to different frames can be judged based on the analysis of the voltage value of the echo signal of the microwave antenna, and the detection of the human body activity state is realized based on the human body states corresponding to continuous frames, so that different human body activity states can be accurately identified, and the application range of the microwave to the detection of human body vital signs is expanded.
In some embodiments, after acquiring the echo signals generated in the preset continuous frames, the method further comprises: and performing a signal amplification operation on the received echo signal by using a microwave amplifier, and performing a noise filtering operation on the echo signal after the signal amplification by using a microwave filter, wherein the echo signal after the noise filtering is taken as an analysis object.
Specifically, since the energy of the echo signal returned to the microwave antenna may be relatively low and the returned echo signal cannot be directly analyzed, it is necessary to amplify the received echo signal by a microwave amplifier, and since multipath noise or gaussian noise is generated when the electromagnetic wave is ejected in the space, it is necessary to perform noise filtering on the echo signal after the signal amplification by a microwave filter after the echo signal is amplified. Here, the conventional technical solutions may be adopted for both signal amplification by the microwave amplifier and noise filtering by the microwave filter, so that the embodiments of the present disclosure do not describe the principle and specific implementation process of signal amplification and noise filtering, and all methods that can implement signal amplification and noise filtering on echo signals are applicable to this scheme.
In some embodiments, the echo signals include echo signals received by multiple sets of microwave antennas, respectively; analyzing a plurality of echo signals generated in each frame to obtain a voltage value corresponding to each echo signal, comprising: each group of microwave antennas receives echo signals reflected by multiple times of space in each frame, and the voltage value corresponding to each echo signal is determined according to the peak information corresponding to the echo signal reflected by each microwave; generating a voltage value matrix corresponding to each microwave reflection according to the voltage value corresponding to each group of microwave antennas, and performing normalization processing on the voltage value matrix to obtain an average voltage value corresponding to each microwave reflection of a plurality of groups of microwave antennas; wherein the microwaves emitted by each group of microwave antennas have different wavelengths and frequencies.
Specifically, the embodiment of the present disclosure may include multiple sets of microwave antennas, where each set of microwave antennas transmits electromagnetic waves and receives echo signals separately, and each set of microwave antennas may use different wave bands and frequencies, that is, electromagnetic waves with microwave frequencies between 300MHz and 300GHz may be used. In practical applications, since multiple reflections and backreturns may occur within a time interval of one frame, each group of microwave antennas corresponds to one voltage value during each time of the backreturn, that is, each group of microwave antennas corresponds to one voltage value matrix during each time of the backreturn of the electromagnetic wave signal.
The following describes a process of generating an average voltage value based on each echo in each frame with reference to the accompanying drawings, and fig. 3 is a schematic diagram of a waveform formed by the average voltage values generated in one frame in a practical application scenario according to the embodiment of the present disclosure. As shown in fig. 3, the specific process of forming the waveform by the average voltage value generated in the frame may include:
the voltage value of the echo signal is determined based on the amplitude corresponding to the wave pattern of the echo signal, and the information feedback received by the microwave antenna (i.e. the echo signal) generates different amplitudes and frequencies, wherein the amplitude is represented by the amplitude in the wave pattern of the echo signal, i.e. the intensity relationship represented by the value V, and the frequency represents the generation period of each echo signal. For example: assuming that there are four groups of microwave antennas, voltage values of echo signals corresponding to the four groups of microwave antennas in echoes of a microwave antenna are respectively 3V, 2V, 5V and 8V, the voltage values of the four groups of microwave antennas form a voltage value matrix, an average voltage value generated by the four groups of microwave antennas during the microwave reflection at this time is obtained by performing normalization processing on the voltage value matrix, that is, calculating an average value corresponding to all the voltage values in the voltage value matrix, and continuing the above embodiment, the average voltage value calculated at this time is 4.5V.
H in FIG. 301～H06Representing the average voltage value, i.e. H, corresponding to 6 echoes of a frame01When echo is generated for the first time in the frame, the average voltage value calculated according to the voltage values corresponding to the multiple groups of microwave antennas is expressed, and H is the same06Indicating that echoes are generated according to multiple groups when the sixth time isCalculating an average voltage value obtained by the voltage value corresponding to the microwave antenna; the average voltage values corresponding to all echoes in a frame are represented by a wave pattern by calculating the average voltage value corresponding to each echo of a plurality of groups of microwave antennas in the frame.
According to the technical scheme provided by the embodiment of the disclosure, by calculating the average value of the voltage values corresponding to the multiple groups of microwave antennas when each echo is generated in each frame, according to the average voltage values generated by all echoes in the frame, a wave pattern corresponding to the frame can be obtained, and the echo with the maximum average voltage value corresponding to the wave peak can be obtained. Because the wave mode can be deviated differently under different human body behavior states, the corresponding behavior state of each current frame is analyzed through the echo signal, so that the human body activity state under continuous frames can be judged based on the behavior state of each frame.
In some embodiments, determining the state decision weight corresponding to the signal wave of each frame according to the voltage value corresponding to the echo signal and the voltage value corresponding to the spatial noise includes: extracting spatial noise from echo signals of multiple spatial reflections received by multiple groups of microwave antennas in each frame, and determining a voltage value corresponding to the spatial noise according to signal waves corresponding to the echo signals; calculating a state decision weight corresponding to the signal wave of each frame according to an average voltage value corresponding to a plurality of microwave reflections of the microwave antennas in each frame and a voltage value corresponding to the space noise in each frame; the space noise includes multipath noise and gaussian noise generated when the microwave is ejected in the space.
Specifically, the spatial noise refers to an overall noise generated in one frame due to the spatial reflection of microwaves and the mutual interference between microwave antennas, that is, the spatial noise represents the noise generated in the echo process, and the state decision weight corresponding to the signal wave of each frame is calculated by increasing the spatial noise, so that the result of the state decision weight can reflect the phenomenon generated in the physical space. Since the spatial noise is reflected in the echo signal as some glitch or oscillation, the voltage value of the spatial noise may be determined based on the amplitude corresponding to the oscillation wave in the echo signal.
Further, after the average voltage value corresponding to each frame and the voltage value of the spatial noise corresponding to each frame of the multiple groups of microwave antennas calculated based on the foregoing embodiment, the following formula may be used to calculate the state decision weight corresponding to the signal wave of each frame:
Figure 430715DEST_PATH_IMAGE001
wherein the content of the first and second substances,
Figure 697749DEST_PATH_IMAGE002
indicating the state decision weight corresponding to a certain frame signal wave,
Figure 365490DEST_PATH_IMAGE003
represents the average voltage value corresponding to a plurality of microwave reflections in a certain frame,
Figure 34369DEST_PATH_IMAGE004
indicating the maximum number of microwave reflections within a certain frame,
Figure 745842DEST_PATH_IMAGE005
representing the voltage value corresponding to the spatial noise within a certain frame.
It should be noted that, when actually calculating the state decision weight corresponding to each frame of signal wave, the voltage value of the spatial noise may not be considered, and only the average voltage value corresponding to each echo in each frame needs to be calculated, and the value of the state decision weight may be represented by a percentage.
In some embodiments, calculating the state value corresponding to each frame according to the state decision weight and the voltage value corresponding to the echo signal includes: and determining the maximum average voltage value according to the average voltage value corresponding to multiple microwave reflections in each frame, and taking the product of the state decision weight corresponding to the signal wave of each frame and the maximum average voltage value of the same frame as the state value of the frame.
Specifically, after obtaining the average voltage value corresponding to each echo in each frame, all the average voltage values are put together for comparison, the maximum average voltage value is selected, and the state decision weight obtained by the previous calculation is multiplied by the maximum average voltage value to obtain a specific voltage value. For example: a total of 5 echoes are generated in a certain frame, the average voltage value corresponding to each echo is 5.3V, 5.8V, 6.2V, 5.7V and 5.5V, respectively, then the maximum average voltage value corresponding to the frame is 6.2V, and assuming that the state decision weight is 0.7, the state value corresponding to the frame is 4.34V.
In some embodiments, comparing the state value corresponding to each frame with a standard value of a preset human body state, and determining the human body state corresponding to each frame according to the comparison result includes: sequentially comparing the state value corresponding to each frame with the standard value of the preset human body state, and taking the preset human body state corresponding to the standard value meeting the preset requirement in the comparison result as the human body state corresponding to the frame; the preset requirements comprise that the difference value between the state value and the standard value is within a certain threshold range, and the preset human body state comprises a body movement state, a thoracic cavity activity state and a heart rhythm activity state.
Specifically, after the state value corresponding to each frame is calculated, the state value of each frame is compared with the standard values, that is, the state value is closer to which standard value, and the closer the state value is to which standard value, the closer the human body state corresponding to the frame is to the preset human body state corresponding to which standard value. The term "close to a numerical value" means that the state value is within a certain fluctuation range of the standard value, that is, the difference between the state value and the standard value is within a certain threshold range, for example, the fluctuation range is 10% of the standard value, and the difference between the state value and the standard value is only within 10% of the standard value.
Further, in one embodiment, if used, the
Figure 500171DEST_PATH_IMAGE006
To indicate the state of a human body corresponding to a certain frame
Figure 706025DEST_PATH_IMAGE007
Representing the basic data (i.e. voltage standard value) corresponding to each preset state by comparing the state value of a certain frame with that of the voltage standard value
Figure 229410DEST_PATH_IMAGE007
The relationship between can be obtained
Figure 128096DEST_PATH_IMAGE006
The output result of (1); in practical applications, for example: the voltage standard values respectively corresponding to the body movement state, the thoracic cavity activity state and the heart rhythm activity state
Figure 369721DEST_PATH_IMAGE007
5V, 3V and 2V, and the state value corresponding to a frame is 4.3V, it is obvious that the state value corresponding to the frame is closer to the standard value of 3V, and therefore, it can be determined that the human body state corresponding to the frame is the chest activity state, i.e. the state of the human body corresponding to the frame is the chest activity state
Figure 644845DEST_PATH_IMAGE006
The corresponding output result is a digital representation corresponding to the activity state of the thoracic cavity.
In some embodiments, after determining the human body state corresponding to each frame according to the comparison result, the method further includes: and respectively coding the human body state corresponding to each frame, and storing the codes of the human body states corresponding to the continuous frames within the preset time, wherein the coding of the human body states comprises representing the human body states in a digital square wave mode.
Specifically, each preset human body state corresponds to a code, for example, the code corresponding to the body movement state is 10, the code corresponding to the chest cavity activity state is 11, and the code corresponding to the heart rhythm activity state is 01; the coding of the human body state corresponding to each frame is expressed in the form of digital square waves. The digital square waves corresponding to the codes of the three preset human body states are described below with reference to fig. 4, fig. 5 and fig. 6, where fig. 4 is a schematic diagram of the digital square waves corresponding to the codes of the body motion states provided by the embodiment of the present disclosure, fig. 5 is a schematic diagram of the digital square waves corresponding to the codes of the thoracic cavity activity states provided by the embodiment of the present disclosure, and fig. 6 is a schematic diagram of the digital square waves corresponding to the codes of the heart rhythm activity states provided by the embodiment of the present disclosure. As shown in fig. 4 to 6, the encoding process of the human body state may include:
the different preset human body states correspond to different codes, the codes of each human body state are transmitted in a digital square wave mode according to the codes of the different human body states, namely the human body states are coded according to the human body states corresponding to each frame determined through calculation to generate digital square waves, and a horizontal axis T in the attached drawing represents the time of the frames corresponding to the human body states in the whole process, so that the different human body states are expressed by the digital square waves in the embodiment of the disclosure. In practical application, the process of judging the human body state corresponding to each frame and generating the digital square waves based on the judgment result is realized in a signal analysis unit of the radar module, and the signal analysis unit sequentially sends the digital square waves corresponding to each frame to a temporary storage unit of the processing module for storage.
In some embodiments, detecting the human activity state according to the human state corresponding to the consecutive frames within the preset time and a pre-configured decision rule includes: drawing the digital square waves of the human body state corresponding to the continuous frames on the same time axis according to the stored digital square waves of the human body state corresponding to the continuous frames within the preset time, and detecting the digital square waves corresponding to the continuous frames on the time axis according to a preset decision rule to obtain a detection result of the human body activity state; the pre-configured decision rule is used for detecting the human body activity state continuously represented by the digital square waves on the time axis according to the digital square waves corresponding to the continuous frames.
Specifically, the temporary storage unit can store digital square waves corresponding to continuous frames within a certain preset time, and each digital square wave corresponds to a human body state, so that after temporary storage for a certain preset time, a continuous digital square wave can be sorted out. The signal analysis unit sends the state information corresponding to each frame to the temporary storage unit for data storage and accumulation, and variation statistics of continuous human body states within a certain preset time is formed. And then, analyzing the codes of the continuous human body states with the duration corresponding to the preset time by the core processing unit so as to judge the human body activity state.
Further, the following describes a process of determining a human activity state according to human states corresponding to consecutive frames within a preset time with reference to the accompanying drawings, and fig. 7 is a schematic diagram of a digital square wave of a human state code corresponding to consecutive frames within a preset time according to an embodiment of the present disclosure. As shown in fig. 7, the process of determining the human activity state may include:
the digital square waves corresponding to the continuous frames within the preset time (for example, within 3 s) are placed on the same time axis to form the digital square waves corresponding to the continuous frames within the preset time, and if the digital square waves corresponding to the continuous frames can represent the change of the human body state within the preset time, if there are ten continuous frames in the preset time, the first frame is a body motion state, the second frame to the sixth frame are chest activity states, the seventh frame is a heart rate activity state, the eighth frame and the ninth frame are body motion states, and the tenth frame is a heart rate activity state, the activity state of the human body within the preset time can be further judged based on the analysis of the change of the human body state of the continuous frames.
In some embodiments, the pre-configured decision rule comprises: when the number of the digital square waves used for representing the body motion state in the digital square waves corresponding to the continuous frames is larger than a preset threshold value, judging that the human body activity state in a preset time is a first activity state; when the number of the digital square waves used for representing the thoracic cavity activity state or the heart rhythm activity in the digital square waves corresponding to the continuous frames is smaller than a preset threshold value, judging that the human body activity state in a preset time is a second activity state; and when the digital square waves used for representing the body motion state, the thoracic cavity activity state and the heart rhythm activity in the digital square waves corresponding to the continuous frames are irregularly arranged, judging that the human body activity state in the preset time is a third activity state.
Specifically, the pre-configured decision rule is used for analyzing the activity state of the human body according to the change of the state of the human body, which is shown by the digital square waves corresponding to the continuous frames, different detected objects or the same detected object can show different state changes in different time, and the activity state of the human body represented by the different state changes can be known based on the research on the rules of the different state changes of the human body. For example, if a certain detected object has a body movement state for 3 times or more within 10s, it can be determined that the sleep quality of the detected object is poor; for another example, when the number of occurrences of the chest activity state of a certain detected subject within 10s is less than a preset threshold, it can be determined that the vital sign of the detected subject is weak; for another example, if the movement state and the thoracic activity state of a certain detected object alternately appear within 10s and the number of occurrences is irregular, it can be determined that there is a problem between the breathing and the sleeping of the detected object.
Further, the decision rule may be configured according to actual usage scenarios and definitions of different human activity states, for example, in the embodiments of the present disclosure, including but not limited to the following decision rules:
the method comprises the steps that a first decision rule is that when the number of digital square waves representing the body motion state is larger than a preset threshold value, the human body motion state in a preset time is judged to be a first motion state; that is, when the human body state of multiple body movements of the detected object occurs within the preset time, it indicates that the detected object is in the first activity state, and the first activity state may be considered as a state with poor sleep quality.
According to a decision rule II, when the number of digital square waves used for representing the thoracic cavity activity state or the heart rhythm activity in the digital square waves corresponding to the continuous frames is smaller than a preset threshold value, the human body activity state in a preset time is judged to be a second activity state; that is, when the number of times of breathing and heartbeat of the detected subject in the preset time is lower than the preset number threshold, it indicates that the detected subject is in the second active state, and the second active state can be regarded as a state with poor breathing quality or weak vital signs.
A third decision rule, when the digital square waves used for representing the body motion state, the thoracic cavity activity state and the heart rhythm activity in the digital square waves corresponding to the continuous frames are irregularly arranged, judging that the human body activity state in the preset time is a third activity state; that is, when the breathing and the body movement of the detected object exhibit irregular state changes within the preset time, it indicates that the detected object is in a third active state, and the third active state can be regarded as a state in which the breathing and the behavior are unstable during the sleep.
According to the technical scheme provided by the embodiment of the disclosure, the electromagnetic waves are transmitted to the preset space, the echo signals are continuously received through a plurality of groups of microwave antennas, the average voltage value corresponding to each echo is calculated, the state decision weight corresponding to each frame signal is determined according to a plurality of average voltage values generated in each frame in a continuous frame, the state value corresponding to each frame is solved according to the state decision weight of each frame, the human body state corresponding to each frame can be determined based on the comparison between the state value of each frame and the standard value of the preset human body state, and finally the activity state of the human body in a certain time can be judged based on the analysis of the human body state change of the continuous frame. The system analyzes the human body state with high precision through electromagnetic waves, realizes dynamic human body state judgment, can detect the change state of the thoracic cavity, and realizes the recognition of the human body breathing state; by analyzing the change of the human behavior state, the judgment of the sleep quality, the respiratory quality and the behavior quality of the human body can be further realized, the activity management of the tested object is assisted, and the application range of detecting the vital signs of the human body by utilizing microwaves is expanded.
The following are embodiments of the disclosed apparatus that may be used to perform embodiments of the disclosed methods. For details not disclosed in the embodiments of the apparatus of the present disclosure, refer to the embodiments of the method of the present disclosure.
Fig. 8 is a schematic structural diagram of a human activity state detection device provided in an embodiment of the present disclosure. As shown in fig. 8, the human activity state detection apparatus includes:
an obtaining module 801 configured to obtain an echo signal generated in a preset continuous frame, where the echo signal is a signal wave reflected back after a microwave is emitted into a predetermined space by using a microwave antenna, and the continuous frame represents a plurality of continuous time intervals;
an analysis module 802 configured to analyze a plurality of echo signals generated in each frame to obtain a voltage value corresponding to each echo signal, and determine a state decision weight corresponding to a signal wave of each frame according to the voltage value corresponding to the echo signal and the voltage value corresponding to the spatial noise;
a comparing module 803, configured to calculate a state value corresponding to each frame according to the state decision weight and the voltage value corresponding to the echo signal, compare the state value corresponding to each frame with a standard value of a preset human body state, and determine a human body state corresponding to each frame according to a comparison result;
the determining module 804 is configured to detect a human activity state according to human states corresponding to consecutive frames within a preset time and a pre-configured decision rule.
In some embodiments, the gain module 805 of fig. 8 performs a signal amplification operation on the received echo signal by using a microwave amplifier after acquiring the echo signal generated in the preset continuous frame, and performs a noise filtering operation on the signal-amplified echo signal by using a microwave filter, and takes the noise-filtered echo signal as an analysis object.
In some embodiments, the echo signals include echo signals respectively received by multiple groups of microwave antennas, the analysis module 802 in fig. 8 receives echo signals of multiple spatial reflections by each group of microwave antennas in each frame, and determines a voltage value corresponding to each echo signal according to peak information corresponding to the echo signal of each microwave reflection; generating a voltage value matrix corresponding to each microwave reflection according to the voltage value corresponding to each group of microwave antennas, and performing normalization processing on the voltage value matrix to obtain an average voltage value corresponding to each microwave reflection of a plurality of groups of microwave antennas; wherein the microwaves emitted by each group of microwave antennas have different wavelengths and frequencies.
In some embodiments, the parsing module 802 of fig. 8 extracts spatial noise from the echo signals of multiple spatial reflections received by multiple groups of microwave antennas in each frame, and determines a voltage value corresponding to the spatial noise according to the signal waves corresponding to the echo signals; calculating a state decision weight corresponding to the signal wave of each frame according to an average voltage value corresponding to a plurality of microwave reflections of the microwave antennas in each frame and a voltage value corresponding to the space noise in each frame; the space noise includes multipath noise and gaussian noise generated when the microwave is ejected in the space.
In some embodiments, the following formula is used to calculate the state decision weight corresponding to the signal wave of each frame:
Figure 757158DEST_PATH_IMAGE008
wherein the content of the first and second substances,
Figure 92324DEST_PATH_IMAGE009
indicating the state decision weight corresponding to a certain frame signal wave,
Figure 539355DEST_PATH_IMAGE010
represents the average voltage value corresponding to a plurality of microwave reflections in a certain frame,
Figure 618169DEST_PATH_IMAGE011
indicating the maximum number of microwave reflections within a certain frame,
Figure 116147DEST_PATH_IMAGE012
representing the voltage value corresponding to the spatial noise within a certain frame.
In some embodiments, the comparing module 803 of fig. 8 determines the maximum average voltage value according to the average voltage values corresponding to multiple microwave reflections within each frame, and takes the product of the state decision weight corresponding to the signal wave of each frame and the maximum average voltage value of the same frame as the state value of the frame.
In some embodiments, the comparing module 803 of fig. 8 sequentially compares the state value corresponding to each frame with the standard value of the preset human body state, and takes the preset human body state corresponding to the standard value meeting the preset requirement in the comparison result as the human body state corresponding to the frame; the preset requirements comprise that the difference value between the state value and the standard value is within a certain threshold range, and the preset human body state comprises a body movement state, a thoracic cavity activity state and a heart rhythm activity state.
In some embodiments, the comparing module 803 of fig. 8, after determining the human body state corresponding to each frame according to the comparison result, respectively encode the human body state corresponding to each frame, and store the human body state codes corresponding to consecutive frames within a preset time, where the encoding of the human body state includes representing the human body state in the form of a digital square wave.
In some embodiments, the determining module 804 in fig. 8 draws the digital square waves in the human body states corresponding to the consecutive frames on the same time axis according to the stored digital square waves in the human body states corresponding to the consecutive frames within the preset time, and detects the digital square waves in the human body states corresponding to the consecutive frames on the time axis according to a pre-configured decision rule to obtain a detection result of the human body activity state; the pre-configured decision rule is used for detecting the human body activity state continuously represented by the digital square waves on the time axis according to the digital square waves corresponding to the continuous frames.
In some embodiments, the pre-configured decision rule comprises: when the number of the digital square waves used for representing the body motion state in the digital square waves corresponding to the continuous frames is larger than a preset threshold value, judging that the human body activity state in a preset time is a first activity state; when the number of the digital square waves used for representing the thoracic cavity activity state or the heart rhythm activity in the digital square waves corresponding to the continuous frames is smaller than a preset threshold value, judging that the human body activity state in a preset time is a second activity state; and when the digital square waves used for representing the body motion state, the thoracic cavity activity state and the heart rhythm activity in the digital square waves corresponding to the continuous frames are irregularly arranged, judging that the human body activity state in the preset time is a third activity state.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present disclosure.
Fig. 9 is a schematic structural diagram of an electronic device 9 provided in the embodiment of the present disclosure. As shown in fig. 9, the electronic apparatus 9 of this embodiment includes: a processor 901, a memory 902 and a computer program 903 stored in the memory 902 and operable on the processor 901. The steps in the various method embodiments described above are implemented when the processor 901 executes the computer program 903. Alternatively, the processor 901 implements the functions of each module/unit in each apparatus embodiment described above when executing the computer program 903.
Illustratively, the computer program 903 may be divided into one or more modules/units, which are stored in the memory 902 and executed by the processor 901 to complete the present disclosure. One or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution of the computer program 903 in the electronic device 9.
The electronic device 9 may be a desktop computer, a notebook, a palm computer, a cloud server, or other electronic devices. The electronic device 9 may include, but is not limited to, a processor 901 and a memory 902. Those skilled in the art will appreciate that fig. 9 is merely an example of the electronic device 9, and does not constitute a limitation of the electronic device 9, and may include more or less components than those shown, or combine certain components, or different components, for example, the electronic device may also include input-output devices, network access devices, buses, etc.
The Processor 901 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 902 may be an internal storage unit of the electronic device 9, for example, a hard disk or a memory of the electronic device 9. The memory 902 may also be an external storage device of the electronic device 9, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) and the like provided on the electronic device 9. Further, the memory 902 may also include both an internal storage unit of the electronic device 9 and an external storage device. The memory 902 is used for storing computer programs and other programs and data required by the electronic device. The memory 902 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules, so as to perform all or part of the functions described above. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.
In the embodiments provided in the present disclosure, it should be understood that the disclosed apparatus/computer device and method may be implemented in other ways. For example, the above-described apparatus/computer device embodiments are merely illustrative, and for example, a division of modules or units, a division of logical functions only, an additional division may be made in actual implementation, multiple units or components may be combined or integrated with another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present disclosure may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, the present disclosure may implement all or part of the flow of the method in the above embodiments, and may also be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of the above methods and embodiments. The computer program may comprise computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain suitable additions or additions that may be required in accordance with legislative and patent practices within the jurisdiction, for example, in some jurisdictions, computer readable media may not include electrical carrier signals or telecommunications signals in accordance with legislative and patent practices.
The above examples are only intended to illustrate the technical solutions of the present disclosure, not to limit them; although the present disclosure has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present disclosure, and are intended to be included within the scope of the present disclosure.

Claims (13)

1. A human activity state detection method is characterized by comprising the following steps:
acquiring echo signals generated in a preset continuous frame, wherein the echo signals are signal waves reflected back after microwave is emitted into a preset space by using a microwave antenna, and the continuous frame represents a plurality of continuous time intervals;
analyzing a plurality of echo signals generated in each frame to obtain a voltage value corresponding to each echo signal, and determining a state decision weight corresponding to a signal wave of each frame according to the voltage value corresponding to the echo signal and the voltage value corresponding to the spatial noise;
calculating to obtain a state value corresponding to each frame according to the state decision weight and a voltage value corresponding to the echo signal, comparing the state value corresponding to each frame with a standard value of a preset human body state, and determining the human body state corresponding to each frame according to a comparison result;
and detecting the activity state of the human body according to the human body state corresponding to the continuous frames within the preset time and a preset decision rule.
2. The method of claim 1, wherein after said acquiring echo signals generated within a predetermined succession of frames, the method further comprises:
and performing a signal amplification operation on the received echo signal by using a microwave amplifier, and performing a noise filtering operation on the echo signal after signal amplification by using a microwave filter, wherein the echo signal after noise filtering is taken as an analysis object.
3. The method of claim 1, wherein the echo signals comprise echo signals respectively received by a plurality of sets of microwave antennas; the analyzing the plurality of echo signals generated in each frame to obtain a voltage value corresponding to each echo signal includes:
each group of microwave antennas receives echo signals reflected by multiple times of space in each frame, and the voltage value corresponding to each echo signal is determined according to the peak information corresponding to the echo signal reflected by each microwave;
generating a voltage value matrix corresponding to each microwave reflection according to the voltage value corresponding to each group of microwave antennas, and performing normalization processing on the voltage value matrix to obtain an average voltage value corresponding to each microwave reflection of the multiple groups of microwave antennas;
wherein the microwaves emitted by each set of microwave antennas have different wavelengths and frequencies.
4. The method according to claim 3, wherein the determining the state decision weight corresponding to the signal wave of each frame according to the voltage value corresponding to the echo signal and the voltage value corresponding to the spatial noise comprises:
extracting spatial noise from echo signals of multiple spatial reflections received by the multiple groups of microwave antennas in each frame, and determining a voltage value corresponding to the spatial noise according to signal waves corresponding to the echo signals;
calculating a state decision weight corresponding to the signal wave of each frame according to an average voltage value corresponding to the multiple microwave reflections of the multiple groups of microwave antennas in each frame and a voltage value corresponding to the space noise in each frame;
the space noise comprises multipath noise and Gaussian noise generated when microwaves are ejected in the space.
5. The method according to claim 4, wherein the state decision weight corresponding to the signal wave of each frame is calculated by using the following formula:
Figure 378567DEST_PATH_IMAGE001
wherein the content of the first and second substances,
Figure 764549DEST_PATH_IMAGE002
indicating the state decision weight corresponding to a certain frame signal wave,
Figure 544286DEST_PATH_IMAGE003
represents the average voltage value corresponding to a plurality of microwave reflections in a certain frame,
Figure 408337DEST_PATH_IMAGE004
indicating the maximum number of microwave reflections within a certain frame,
Figure 222709DEST_PATH_IMAGE005
representing the voltage value corresponding to the spatial noise within a certain frame.
6. The method according to claim 4, wherein the calculating the state value corresponding to each frame according to the state decision weight and the voltage value corresponding to the echo signal comprises:
and determining the maximum average voltage value according to the average voltage value corresponding to the microwave reflection in each frame, and taking the product of the state decision weight corresponding to the signal wave of each frame and the maximum average voltage value of the same frame as the state value of the frame.
7. The method according to claim 1, wherein the comparing the state value corresponding to each frame with a standard value of a preset human body state and determining the human body state corresponding to each frame according to the comparison result comprises:
sequentially comparing the state value corresponding to each frame with a standard value of a preset human body state, and taking the preset human body state corresponding to the standard value meeting preset requirements in the comparison result as the human body state corresponding to the frame;
the preset requirement comprises that the difference value between the state value and the standard value is within a certain threshold range, and the preset human body state comprises a body movement state, a thoracic cavity activity state and a heart rhythm activity state.
8. The method according to claim 1, wherein after the determining the corresponding human body state of each frame according to the comparison result, the method further comprises:
and respectively coding the human body state corresponding to each frame, and storing the codes of the human body states corresponding to the continuous frames within the preset time, wherein the coding of the human body states comprises representing the human body states in a digital square wave form.
9. The method according to claim 8, wherein the detecting the human activity state according to the human state corresponding to the continuous frames within the preset time and a pre-configured decision rule comprises:
drawing the digital square waves of the human body state corresponding to the continuous frames on the same time axis according to the stored digital square waves of the human body state corresponding to the continuous frames within the preset time, and detecting the digital square waves corresponding to the continuous frames on the time axis according to the preset decision rule to obtain a detection result of the human body activity state;
and the pre-configured decision rule is used for detecting the human activity state continuously represented by the digital square waves on the time axis according to the digital square waves corresponding to the continuous frames.
10. The method of claim 9, wherein the preconfigured decision rule comprises:
when the number of the digital square waves used for representing the body motion state in the digital square waves corresponding to the continuous frames is larger than a preset threshold value, judging that the human body activity state in the preset time is a first activity state;
when the number of the digital square waves used for representing the thoracic cavity activity state or the heart rhythm activity in the digital square waves corresponding to the continuous frames is smaller than a preset threshold value, judging that the human body activity state in the preset time is a second activity state;
and when the digital square waves used for representing the body motion state, the thoracic cavity activity state and the heart rhythm activity in the digital square waves corresponding to the continuous frames are irregularly arranged, judging that the human body activity state in the preset time is a third activity state.
11. A human activity state detection device, comprising:
the device comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is configured to acquire echo signals generated in preset continuous frames, the echo signals are signal waves reflected back after microwave waves are emitted into a preset space by using a microwave antenna, and the continuous frames represent a plurality of continuous time intervals;
the analysis module is configured to analyze the echo signals generated in each frame to obtain a voltage value corresponding to each echo signal, and determine a state decision weight corresponding to a signal wave of each frame according to the voltage value corresponding to the echo signal and a voltage value corresponding to spatial noise;
the comparison module is configured to calculate a state value corresponding to each frame according to the state decision weight and the voltage value corresponding to the echo signal, compare the state value corresponding to each frame with a standard value of a preset human body state, and determine the human body state corresponding to each frame according to a comparison result;
and the judging module is configured to detect the activity state of the human body according to the human body state corresponding to the continuous frames within the preset time and a preset decision rule.
12. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the method of any one of claims 1 to 10 when executing the program.
13. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 10.
CN202111207305.6A 2021-10-18 2021-10-18 Human body activity state detection method, device, equipment and storage medium Active CN113633271B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202111207305.6A CN113633271B (en) 2021-10-18 2021-10-18 Human body activity state detection method, device, equipment and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202111207305.6A CN113633271B (en) 2021-10-18 2021-10-18 Human body activity state detection method, device, equipment and storage medium

Publications (2)

Publication Number Publication Date
CN113633271A CN113633271A (en) 2021-11-12
CN113633271B true CN113633271B (en) 2021-12-31

Family

ID=78427263

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202111207305.6A Active CN113633271B (en) 2021-10-18 2021-10-18 Human body activity state detection method, device, equipment and storage medium

Country Status (1)

Country Link
CN (1) CN113633271B (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114287922A (en) * 2021-12-28 2022-04-08 上海卓菡科技有限公司 Method, device and equipment for detecting human body out-of-bed state and storage medium

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102988051B (en) * 2012-12-13 2014-07-02 中国人民解放军第四军医大学 Device for monitoring health of computer operator
JP2016521363A (en) * 2013-04-18 2016-07-21 カリフォルニア インスティチュート オブ テクノロジー Life detection radar
CN106821347B (en) * 2016-12-20 2020-05-05 中国人民解放军第三军医大学 FMCW broadband life detection radar respiration and heartbeat signal extraction algorithm
CN111938613B (en) * 2020-08-07 2023-10-31 南京茂森电子技术有限公司 Health monitoring device and method based on millimeter wave radar
CN112220464A (en) * 2020-10-27 2021-01-15 广西脉吾科技有限责任公司 Human body respiration and heartbeat signal detection method and system based on UWB radar
CN112168153B (en) * 2020-11-04 2023-05-30 珠海市海米软件技术有限公司 Contactless respiratory or heartbeat detection system

Also Published As

Publication number Publication date
CN113633271A (en) 2021-11-12

Similar Documents

Publication Publication Date Title
Duan et al. Non-contact detection of vital signs using a UWB radar sensor
US10992774B2 (en) Device-free activity identification using fine grained WiFi signatures
Kim et al. ECG signal compression and classification algorithm with quad level vector for ECG holter system
CN112998701A (en) Vital sign detection and identity recognition system and method based on millimeter wave radar
CN111142102B (en) Respiratory data calculation method and related equipment
CN109363647B (en) Sleep quality monitoring method and device and terminal equipment
CN106691423B (en) The wearable device and signal processing method of health of heart are assessed by heartbeat signal
CN103750820A (en) Method and device for monitoring sleep quality
Zhang et al. Can we obtain fine-grained heartbeat waveform via contact-free rf-sensing?
CN113633271B (en) Human body activity state detection method, device, equipment and storage medium
KR20140060737A (en) Device of transmitting a bio signal, device of receiving the bio signal, and method thereof
Nejadgholi et al. Classification of Doppler radar reflections as preprocessing for breathing rate monitoring
CN114305355B (en) Breathing heartbeat detection method, system and device based on millimeter wave radar
Al-Hamadi et al. An automatic ECG generator for testing and evaluating ECG sensor algorithms
Wang et al. HeRe: Heartbeat signal reconstruction for low-power millimeter-wave radar based on deep learning
Sutar et al. Intelligent electrocardiogram pattern classification and recognition using low‐cost cardio‐care system
Sharma Extraction of respiratory rate from PPG using ensemble empirical mode decomposition with Kalman filter
JP6706996B2 (en) Biological signal processing device, abnormality determination method and program
CN113288078B (en) Sleep quality monitoring method, device and system
CN108549387A (en) A kind of intelligent carriage control system and control method based on brain wave detection
CN114287922A (en) Method, device and equipment for detecting human body out-of-bed state and storage medium
CN114159024A (en) Sleep staging method and device
AlMusallam et al. Design of embedded atrial fibrillation detection scheme for wireless body area networks
CN114098645B (en) Sleep staging method and device
Hansen et al. Fusion learning on multiple-tag RFID measurements for respiratory rate monitoring

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
TR01 Transfer of patent right

Effective date of registration: 20220725

Address after: 5305, floor 5, building 6, No. 8, Beiyuan street, Chaoyang District, Beijing 100020

Patentee after: Beijing Longzhi Digital Technology Service Co.,Ltd.

Address before: 101100-090, floor 1, building 1, No. 2, Jufu North Road, Jufuyuan national industry development base, Tongzhou District, Beijing

Patentee before: Beijing zhuojianzhihan Technology Co.,Ltd.

Patentee before: Shanghai zhuohan Technology Co.,Ltd.

TR01 Transfer of patent right