CN114287922A - Method, device and equipment for detecting human body out-of-bed state and storage medium - Google Patents
Method, device and equipment for detecting human body out-of-bed state and storage medium Download PDFInfo
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Abstract
The disclosure provides a method, a device, equipment and a storage medium for detecting a human body out-of-bed state. The method comprises the following steps: transmitting electromagnetic waves to a preset direction by using an antenna array consisting of a plurality of electromagnetic wave antennas, and acquiring sine wave signals generated in a continuous time period; generating a digital signal matrix in each time period according to the sine wave signals, and judging the human body state by using the digital signal matrix; processing the digital signal matrix in each time period to obtain a matrix graph corresponding to each time period, and determining the dynamic matrix graph change corresponding to the continuous time period in the preset time according to the matrix graph; and determining the human body state change within the preset time according to the dynamic matrix graph change, and detecting the human body out-of-bed state according to the human body state change and a preset decision rule. The method and the device can realize non-sensing detection of the state that the human body leaves the bed, improve user experience and improve accuracy of detection results.
Description
Technical Field
The present disclosure relates to the field of electromagnetic wave detection technologies, and in particular, to a method, an apparatus, a device, and a storage medium for detecting a human body leaving from a bed.
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 certain frequency, the radio frequency waves generate reflected waves after contacting with a human body, so that the position change of the human body is sensed, different states of the human body can be judged based on the change of the position of the human body, and therefore non-sensing detection of the activity state of the human body is achieved, such as detection of the state of the human body leaving a bed and the like.
In the prior art, when detecting the state of a human body leaving a bed, the detection is usually realized by adopting a fiber leaving bed detection belt or a pressure-sensitive mattress. The technical principle of the optical fiber bed-leaving detection belt is that the state of a person on a bed is judged in a mode that the human body deforms the detection belt; the pressure-sensitive mattress adopts the technical principle that the state of a person on a bed is judged in a mode of detecting the pressure of the human body on the mattress through a pressure sensor. However, both of the two modes can be realized only by directly contacting with the human body, physical contact between the human body and the detection equipment can cause discomfort to the human body and reduce user experience, and the mode of realizing detection by contacting with the human body can reduce the accuracy of a detection result.
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 body out-of-bed state, so as to solve the problems of poor user experience and low accuracy of detection results in the prior art.
In a first aspect of the embodiments of the present disclosure, a method for detecting a human body out-of-bed state is provided, including: transmitting electromagnetic waves to a preset direction by using an antenna array consisting of a plurality of electromagnetic wave antennas, and acquiring sine wave signals generated in a continuous time period; generating a digital signal matrix in each time period according to the sine wave signals, and judging the human body state by using the digital signal matrix, wherein the digital signal matrix comprises matrix variables of voltage values corresponding to the sine wave signals; processing the digital signal matrix in each time period to obtain a matrix graph corresponding to each time period, and determining the dynamic matrix graph change corresponding to the continuous time period in the preset time according to the matrix graph; and determining the human body state change within the preset time according to the dynamic matrix graph change, and detecting the human body out-of-bed state according to the human body state change and a preset decision rule.
In a second aspect of the embodiments of the present disclosure, there is provided a human body out-of-bed state detection apparatus, including: the acquisition module is configured to transmit electromagnetic waves to a preset direction by using an antenna array consisting of a plurality of electromagnetic wave antennas and acquire sine wave signals generated in continuous time periods; the judging module is configured to generate a digital signal matrix in each time period according to the sine wave signals, and judge the state of the human body by using the digital signal matrix, wherein the digital signal matrix comprises matrix variables of voltage values corresponding to the sine wave signals; the processing module is configured to process the digital signal matrix in each time period to obtain a matrix graph corresponding to each time period, and determine dynamic matrix graph changes corresponding to continuous time periods in preset time according to the matrix graph; the detection module is configured to determine the human body state change within a preset time according to the dynamic matrix graph change, and detect the human body out-of-bed state according to the human body state change 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:
transmitting electromagnetic waves to a preset direction by using an antenna array consisting of a plurality of electromagnetic wave antennas, and acquiring sine wave signals generated in a continuous time period; generating a digital signal matrix in each time period according to the sine wave signals, and judging the human body state by using the digital signal matrix, wherein the digital signal matrix comprises matrix variables of voltage values corresponding to the sine wave signals; processing the digital signal matrix in each time period to obtain a matrix graph corresponding to each time period, and determining the dynamic matrix graph change corresponding to the continuous time period in the preset time according to the matrix graph; and determining the human body state change within the preset time according to the dynamic matrix graph change, and detecting the human body out-of-bed state according to the human body state change and a preset decision rule. This is disclosed realizes not knowing the detection to the human body through the microwave radar, according to the analysis to the sinusoidal wave signal, judges the state change of human body on the bed to realize the human detection of leaving the bed state, not only promoted user experience, promoted the accuracy of testing result moreover.
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 method for detecting a human body out-of-bed state according to an embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of a human body out-of-bed state detection device provided in the embodiment of the present disclosure;
fig. 4 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 transmits microwaves with certain frequency to the space, the transmitted microwaves directly irradiate a human body, the microwave signals can be changed due to different actions of the human body, and the information of the position change of the human body can be obtained by demodulating the phases of the microwave signals reflected by the radar, so that the non-contact detection of the activity state of the human body is realized. The detection of the human body activity state based on the microwave radar has wide application in the fields of health care, intelligent home and the like. The following description will be made of the principle and the existing problems of the existing method for detecting the human body getting out of bed, taking the clinical medical field as an example, and specifically includes the following contents:
in clinical medicine, for some patients, medical staff need to know the state of the patient in bed or determine whether the patient is in bed. Therefore, real-time detection data are needed for the state of the patient on the bed, the state of the patient on the bed or the like is judged according to the detection data, an alarm is given in time, and the detection on the state of the human body on the bed is significant.
At the present stage, the judgment of the bed-leaving state of a patient or the old mainly adopts the following two modes, the first mode is to adopt an optical fiber bed-leaving detection belt to detect the state of a human body, namely, the detection belt is installed on a bed, and the state of the human body on the bed is judged according to the mode that the human body deforms the detection belt; the second method is to detect the state of the human body by using a pressure-sensitive mattress, that is, the pressure generated by the human body on the pressure-sensitive mattress is detected by a pressure sensor, and the state of the human body on the bed is judged according to the change of the pressure.
However, whether the optical fiber bed-exit detection belt or the pressure-sensitive mattress is used, the detection method depends on not only complicated electrical equipment, but also the user needs to access the equipment on the body or wear wearable equipment. Therefore, the existing human body bed-leaving detection method based on the optical fiber bed-leaving detection belt or the pressure-sensitive mattress can realize detection only by directly contacting equipment with a human body and needs physical contact between the human body and the detection equipment, which not only can cause discomfort for a user, but also can influence a detection result and make the detection result of the human body bed-leaving state inaccurate by directly contacting the human body with the bed body as the human body is needed and the detection equipment is in contact with a barrier.
In view of the above problems in the prior art, it is desirable to provide a method for detecting a person getting out of bed based on electromagnetic waves, which can detect the state of the person in bed by analyzing the reflected signal of a microwave antenna by utilizing the penetrability and non-contact property of a microwave radar, so as to distinguish and judge the state of the person getting out of bed. Therefore, under the condition of contacting the human body, the non-sensing detection of the human body state is realized, and the human body state sensing device has secrecy and desensitization. Because need not with user's health direct contact, consequently avoid causing uncomfortable sense to the user, promote user's experience, guarantee the accuracy of testing result.
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 an antenna array unit, a signal acquisition 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 array unit can be composed of a plurality of groups of microwave antennas, the microwave antennas integrate power transmission and reception, and space scanning is realized by transmitting microwave signals into space and reflecting and scattering the microwave signals; because the energy of the returned echo signal may not satisfy the analysis condition, the signal acquisition unit is required to perform signal amplification and noise filtering processing on the echo signal received by the antenna unit, the signal acquisition unit may include a microwave amplifier and a microwave filter, and the signal analysis unit is used to perform digital processing on the linear wave pattern of the microwave signal processed by the signal acquisition unit and generate a decision signal.
Furthermore, the antenna array unit is composed of a plurality of electromagnetic wave antennas and is also a transmitting-receiving body; transmitting electromagnetic waves through a plurality of antennas and receiving reflected signals to form level information, and sending the received information to a signal acquisition unit; performing signal amplification gain on the received level signal through a signal acquisition unit, and performing first filtering operation, wherein the filtering operation refers to the elimination of multipath noise or Gaussian noise and the like generated during space ejection; the filtering can suppress the received noise and the noise and transmit the information to the signal analysis unit; the signal analysis unit is used for independently analyzing the multi-antenna information to form a digital signal array with a matrix structure and sending the analyzed array information to the core processing unit.
Furthermore, 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 the core processing unit; analyzing the decision signal by using a core processing unit, judging the decision signal continuously generated within a preset time by using a preset decision rule so as to determine the human activity state of the detected object within the time, performing data coding on the judgment result and sending out information through a communication unit; the core processing unit temporarily stores the information and collects the data, and performs data interpretation after waiting for a certain accumulation time of the data, wherein the interpretation is obtained by comparison of an expert system; and finally, outputting a system decision.
It should be noted that, in practical applications, in order to more accurately receive the echo signal and avoid interference of excessive noise on the determination result, the apparatus (for example, the apparatus is integrated into a radar apparatus having the above function) composed of the radar module and the processing module may be placed near the object to be detected, for example, the microwave radars may be arranged at the bottom of the bed or at the periphery of the bed in an array manner. The following embodiments of the present disclosure are described by taking the detection of the human activity state of the measured object on the bed as an example, however, the embodiments of the present disclosure are not limited to the detection of the human activity state on the bed, and the present solution is also applicable to the detection of the human activity state in other application scenarios, for example, the detection of the human activity state in an indoor scenario, and the application scenario of the embodiments of the present disclosure does not constitute a limitation to the present technical solution.
Fig. 2 is a schematic flow chart of a method for detecting a human body out-of-bed state according to an embodiment of the present disclosure. The human body out-of-bed state detection method of fig. 2 may be performed by a microwave radar alone or the microwave radar and a server together. As shown in fig. 2, the method for detecting a human body out-of-bed state may specifically include:
s201, transmitting electromagnetic waves to a preset direction by using an antenna array consisting of a plurality of electromagnetic wave antennas, and acquiring sine wave signals generated in a continuous time period;
s202, generating a digital signal matrix in each time period according to the sine wave signals, and judging the state of the human body by using the digital signal matrix, wherein the digital signal matrix comprises matrix variables of voltage values corresponding to the sine wave signals;
s203, processing the digital signal matrix in each time period to obtain a matrix graph corresponding to each time period, and determining the dynamic matrix graph change corresponding to the continuous time period in the preset time according to the matrix graph;
s204, determining the human body state change within the preset time according to the dynamic matrix graph change, and detecting the human body out-of-bed state according to the human body state change and a preset decision rule.
Specifically, the antenna array in the embodiment of the present disclosure may be laid under a mattress or a bed board, and the like, and the accuracy of measurement may be improved for a bed frame composed of a non-metal structure. In practical application, a plurality of electromagnetic wave antennas can be arranged below the bed plate in an array mode, and object identification is carried out by emitting electromagnetic waves. The electromagnetic wave has the penetrating characteristic, so that the electromagnetic wave can penetrate non-liquid or metal objects such as bed boards, mattresses, bedding and the like.
Further, a time period in the embodiment of the present disclosure corresponds to one frame, where the frame is not an image frame in the conventional sense, but a process of transmitting electromagnetic waves to the space by the microwave antenna and receiving echo signals within a certain time interval is referred to as one frame, and therefore, the time interval corresponding to one frame may be customized, for example, the microwave transmitting and recovering process within 0.1s is regarded as one 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 embodiment of the present disclosure analyzes and processes the echo signal (i.e. the sine wave signal) in units of frames, and multiple echo signals may be received within a frame, for example, the time interval of one echo is 0.01s, and the time interval of one frame is 0.1s, so that the microwave antenna receives 10 echo signals within a 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, an antenna array consisting of a plurality of electromagnetic wave antennas is used for transmitting electromagnetic waves to a preset direction, and sinusoidal signals generated in a continuous time period are acquired; generating a digital signal matrix in each time period according to the sine wave signals, and judging the human body state by using the digital signal matrix, wherein the digital signal matrix comprises matrix variables of voltage values corresponding to the sine wave signals; processing the digital signal matrix in each time period to obtain a matrix graph corresponding to each time period, and determining the dynamic matrix graph change corresponding to the continuous time period in the preset time according to the matrix graph; and determining the human body state change within the preset time according to the dynamic matrix graph change, and detecting the human body out-of-bed state according to the human body state change and a preset decision rule. This is disclosed realizes human noninductive detection through microwave radar, according to the analysis to the sinusoidal wave signal, judges the state change of human body on the bed to realize the human detection of leaving the bed state, not only promoted user experience, promoted the accuracy of testing result moreover.
In some embodiments, after acquiring the sinusoidal signals generated for successive time periods, the method further comprises: and amplifying the sinusoidal signals by using a microwave amplifier, performing noise filtering on the sinusoidal signals after signal amplification by using a microwave filter, and analyzing the sinusoidal signals after noise filtering to obtain level information.
Specifically, the echo signals received by the electromagnetic wave antennas are sinusoidal signals, and the sinusoidal signal corresponding to each electromagnetic wave antenna changes with the reception of the signals. Since the energy of the echo signal (i.e., the sine wave 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 using 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 signal amplification by using 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.
Further, the antenna array of the embodiment of the present disclosure may include multiple sets of microwave antennas, each set of microwave antennas individually transmits electromagnetic waves and receives echo signals, 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.
In some embodiments, generating a matrix of digital signals in each time period from the sine wave signals comprises: acquiring sine wave signals received by each electromagnetic wave antenna in a time period, determining a voltage value corresponding to each sine wave signal according to wave crest information corresponding to the sine wave signals, converting the voltage values into matrix variables according to a preset conversion rule, and constructing a digital signal matrix according to the matrix variables corresponding to all the sine wave signals in the time period.
Specifically, 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 occurrence period of each echo signal. The received sinusoidal signals can be converted into information represented by 1 and 0 square waves through analysis, and therefore a digital signal matrix formed by 1 and 0 matrix variables corresponding to each microwave antenna is described in the digital signal matrix.
Furthermore, 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, a waveform corresponding to the frame can be obtained according to the average voltage values generated by all echoes in the frame, and the echo with the peak corresponding to the maximum average voltage value. 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.
Further, the sine wave signals received by the antenna array may be abstracted into the following digital signal matrix:
[A]＝[B]+σ
wherein [ A ] is the sum of the continuous receiving states, [ B ] is the sum of the real-time excited states, and σ is the error value generated by each transmitting and receiving.
In some embodiments, the determining the human body state by using the digital signal matrix comprises: and generating a digital square wave corresponding to the digital signal matrix according to the matrix variable in the digital signal matrix, and judging the human body state corresponding to the digital signal matrix according to a preset mapping relation between the human body state and the digital square wave.
Specifically, when the array antenna changes, the signal matrix also changes, and since the human body is mostly composed of liquid, the signal feedback is strong, the air flight time of local signals is shortened, and the received information is changed. In practical application, a digital square wave corresponding to the digital signal matrix is generated according to the 1 and 0 values corresponding to the matrix variables, the digital square wave can represent codes for human body states, and each preset human body state corresponds to one code, for example, the code corresponding to the bed-lying state is 10, the code corresponding to the bed-sitting state is 11, and the like.
In some embodiments, processing the digital signal matrix in each time period to obtain a matrix pattern corresponding to each time period includes: and aiming at each time period, determining a digital signal matrix generated by receiving the sine wave signal by the antenna array each time in the time period, and performing superposition operation on all digital signal matrixes generated in the time period to obtain a matrix graph corresponding to the time period.
Specifically, according to a digital signal matrix generated by the antenna array receiving the sine wave signal each time in each frame, all digital signal matrices corresponding to each frame are subjected to superposition processing, and a matrix graph corresponding to each frame can be obtained.
In some embodiments, each matrix pattern corresponds to at least one human body state, and determining the change of the human body state within a preset time according to the change of the dynamic matrix pattern includes: acquiring a matrix graph corresponding to each time period in preset time, arranging the matrix graphs according to a time axis, generating dynamic matrix graph change according to the continuously arranged matrix graphs, and determining human body state change in the preset time according to the dynamic matrix graph change; the matrix pattern is used for representing matrix variables by dot signals of different colors.
Specifically, the core processing unit stores different matrix patterns generated along with time within a certain time, the different matrix patterns form a continuous dynamic change along a time axis, and each matrix pattern corresponds to a human body state, so that the change of the dynamic matrix patterns can represent the change condition of the activity state of the human body within the time. The following detailed description of the formula representation of the matrix pattern by using the formula may specifically include the following:
where H is a certain primary matrix variable in a given time T, assuming that the total time length T is 1 second and the frequency of H is 10, that means that 10H matrix variables are obtained within 1 second.
Further, the different matrices are superimposed into a matrix pattern [ A ] that analyzes the number of times the number exists within each matrix. If the image is regarded as a bit image, each pixel point will change in depth according to the number of occurrences within 1 second. And the bit image obtained after 1 second is identified with the image bottom library, and when the bit image meets the image of a certain bottom library, the command is sent according to the mark of the image (such as sitting on a bed).
Further, calculating weights from the matrix pattern may be expressed as:
ω＝[A]·T+ρ
where ω is a weight value, [ A ]. T is the product of the spatial matrix and time, and ρ is an error variable. [A] There is a strong correlation with time and can be expressed as a change in the matrix received by the sensor that is generated within a particular time.
In some embodiments, detecting the human body out-of-bed state according to the human body state change and a pre-configured decision rule includes: matching the dynamic matrix pattern change with a pre-configured decision rule to determine a human body out-of-bed state corresponding to the dynamic matrix pattern change in the pre-configured decision rule to obtain a detection result of the human body out-of-bed state; the pre-configured decision rule comprises human body out-of-bed states corresponding to different dynamic matrix graphic changes.
Specifically, the pre-configured decision rule is used for detecting the bed-leaving state of the human body according to the change of the state of the human body, which is presented by the change of the dynamic matrix pattern corresponding to the continuous frames, different detected objects or the same detected object can present different state changes in different time, and the activity states 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, the out-of-bed state of the human body is judged through continuous human body state changes in a preset time, and the detected object is in the in-bed state and the out-of-bed state respectively in a certain preset time, which indicates that the detected object gets up and leaves the bed.
Further, different signal response matrixes are generated according to different detected states of the human body on the bed, and the current behavior profile of the target person, such as turning over, leaning on, getting up, getting out of bed and the like, can be obtained by making decisions on the current signal response matrixes. By adding the human body states into the time dimension, the activity track of the detected object in the specific time can be obtained, so that the current or specific time period of human body behaviors can be further analyzed, and finally, the functions of sleep quality, ceremony correction, clinical monitoring and the like can be realized.
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. 3 is a schematic structural diagram of a human body out-of-bed state detection device provided in the embodiment of the present disclosure. As shown in fig. 3, the human body out-of-bed state detecting apparatus includes:
an obtaining module 301 configured to transmit an electromagnetic wave to a preset direction by using an antenna array composed of a plurality of electromagnetic wave antennas, and obtain a sinusoidal signal generated in a continuous time period;
the judging module 302 is configured to generate a digital signal matrix in each time period according to the sine wave signal, and judge the human body state by using the digital signal matrix, wherein the digital signal matrix comprises a matrix variable of a voltage value corresponding to the sine wave signal;
the processing module 303 is configured to process the digital signal matrix in each time period to obtain a matrix pattern corresponding to each time period, and determine a dynamic matrix pattern change corresponding to a continuous time period in a preset time according to the matrix pattern;
the detection module 304 is configured to determine a human body state change within a preset time according to the dynamic matrix pattern change, and detect a human body out-of-bed state according to the human body state change and a preset decision rule.
In some embodiments, after acquiring the sinusoidal signals generated in the continuous time period, the acquiring module 301 in fig. 3 utilizes a microwave amplifier to amplify the sinusoidal signals, utilizes a microwave filter to perform noise filtering on the sinusoidal signals after signal amplification, and analyzes the sinusoidal signals after noise filtering to obtain the level information.
In some embodiments, the determining module 302 shown in fig. 3 obtains a sinusoidal signal received by each electromagnetic wave antenna in a time period, determines a voltage value corresponding to each sinusoidal signal according to peak information corresponding to the sinusoidal signal, converts the voltage value into a matrix variable according to a preset conversion rule, and constructs a digital signal matrix according to the matrix variables corresponding to all sinusoidal signals in the time period.
In some embodiments, the determining module 302 in fig. 3 generates a digital square wave corresponding to the digital signal matrix according to a matrix variable in the digital signal matrix, and determines the human body state corresponding to the digital signal matrix according to a preset mapping relationship between the human body state and the digital square wave.
In some embodiments, the processing module 303 of fig. 3 determines, for each time period, a digital signal matrix generated by each time the antenna array receives a sine wave signal in the time period, and performs an overlap operation on all digital signal matrices generated in the time period to obtain a matrix pattern corresponding to the time period.
In some embodiments, each matrix pattern corresponds to at least one human body state, the detection module 304 in fig. 3 obtains the matrix pattern corresponding to each time period within a preset time, arranges the matrix patterns according to a time axis, generates a dynamic matrix pattern change according to the continuously arranged matrix patterns, and determines a human body state change within the preset time according to the dynamic matrix pattern change; the matrix pattern is used for representing matrix variables by dot signals of different colors.
In some embodiments, the detection module 304 in fig. 3 matches the dynamic matrix pattern change with a pre-configured decision rule to determine a human body out-of-bed state corresponding to the dynamic matrix pattern change in the pre-configured decision rule, so as to obtain a detection result of the human body out-of-bed state; the pre-configured decision rule comprises human body out-of-bed states corresponding to different dynamic matrix graphic changes.
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. 4 is a schematic structural diagram of the electronic device 4 provided in the embodiment of the present disclosure. As shown in fig. 4, the electronic apparatus 4 of this embodiment includes: a processor 401, a memory 402 and a computer program 403 stored in the memory 402 and executable on the processor 401. The steps in the various method embodiments described above are implemented when the processor 401 executes the computer program 403. Alternatively, the processor 401 implements the functions of the respective modules/units in the above-described respective apparatus embodiments when executing the computer program 403.
Illustratively, the computer program 403 may be partitioned into one or more modules/units, which are stored in the memory 402 and executed by the processor 401 to accomplish 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 403 in the electronic device 4.
The electronic device 4 may be a desktop computer, a notebook, a palm computer, a cloud server, or other electronic devices. The electronic device 4 may include, but is not limited to, a processor 401 and a memory 402. Those skilled in the art will appreciate that fig. 4 is merely an example of the electronic device 4, and does not constitute a limitation of the electronic device 4, and may include more or less components than those shown, or combine certain components, or different components, e.g., the electronic device may also include input-output devices, network access devices, buses, etc.
The Processor 401 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 402 may be an internal storage unit of the electronic device 4, for example, a hard disk or a memory of the electronic device 4. The memory 402 may also be an external storage device of the electronic device 4, 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 4. Further, the memory 402 may also include both internal storage units of the electronic device 4 and external storage devices. The memory 402 is used for storing computer programs and other programs and data required by the electronic device. The memory 402 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 (10)
1. A method for detecting a human body out-of-bed state is characterized by comprising the following steps:
transmitting electromagnetic waves to a preset direction by using an antenna array consisting of a plurality of electromagnetic wave antennas, and acquiring sine wave signals generated in a continuous time period;
generating a digital signal matrix in each time period according to the sine wave signals, and judging the state of the human body by using the digital signal matrix, wherein the digital signal matrix comprises matrix variables of voltage values corresponding to the sine wave signals;
processing the digital signal matrix in each time period to obtain a matrix graph corresponding to each time period, and determining the change of a dynamic matrix graph corresponding to a continuous time period in preset time according to the matrix graph;
and determining the human body state change within the preset time according to the dynamic matrix graph change, and detecting the human body out-of-bed state according to the human body state change and a preset decision rule.
2. The method of claim 1, wherein after said acquiring the sinusoidal signals generated for successive time periods, the method further comprises:
and performing signal amplification on the sinusoidal signals by using a microwave amplifier, performing noise filtering on the sinusoidal signals after signal amplification by using a microwave filter, and analyzing the sinusoidal signals after noise filtering to obtain level information.
3. The method of claim 1, wherein said generating a matrix of digital signals for each of said time periods from said sinusoidal signals comprises:
acquiring sine wave signals received by each electromagnetic wave antenna in the time period, determining a voltage value corresponding to each sine wave signal according to wave crest information corresponding to the sine wave signals, converting the voltage values into matrix variables according to a preset conversion rule, and constructing the digital signal matrix according to the matrix variables corresponding to all the sine wave signals in the time period.
4. The method of claim 1, wherein the determining the human body state by using the digital signal matrix comprises:
and generating a digital square wave corresponding to the digital signal matrix according to the matrix variable in the digital signal matrix, and judging the human body state corresponding to the digital signal matrix according to a preset mapping relation between the human body state and the digital square wave.
5. The method of claim 1, wherein the processing the digital signal matrix in each of the time periods to obtain a matrix pattern corresponding to each of the time periods comprises:
and aiming at each time period, determining a digital signal matrix generated by receiving the sine wave signal by the antenna array each time in the time period, and performing superposition operation on all digital signal matrices generated in the time period to obtain a matrix graph corresponding to the time period.
6. The method according to claim 1, wherein each matrix pattern corresponds to at least one human body state, and the determining the human body state change within the preset time according to the dynamic matrix pattern change comprises:
acquiring a matrix graph corresponding to each time period within the preset time, arranging the matrix graphs according to a time axis, generating the dynamic matrix graph change according to the continuously arranged matrix graphs, and determining the human body state change within the preset time according to the dynamic matrix graph change;
the matrix pattern comprises a matrix pattern, and the matrix pattern is used for representing the matrix variable by dot signals of different colors.
7. The method according to claim 1, wherein the detecting the human body out-of-bed state according to the human body state change and a pre-configured decision rule comprises:
matching the dynamic matrix pattern change with the pre-configured decision rule to determine a human body out-of-bed state corresponding to the dynamic matrix pattern change in the pre-configured decision rule, and obtaining a detection result of the human body out-of-bed state;
wherein, the pre-configured decision rule comprises human body out-of-bed states corresponding to different dynamic matrix graphic changes.
8. A human body out-of-bed state detection device is characterized by comprising:
the acquisition module is configured to transmit electromagnetic waves to a preset direction by using an antenna array consisting of a plurality of electromagnetic wave antennas and acquire sine wave signals generated in continuous time periods;
the judging module is configured to generate a digital signal matrix in each time period according to the sine wave signals, and judge the human body state by using the digital signal matrix, wherein the digital signal matrix comprises matrix variables of voltage values corresponding to the sine wave signals;
the processing module is configured to process the digital signal matrix in each time period to obtain a matrix graph corresponding to each time period, and determine dynamic matrix graph changes corresponding to continuous time periods in preset time according to the matrix graphs;
the detection module is configured to determine the human body state change within the preset time according to the dynamic matrix graph change, and detect the human body out-of-bed state according to the human body state change and a preset decision rule.
9. 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 7 when executing the program.
10. 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 7.
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| JP2001238922A (en) * | 2000-02-29 | 2001-09-04 | Omron Corp | Human body detector and bed provided with the same |
| JP2011130830A (en) * | 2009-12-22 | 2011-07-07 | Kyushu Hitachi Maxell Ltd | Leaving-bed detection system |
| CN113633271A (en) * | 2021-10-18 | 2021-11-12 | 北京卓建智菡科技有限公司 | Human health state detection method, device, equipment and storage medium |
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2021
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| Publication number | Priority date | Publication date | Assignee | Title |
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| JP2001238922A (en) * | 2000-02-29 | 2001-09-04 | Omron Corp | Human body detector and bed provided with the same |
| JP2011130830A (en) * | 2009-12-22 | 2011-07-07 | Kyushu Hitachi Maxell Ltd | Leaving-bed detection system |
| CN113633271A (en) * | 2021-10-18 | 2021-11-12 | 北京卓建智菡科技有限公司 | Human health state detection method, device, equipment and storage medium |
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