CN114366052A - Intelligent nursing home monitoring system and method based on millimeter wave radar - Google Patents
Intelligent nursing home monitoring system and method based on millimeter wave radar Download PDFInfo
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Abstract
The invention belongs to the technical field of intelligent monitoring, and provides an intelligent monitoring device of an aged people house based on a millimeter wave radar, wherein a vital sign signal acquisition module is used for sending a radar signal to a target to be detected and receiving a returned echo signal, a signal processing module is used for processing the echo signal to obtain a distance-speed spectrogram and a distance-angle spectrogram, judging whether the target to be detected is a target human body or not based on the distance-speed spectrogram and the distance-angle spectrogram, if so, calculating distance information of the surface fluctuation of the chest cavity of the target human body in unit time according to the echo signal, and extracting vital sign data of the target human body according to a phase difference signal in the distance information; the signal processing module is used for judging whether a set threshold value is exceeded or not according to the target human body vital sign data, if so, sending an early warning signal to the cloud early warning module, and sending a notice or timely warning to a related contact person or a caregiver through the cloud early warning module.
Description
Technical Field
The invention belongs to the technical field of intelligent monitoring, and particularly relates to an intelligent monitoring method and system for an aged care department based on a millimeter wave radar.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
With the progress of China into a deeply aging society, the phenomenon of empty nesters is more serious, nursing and inspection in the management of an aging institution consumes a large amount of labor cost but has unsatisfactory effect, and rejection psychology is easily caused.
For example, in the patent of the invention-CN 112472051A that has been disclosed, the method for performing intelligent monitoring based on the millimeter wave radar in the prior art is to directly extract and process a vital sign signal of a target human body according to a collected radar signal to obtain a corresponding human body index, and does not consider the interference of a stationary object on a moving target, especially false detection points are caused by the movement of the target in an indoor scene, and the false detection points are mistakenly considered by the millimeter wave radar sensor as the target to be tracked and output, which causes a false alarm problem.
Disclosure of Invention
In order to solve at least one technical problem in the background technology, the invention provides an intelligent nursing home monitoring method and system based on a millimeter wave radar, which integrates a millimeter wave radar chip type nursing system for monitoring the old people with smaller volume and higher precision, can realize monitoring and checking the body vital signs and limb activities of the old people without installing monitoring cameras inside and outside the old people room, and sends out an alarm to other relatives or nursing staff when the old people at home happen to be dangerous, so as to guide quick rescue. Meanwhile, the monitoring device can help a caregiver to monitor whether the solitary old man falls down or not at home and the like, and track the old man in the nursing home to ensure safety.
In order to achieve the purpose, the invention adopts the following technical scheme:
the invention provides an intelligent monitoring device for a nursing home based on a millimeter wave radar, which comprises: the system comprises a vital sign signal acquisition module, a signal processing module and a cloud early warning module;
the vital sign signal acquisition module is used for sending a radar signal to a target to be detected and receiving a returned echo signal, the signal processing module is used for processing the echo signal to obtain a distance-speed spectrogram and a distance-angle spectrogram, judging whether the target to be detected is a target human body or not based on the distance-speed spectrogram and the distance-angle spectrogram, if so, calculating distance information of the surface fluctuation of the chest cavity of the target human body in unit time according to the echo signal, and extracting vital sign data of the target human body according to a phase difference signal in the distance information;
the signal processing module is used for judging whether a set threshold value is exceeded or not according to the target human body vital sign data, if so, sending an early warning signal to the cloud early warning module, and sending a notice or timely warning to a related contact person or a caregiver through the cloud early warning module.
The invention provides an intelligent nursing home monitoring method based on a millimeter wave radar, which comprises the following steps:
sending a radar signal to a target to be detected, and receiving a returned echo signal;
processing the echo signals to obtain a distance-velocity spectrogram and a distance-angle spectrogram, judging whether the target to be detected is a target human body or not based on the distance-velocity spectrogram and the distance-angle spectrogram, if so, calculating distance information of the surface fluctuation of the chest cavity of the target human body in unit time according to the echo signals, and extracting vital sign data of the target human body according to phase difference signals in the distance information;
and judging whether the target human body vital sign data exceeds a set threshold value, if so, sending an early warning signal to a cloud early warning module, and sending a notice or timely warning to a related contact or a caregiver through the cloud early warning module.
Compared with the prior art, the invention has the beneficial effects that:
the method comprises the steps of carrying out analog-to-digital conversion on intermediate frequency signals acquired by an FMCW radar, obtaining a distance-speed spectrogram and a distance-angle spectrogram through Fourier transform, and acquiring information such as speed, direction, distance, signal-to-noise ratio and the like of a target according to a target monitoring algorithm and a multi-target tracking method through processed signals. The static object eliminating algorithm is used for eliminating the static object in the indoor environment, and the interference of the static object to the moving target is avoided. False detection points caused by target motion in an indoor scene are eliminated through a multipath interference elimination algorithm, and the problem of false alarm caused by the fact that the false detection points are mistakenly considered by a millimeter wave radar sensor as targets to be tracked and output is avoided.
The method comprises the steps that real-time health monitoring is conducted on elderly patients, when data reach a threshold value set in an intelligent nursing system before, an instant alarm is sent to a nursing person or an associated person, health data of a user object are collected and analyzed through a cloud technology and an AI intelligent algorithm, a health file is established for the elderly with customized service, a health report is sent regularly, a treatment scheme is made or improved in a targeted mode, and health information is fed back in time.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
FIG. 1 is a schematic diagram of the structure of an intelligent monitoring device of a nursing home based on millimeter wave radar according to the present invention;
FIG. 2 is a flow chart illustrating a second embodiment of signal processing according to the present invention;
FIG. 3 is a schematic diagram of a chirp signal embodying the present invention;
FIG. 4 is a schematic diagram of two intermediate frequency signal outputs in accordance with the present invention;
FIG. 5 is a frequency plot of two intermediate frequency signals as a function of time for an implementation of the present invention;
FIG. 6 is a representation of three different RX chirps received for different objects in an implementation two of the present invention;
FIG. 7 is a schematic diagram of millimeter wave radar vital signs monitoring in accordance with a second embodiment of the present invention;
FIGS. 8(a) -8 (b) are graphs showing the results of target tracking and positioning experiments in the second embodiment of the present invention;
FIG. 9 is a 2-dimensional FFT distance-velocity diagram in accordance with a second embodiment of the present invention;
FIGS. 10(a) -10 (d) are graphs showing the results of the window function algorithm in the second embodiment of the present invention;
FIGS. 11(a) to 11(f) are graphs showing the results of the test person 1 who keeps breathing normally in the second embodiment of the present invention;
FIGS. 12(a) to 12(f) are graphs showing the results of the test person 2 who keeps breathing normally in the second embodiment of the present invention;
fig. 13(a) to 13(f) are graphs showing the results of the test performed by the test person 3 holding his breath in the second embodiment of the present invention.
Detailed Description
The invention is further described with reference to the following figures and examples.
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
Interpretation of terms:
millimeter wave: millimeter waves are a special radar technology using short-wavelength electromagnetic waves, electromagnetic wave signals emitted by a radar system are blocked by objects on the emission path of the radar system and then reflected, and the radar system can determine the distance, speed and angle of the objects by capturing the reflected signals.
FMCW: frequency Modulated Continuous Wave (fm cw) radar continuously transmits fm signals to measure range, as well as angle and velocity. This is different from conventional pulse radar systems that periodically transmit short pulses. In a radar system, the basic concept refers to the reflection of an electromagnetic signal during its transmission, which is blocked by an object in its transmission path. The frequency of the signals used by FMCW radar systems increases linearly with time, a type of signal also known as a chirp.
Single chirp: i.e. a single chirp, one signal transmitted by the FMCW radar is called chirp, one chirp being a sinusoid whose frequency increases linearly with time.
Example one
The complete millimeter wave radar system comprises analog components such as a Transmitting (TX), a Receiving (RX), a Radio Frequency (RF) component and a clock, and digital components such as an analog-to-digital converter (ADC), a Microcontroller (MCU) and a Digital Signal Processor (DSP).
As shown in fig. 1, the present embodiment provides an intelligent monitoring device for nursing home based on millimeter wave radar, which includes: the system comprises a vital sign signal acquisition module, a signal processing module and a cloud early warning module;
the vital sign signal acquisition module comprises a signal generator and a millimeter wave radar transceiver unit; the signal generator is used for generating a chirp radar signal; the millimeter wave radar transceiver unit is used for transmitting a generated linear frequency modulation pulse radar signal through a transmitting antenna, obtaining a reflected echo after the linear frequency modulation pulse radar signal passes through a target to be detected, and receiving the transmitted echo signal through a receiving antenna;
the signal processing module is used for processing the echo signals to obtain a distance-speed spectrogram and a distance-angle spectrogram, judging whether the target to be detected is a target human body or not based on the distance-speed spectrogram and the distance-angle spectrogram, if so, calculating distance information of the surface fluctuation of the chest cavity of the target human body in unit time according to the echo signals, and extracting vital sign data of the target human body according to phase difference signals in the distance information;
the signal processing module is used for performing analog-to-digital conversion on the echo signals, obtaining a distance-speed spectrogram and a distance-angle spectrogram through Fourier change, acting on the distance-speed spectrogram by adopting a CFAR (computational fluid dynamics) algorithm and combining the distance-angle spectrogram to obtain point cloud data, performing condensation processing on the point cloud data by adopting a density clustering algorithm, condensing detected points into clusters, and taking each cluster as a human body target; when a human body target moves, a corresponding cluster is necessary to move, and the position and the speed of a human body can be obtained according to the position and the speed of the cluster.
According to a target monitoring algorithm and a multi-target tracking algorithm, information such as speed, direction, distance, signal to noise ratio and the like of a target is obtained, and a static object elimination algorithm is used for eliminating a static object in an indoor environment, so that the interference of the static object to a moving target is avoided.
False detection points caused by target motion in an indoor scene are eliminated through a multipath interference elimination algorithm, and the problem of false alarm caused by the fact that the false detection points are mistakenly considered by a millimeter wave radar sensor as targets to be tracked and output is avoided.
The cloud early warning module is connected with the signal processing module, the cloud early warning module is used for receiving vital sign data such as heart rate and respiratory rate of a target human body, the signal processing module is used for judging whether vital sign indexes exceed a set threshold value, and if yes, a notice or a timely alarm is sent to a related contact person or a caregiver through the cloud early warning module;
the signal processing module is used for obtaining the body posture and the motion information of the target human body according to the distance-speed spectrogram and the distance-angle spectrogram, judging whether an emergency happens or not according to the body posture and the motion information of the target human body, and if yes, sending a notice or timely alarming to a related contact person or a caregiver. The body posture and the movement of the old people are monitored in real time and accurately identified, and when the old people have emergencies, the old people send notifications or timely alarms to related contacts or caregivers.
Meanwhile, data are uploaded to the cloud health maintenance service platform, and the data have the traceable characteristic, so that the old-age care organization can be helped to clear responsibility and reduce risks. Meanwhile, a health file is established on a cloud health maintenance service platform, health data analysis is carried out on the old people with customized services through an AI algorithm, health reports are sent regularly, improvement or treatment schemes are made, health data are fed back in time, and the schemes are corrected.
The real-time sleep monitoring system is used for monitoring the sleep in real time in the environment familiar to the user, so that more accurate data can be obtained, a doctor is assisted in diagnosing and treating, and meanwhile, data are fed back in time in the process of treating or improving the sleep quality, and the doctor or an expert is helped to correct the scheme.
The system is combined with the intelligent home, intelligent home control is performed through various modes such as gestures and voice, operation difficulty is reduced, and the system is suitable for operation habits of different old people.
Example two
As shown in fig. 2, the present embodiment provides an intelligent monitoring method for a nursing home based on millimeter wave radar, by adopting FMCW millimeter wave radar principle, emitting millimeter waves outwards through a microstrip array antenna, receiving reflected and transmitted signals of a target object, acquiring phase information of the target object, analyzing and processing data of the phase information, therefore, the data of various vital signs such as the respiratory rate, the heart rate and the like of the human body are obtained without visual contact, the real-time health monitoring is carried out on the elderly patients, when the data reaches the threshold value set before by the intelligent nursing system, an instant alarm is sent to the nursing person or the associated persons to inform the nursing person or the associated persons, and through a cloud technology and an AI intelligent algorithm, health data of the user object are collected and analyzed, a health file is established for the old with customized service, a health report is sent regularly, a treatment scheme is made or improved in a targeted manner, and health information is fed back in time.
The method comprises the following steps:
s1, sending radar signals to the target to be detected, and receiving returned echo signals;
s2, processing the echo signals to obtain a distance-velocity spectrogram and a distance-angle spectrogram, judging whether the target to be detected is the target human body or not based on the distance-velocity spectrogram and the distance-angle spectrogram, if so, calculating distance information of the fluctuation of the surface of the chest cavity of the target human body in unit time according to the echo signals, and extracting vital sign data of the target human body according to phase difference signals in the distance information;
and S3, judging whether the target human body vital sign data exceed a set threshold value, if so, sending an early warning signal to a cloud early warning module, and sending a notice or timely warning to a related contact person or a caregiver through the cloud early warning module. And obtaining the body posture and the motion information of the target human body according to the distance-speed spectrogram and the distance-angle spectrogram, judging whether an emergency occurs according to the body posture and the motion information of the target human body, and if so, sending a notice or timely alarming to a related contact person or a caregiver.
As shown in fig. 3-4, the FMCW millimeter wave radar main RF component includes a synthesizer, a transmitting antenna (TX), a receiving antenna (RX), a Radio Frequency (RF) component, and a mixer, and its operation principle is as follows:
the signal generator generates a chirp signal and transmits the signal x via a transmitting antennaT(t) the echo signal reflected by the target is received by the receiving antenna, the transmitted signal and the received signal xRAnd (t) entering a mixer for mixing to obtain a difference signal of the transmitting signal TX and the receiving signal RX, namely an Intermediate Frequency (IF) signal.
Wherein the transmission signal x of the FMCW radarT(t) can be expressed as:
wherein f iscIs the start frequency of the chirp signal, B is the bandwidth, ATXIs the amplitude of the transmitted signal, θ (T) is the phase noise, TcIs the width of the chirp signal pulse,
is the slope of the chirp signal, which represents the change in frequency.
Received signal xR(t) is:
in the formula, tdFor time delay, td2x (t)/c, x (t) is the chest-to-radar distance, x (t) ═ r (t) + d0R (t) is the displacement of the chest movement, d0The distance from the radar sensor to the human body, and c is the speed of light.
The echo signal and the transmission signal are mixed by two orthogonal I/Q channels and then passed through a low pass filter to obtain an intermediate frequency signal SIF(t)：
Wherein f isbAnd
comprises the following steps:
in the period between the vertical dashed lines in fig. 5, the IF signal is only valid for the period in which the TX chirp and the RX chirp overlap, and the distance between the two lines is fixed, which means that the IF signal contains a single tone signal of constant frequency.
Fig. 6 shows the reception of three different RX chirps from different objects. The delay of each chirp is different and is proportional to the distance to the object. The different RX chirps are converted into a plurality of IF single tone signals, each of which is of constant frequency.
The heart beat and the breathing rate are important indicators of the cardiopulmonary function of the human body, and for a typical adult, the heart beat is about 60 to 100 beats per minute, and the breathing is 15 to 30. The beating process of the human heart can be observed in a plurality of medical images, the motion mode is similar to vibration expansion and contraction, and the expansion and contraction amplitude is about 0.01-0.2 mm; and the rate of the human heartbeat is periodically changed in a stable range, so that the heartbeat can be approximated to a sinusoidal vibration model.
The respiration is completed by expanding and contracting the thoracic cavity, is similar to sine vibration and can be approximated to a sine vibration model, and the fluctuation amplitude of the model is about 0.1-0.5 mm. Because the respiratory frequencies of heartbeats are different, phase delay exists between the two, and assuming that the human body is in a static state relative to the radar, a chest motion displacement model r (t) can be established according to the analysis:
R(t)＝R0+H(t)+X(t) (6)
wherein H (t) is a respiratory component, X (t) is a heartbeat component, R0Distance between radar and human body, H (t) ═ Ahsin(2πfht)，X(t)＝Absin(2πfbt+θ)。
Wherein A ishAmplitude of vibration for respiration, fhIs the frequency value of respiration, AbAmplitude of vibration of heartbeat, fbBeing the frequency value of the heartbeat, θ is the initial phase of the heartbeat.
The heart beat, respiratory displacement and frequency parameters of the ordinary adult are as follows:
TABLE 1 adult Heart beat, respiratory Displacement and frequency parameters
As shown in fig. 7, the schematic diagram of the monitoring of the vital signs of the millimeter wave radar is shown, the signal generator of the millimeter wave radar of the vital sign monitoring module transmits a signal, the transmitted signal is reflected after encountering an object to be measured, the reflected echo signal is also different due to the vibration of the thoracic cavity caused by respiration and heartbeat, the echo signal is captured by the orthogonal receiver and orthogonally mixed with the transmitted signal to generate a mixing signal, and a low-pass filter is used for filtering a high-frequency part to obtain an intermediate-frequency signal.
The phase difference signal acquisition process in the distance information comprises the following steps:
and performing AD sampling on each linear frequency modulation signal to generate a time domain sampling signal, and performing distance FFT on the time domain sampling signal.
FFT is performed with a single chirp on a fast sampling time axis to obtain a spectrum of a beat signal whose peaks correspond to objects at different distances, called range FFT. And performing FFT on a slow sampling time axis to obtain the vibration frequency, which is called vibration FFT.
And recording and calculating the phase on the target distance unit every time the linear frequency modulation signal is ended, and calculating the phase change to obtain a phase difference set.
After a group of data is collected, filtering and FFT (fast Fourier transform) processing are carried out on the data stored by the upper computer to obtain time domain and frequency domain information of respiration and heartbeat, the heart rate and the respiration rate are obtained through spectral peak searching and calculating, and the heart rate and the respiration rate are displayed through a display interface.
The millimeter wave radar can transmit signals with the wavelength of millimeter magnitude. In the electromagnetic spectrum, this wavelength is considered to be a short wavelength, which is also one of the advantages of this technology. Thus, the size of the system components (e.g., antennas) required to process millimeter-wave signals is truly small, and another advantage of the short wavelengths is high accuracy. A millimeter wave system with an operating frequency of 76-81 GHz (corresponding to a wavelength of about 4mm) will be able to detect movements as small as a few tenths of a millimeter.
The obtaining of the body posture and the motion information of the target human body according to the distance-velocity spectrogram and the distance-angle spectrogram comprises: firstly, echo signals are subjected to noise removal through a low-noise amplifier to ensure the smoothness of waveforms, high-frequency signals are filtered through a low-pass filter, intermediate-frequency signals acquired by an FMCW radar are subjected to analog-to-digital conversion, a distance-speed spectrogram and a distance-angle spectrogram are obtained through Fourier transform, and information such as the speed, the direction, the distance, the signal-to-noise ratio and the like of a target is acquired through the processed signals according to a target monitoring algorithm and a multi-target tracking method. The static object eliminating algorithm is used for eliminating the static object in the indoor environment, and the interference of the static object to the moving target is avoided. False detection points caused by target motion in an indoor scene are eliminated through a multipath interference elimination algorithm, and the problem of false alarm caused by the fact that the false detection points are mistakenly considered by a millimeter wave radar sensor as targets to be tracked and output is avoided.
The CFAR algorithm is acted on the distance-speed spectrogram and combined with the distance-angle spectrogram to obtain point cloud, because the head, the arms, the legs and the like of a person can generate reflection, a plurality of reflection points can be generated in a radar detectable range, the obtained point cloud data needs to be subjected to condensation processing by using a density clustering algorithm, the detected points are condensed into a cluster, and the cluster is regarded as a human body target.
When a person moves, a corresponding cluster is required to move, and the position and the speed of the person can be obtained according to the position and the speed of the cluster.
In this embodiment, the detection algorithm is a CFAR-CA algorithm, the CFAR window size is 32, and the CFAR threshold is 18 dB.
As shown in fig. 8(a) -8 (b), the data obtained by conducting a plurality of experiments indoors are analyzed, the interface displays 0 when no person enters, and tracking and positioning are performed when a person appears, so that the number of persons and the position information are displayed. As can be seen from fig. 8(b), the current number of people is 4, and dynamic tracking and positioning can be performed when people move, and the iris display is the current position of the people.
Sinusoidal signals transmitted by the millimeter wave radar transmit frequency modulation continuous pulse signals to a target on a plurality of transmitting antennas TX in a time division multiplexing mode, echo signals reflected by the target are received through a plurality of radar receivers RX, the echo signals are collected and processed, the processed echo signals are mixed with the transmitting signals, I/Q two-path baseband signals are obtained, the I/Q two-path baseband signals are demodulated, frequency values and peak values of respiration and heartbeat are obtained through filtering and fast Fourier transform, and respiration and heartbeat rates are output.
The distance-velocity diagram obtained by 2D-FFT computation of one frame of the captured scene is shown in fig. 9. The x-axis represents speed (in meters per second) and the y-axis represents range (in meters). The strong reflector is displayed in a brighter color and the noisy floor is displayed in a dark blue color. The 2D output of each channel may be independently selected using a channel selector. If the "common" option is selected in the channel selector, the non-coherent sum of the 2D FFT outputs across the channels is plotted.
As shown in fig. 10(a) -10 (d), in the present embodiment, the hamming window algorithm used by the FFT window function significantly narrows the strong reflection area of the 2d DFFT amplitude diagram when the windowless design is used, the CFAR-CA algorithm is used as the detection algorithm, and as is clear from the one-dimensional FFT amplitude diagram, the large fluctuation is caused by respiration, and the small peak and valley is caused by heartbeat. The real waveform and the ideal waveform of the time domain diagram are approximately the same.
Fig. 11(a) -11 (f) are test result graphs of the tester 1 in the case of keeping normal breathing, the tester is about 0.5m away from the radar, the tester 1 breathes 18 times/min at this time, and the heartbeat is 68 times/min, fig. 12(a) -12 (f) are test result graphs of the tester 2 in the case of keeping normal breathing, the tester is about 0.8 m away from the radar, the tester 2 breathes 13 times/min at this time, and the heartbeat is 80 times/min, and the respiratory and heartbeat signal waveforms, the thoracic cavity displacement change and the one-dimensional distance graph of the target can be smoothly displayed in the detection process.
Fig. 13(a) -13 (f) are graphs of the test result of the tester 3 holding his breath, as shown in the figure, the breath of the tested person is 0, the change of the respiration waveform is very small and tends to zero, but the heartbeat waveform is still clear, and because of holding his breath, the displacement of the thoracic cavity of the tested person is caused by the heartbeat of the human body, and the displacement of the thoracic cavity caused by the heartbeat of the human body is much smaller than that caused by the breath, so it can be seen from fig. 13(a) -13 (f) that the displacement of the thoracic cavity at this time also becomes gradually smaller in the process of switching the tested person from normal breathing to holding breathing.
Through the tests, the designed system can be stably operated, and important information such as respiratory and heartbeat frequency required by people can be obtained.
The invention mainly adopts 77GHz millimeter wave radar technology, cloud computing technology and AI intelligent algorithm, wherein, the 77GHz millimeter wave radar transmits millimeter waves outwards through the microstrip array antenna, receives reflected and transmitted signals of a target object, acquires phase information of the target object and analyzes and processes data of the phase information, therefore, the data of various vital signs such as the respiratory rate, the heart rate and the like of the human body are obtained without visual contact, the real-time health monitoring is carried out on the elderly patients, when the data reaches the threshold value set before by the intelligent nursing system, an instant alarm is sent to the nursing person or the associated persons to inform the nursing person or the associated persons, and through a cloud technology and an AI intelligent algorithm, health data of the user object are collected and analyzed, a health file is established for the old with customized service, a health report is sent regularly, a treatment scheme is made or improved in a targeted manner, and health information is fed back in time.
Synthesize above technique, organically combine soft service systems such as with intelligent house with it, with this project wide application in institutional type endowment, community formula endowment is in the healthy endowment at home, let more old person just can enjoy a long service through pronunciation and limbs action, the precision and the efficiency of monitoring have been improved greatly, the cost of labor has been reduced, make simultaneously again that we can furthest reduce to the greatest extent as far as possible to old person's operation difficulty degree and uncomfortable and feel, the healthy endowment service of high-quality has been provided for more old person, thereby realized satisfying different aspect, diversified endowment requirement. The system is suitable for all people, is not easily influenced by environments such as smoke and the like, has higher response speed and wider monitoring range, realizes the purpose of checking the health condition of people at any time and any place, finds problems in time and takes measures, and avoids danger. The method can realize the detection within twenty-four hours without invading privacy and being bound by equipment, and truly and effectively reflects the real condition of the detected person. The intelligent monitoring system brings more comfortable and faster intelligent experience to human bodies, has very important significance in the aspect of non-contact monitoring, and has wide future application value.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. The utility model provides a nursing home intelligence guardianship device based on millimeter wave radar which characterized in that includes: the system comprises a vital sign signal acquisition module, a signal processing module and a cloud early warning module;
the vital sign signal acquisition module is used for sending a radar signal to a target to be detected and receiving a returned echo signal, the signal processing module is used for processing the echo signal to obtain a distance-speed spectrogram and a distance-angle spectrogram, judging whether the target to be detected is a target human body or not based on the distance-speed spectrogram and the distance-angle spectrogram, if so, calculating distance information of the surface fluctuation of the chest cavity of the target human body in unit time according to the echo signal, and extracting vital sign data of the target human body according to a phase difference signal in the distance information;
the signal processing module is used for judging whether a set threshold value is exceeded or not according to the target human body vital sign data, if so, sending an early warning signal to the cloud early warning module, and sending a notice or timely warning to a related contact person or a caregiver through the cloud early warning module.
2. The intelligent nursing home monitoring device based on millimeter wave radar as claimed in claim 1, further comprising a cloud early warning module, wherein the cloud early warning module is connected with the signal processing module, the signal processing module is configured to obtain the body posture and motion information of the target human body according to the distance-velocity spectrogram and the distance-angle spectrogram, determine whether an emergency occurs according to the body posture and motion information of the target human body, and if so, send a notification or a timely alarm to a caregiver or a timely alarm of a relevant contact person.
3. The intelligent monitoring device for the nursing home based on the millimeter wave radar as claimed in claim 1, wherein the vital sign signal collecting module comprises a signal generator and a millimeter wave radar transceiver unit;
the signal generator is used for generating a chirp radar signal; and the millimeter wave radar transceiver unit is used for transmitting the generated chirp radar signal through the transmitting antenna.
4. An intelligent nursing home monitoring method based on a millimeter wave radar is characterized by comprising the following steps:
sending a radar signal to a target to be detected, and receiving a returned echo signal;
processing the echo signals to obtain a distance-velocity spectrogram and a distance-angle spectrogram, judging whether the target to be detected is a target human body or not based on the distance-velocity spectrogram and the distance-angle spectrogram, if so, calculating distance information of the surface fluctuation of the chest cavity of the target human body in unit time according to the echo signals, and extracting vital sign data of the target human body according to phase difference signals in the distance information;
and judging whether the target human body vital sign data exceeds a set threshold value, if so, sending an early warning signal to a cloud early warning module, and sending a notice or timely warning to a related contact or a caregiver through the cloud early warning module.
5. The intelligent nursing home monitoring method based on millimeter wave radar as claimed in claim 4, wherein the body posture and movement information of the target human body are obtained according to the distance-velocity spectrogram and the distance-angle spectrogram, whether an emergency occurs or not is judged according to the body posture and movement information of the target human body, and if yes, a notification or a timely alarm is sent to a relevant contact person or a caregiver.
6. The intelligent nursing method of claim 4, wherein the obtaining of the body posture and motion information of the target human body according to the distance-velocity spectrogram and the distance-angle spectrogram comprises: and (3) performing a CFAR algorithm on the distance-speed spectrogram and combining the distance-angle spectrogram to obtain point cloud data, performing aggregation on the point cloud data by using a density clustering algorithm, aggregating the detected points into clusters, taking each cluster as a human body target, and obtaining the body posture and motion information of the target to be detected according to the position and speed of the clusters.
7. The intelligent nursing method for the aged based on millimeter wave radar as claimed in claim 4, wherein the phase difference signal obtaining process in the distance information comprises:
receiving an echo signal reflected by a target human body, obtaining an intermediate frequency signal based on the reflected echo signal, carrying out FFT (fast Fourier transform) on the intermediate frequency signal to obtain distance information of a real-time tracking target, obtaining a phase on a target distance unit based on the distance information of the tracking target, and calculating phase change to obtain a phase difference set.
8. The intelligent nursing method for the aged based on millimeter wave radar as claimed in claim 4, wherein the human vital sign data includes a respiration signal and a heartbeat signal, and the respiration signal and the heartbeat signal are filtered and fast Fourier transformed to output respiration and heartbeat rates.
9. The intelligent nursing method for the aged based on millimeter wave radar as claimed in claim 4, wherein the phase difference signal obtaining process in the distance information comprises:
performing AD sampling on each linear frequency modulation signal to generate a time domain sampling signal, and performing distance FFT on the time domain sampling signal;
FFT is carried out on a fast sampling time axis and a slow sampling time axis to obtain distance FFT and vibration FFT;
and calculating the phase on the target distance unit based on the distance FFT and the vibration FFT, thereby calculating the phase change and obtaining a set of phase differences.
10. The intelligent nursing method of the nursing home based on millimeter wave radar as claimed in claim 4, wherein the distance information of the surface relief of the chest cavity of the target human body is obtained based on a chest movement displacement model, and the chest movement displacement model is:
R(t)＝R0+H(t)+X(t)
wherein H (t) is a respiratory component, X (t) is a heartbeat component, R0Distance between radar and human body, H (t) ═ Ahsin(2πfht)，X(t)＝Absin(2πfbt+θ)，AhAmplitude of vibration for respiration, fhIs the frequency value of respiration, AbAmplitude of vibration of heartbeat, fbBeing the frequency value of the heartbeat, θ is the initial phase of the heartbeat.
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