CN117218793A - High-accuracy household type fall alarm intelligent robot - Google Patents
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Abstract
The application provides a high-accuracy household intelligent robot for fall alarm, which is used in combination with an intelligent watch or an intelligent bracelet worn on the hand of a wearer, wherein the intelligent watch or the intelligent bracelet monitors basic physiological indexes of the wearer and integrates a 3D low-frequency antenna, and the household intelligent robot for fall alarm comprises: the mobile chassis is provided with a laser radar and an ultrasonic sensor, and a main body structure arranged on the mobile chassis, wherein a 3D base station antenna, a millimeter wave radar sensor, a camera and a main control board are arranged in the main body structure; the main control board judges whether the wearer falls or is in the position of falling based on the millimeter wave radar sensor, based on electromagnetic intensity of three directions of the 3D low-frequency antenna on the intelligent watch or the intelligent bracelet, calculates the absolute ground clearance of the wearer based on the electromagnetic intensity of three directions, judges that the wearer falls if the absolute ground clearance is lower than a set height and the wearer is in the position of lying down, realizes the effect of accurately detecting the fall of the old on the mobile robot, and has the accuracy rate of more than 99%.
Description
Technical Field
The application relates to the field of intelligent robots, in particular to a high-accuracy household intelligent robot for fall alarm.
Background
A fall refers to a sudden, involuntary, unintended posture change. Compared with young people, the old people are very fragile in bone, the old people are easy to fall down to generate hip fracture, lumbar vertebra fracture and other phenomena when the hip lands, so that normal standing and walking are affected, and once the old people lie in bed for a long time, the old people are easy to generate problems of infection, pressure sore, lower limb deep vein thrombosis and the like, and statistics show that the death rate of the old people is very high one year after the hip fracture. According to measurement and calculation, the elderly in China is up to 1.2 hundred million people, more than 6000 thousands of elderly fall every year, wherein about 60% of the elderly fall in home, the occurrence rate of fall fracture of the elderly is up to 20%, the death rate of the elderly in one year after hip fracture is up to 30%, the hazard degree is obviously higher than that of cancers, and how to fall of the elderly in home in time is urgent need of the elderly in the world, communities, children and health care institutions.
At present, although home care robots exist in the market, most home care robots only can provide basic functions such as basic physiological index measurement, voice interaction, medication reminding and the like, and the problem of the pain point of the old in the falling alarm requirement cannot be solved. Of course, products are also used for realizing falling detection through millimeter wave sensors or cameras installed at high places of home care environments such as bathrooms, living rooms and bedrooms, for example, CN115662060a provides a method for monitoring the activity state of old people through millimeter wave radar sensors, the human falling sensors mentioned in the method are needed to be installed at indoor high places to realize the detection of falling behaviors of the old people, the problem of high installation difficulty exists, and millimeter wave radar signals only judge whether falling behaviors exist through distance Doppler information, so that the normal living behaviors of the old people in sleeping rest are often misjudged as falling behaviors, and the misreporting rate of a scheme for detecting falling by utilizing the millimeter wave sensors is as high as more than 5%, so that the application of the products becomes display and furnishing in various home care places.
Disclosure of Invention
The application provides a high-accuracy household intelligent falling alarm robot which is designed into a mobile structure integrating physiological index detection and falling detection, can track old people to realize real-time falling detection, and combines the monitoring of a millimeter wave sensor and an absolute ground clearance to improve the accuracy of falling detection.
For realizing above purpose, this scheme provides high accuracy's house formula intelligent robot of reporting to police of tumbleing, and cooperation is worn on the person's of wearing intelligent wrist-watch or intelligent bracelet and is used, and wherein intelligent wrist-watch or intelligent bracelet monitor the basic physical index of person of wearing and integrate 3D low frequency antenna, and house formula intelligent robot of reporting to police of tumbleing includes:
the mobile chassis is provided with a laser radar and an ultrasonic sensor, and a main body structure arranged on the mobile chassis, wherein a 3D base station antenna, a millimeter wave radar sensor, a camera and a main control board are arranged in the main body structure;
the main control board acquires distance sensing signals fed back by the laser radar and/or the ultrasonic sensor, and adjusts and controls the walking track of the mobile chassis through the motor based on the distance sensing signals;
the method comprises the steps that a main control board obtains a 3D height point cloud signal collected by a millimeter wave radar sensor, the 3D height point cloud signal is processed to obtain point cloud data comprising the distance, horizontal angle, vertical angle and speed of a target, and whether a wearer falls or is in a falling position is judged based on the point cloud data;
the main control board obtains the electromagnetic intensity of three directions of the 3D low frequency antenna on the intelligent watch or the intelligent bracelet, calculates the absolute ground clearance of the wearer based on the electromagnetic intensity of three directions, and if the absolute ground clearance is lower than the set height and the wearer is in the sleeping position, then judges that the wearer falls.
Compared with the prior art, the technical scheme has the following characteristics and beneficial effects:
the intelligent household falling alarm robot is characterized in that the intelligent household falling alarm robot is fixedly arranged at a specific space position, the intelligent household falling alarm robot is integrated with a physiological monitoring sensor and a falling detection sensor, the chassis of the intelligent household falling alarm robot can track the track of the old people for 24 hours freely, non-contact data such as falling and physiology are detected within the range of 0.5m-2m, and due to the enhancement of signal to noise ratio, the difficulty and cost of installation and implementation are reduced, and the false alarm rate is reduced. The intelligent watch or the intelligent bracelet is worn on the hands of the old people in a linked mode, the intelligent watch or the intelligent bracelet interacts with the robot to detect the absolute vertical distance between the wearer and the ground, the position of the person is judged by utilizing the absolute ground clearance, the person can be considered to lie on the ground if the absolute ground clearance between the person and the ground is generally less than 35 centimeters, the detection signal of the millimeter wave sensor is combined with time tracking to judge the lying time so as to accurately judge whether the person is in the falling action, and the false alarm rate of the falling action detection is reduced.
Drawings
Fig. 1 is a schematic structural diagram of a high-accuracy household type fall alarm intelligent robot.
Fig. 2 is a logic schematic diagram of the main control board in this scheme for judging whether the wearer falls or is in a falling position.
Fig. 3 is a schematic diagram of the UWB radar non-contact test user physiological index of the present solution.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which are derived by a person skilled in the art based on the embodiments of the application, fall within the scope of protection of the application.
It will be appreciated by those skilled in the art that in the present disclosure, the terms "longitudinal," "transverse," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," etc. refer to an orientation or positional relationship based on that shown in the drawings, which is merely for convenience of description and to simplify the description, and do not indicate or imply that the apparatus or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore the above terms should not be construed as limiting the present application.
It will be understood that the terms "a" and "an" should be interpreted as referring to "at least one" or "one or more," i.e., in one embodiment, the number of elements may be one, while in another embodiment, the number of elements may be plural, and the term "a" should not be interpreted as limiting the number.
The scheme provides a high accuracy's intelligent robot of warning of falling at home, cooperation wear in the intelligent wrist-watch or intelligent bracelet on the wearer's hand and use, and wherein intelligent wrist-watch or intelligent bracelet monitor the basic physical index of wearer and integrate 3D low frequency antenna, and this intelligent robot includes:
the mobile chassis is provided with a laser radar and an ultrasonic sensor, and a main body structure arranged on the mobile chassis, wherein a 3D base station antenna, a millimeter wave radar sensor, a camera and a main control board are arranged in the main body structure;
the main control board acquires distance sensing signals fed back by the laser radar and/or the ultrasonic sensor, and adjusts and controls the walking track of the mobile chassis through the motor based on the distance sensing signals;
the method comprises the steps that a main control board obtains a 3D height point cloud signal collected by a millimeter wave radar sensor, the 3D height point cloud signal is processed to obtain point cloud data comprising the distance, horizontal angle, vertical angle and speed of a target, and whether a wearer falls or is in a falling position is judged based on the point cloud data;
the main control board obtains the electromagnetic intensity of three directions of the 3D low frequency antenna on the intelligent watch or the intelligent bracelet, calculates the absolute ground clearance of the wearer based on the electromagnetic intensity of three directions, and if the absolute ground clearance is lower than the set height and the wearer is in the sleeping position, then judges that the wearer falls.
The utility model provides a fall detection scheme, be different from mainstream fall detection scheme needs to fix millimeter wave sensor and camera in the mode of specific position, this scheme is installed millimeter wave sensor on can be along with the major structure of mobile chassis removal and cooperation 3D low frequency antenna detects the absolute distance from ground of wearer at the peripheral electromagnetic strength of 3D basic station antenna, so the benefit lies in having avoided dead angle and the false alarm that signal attenuation brought that the environment mounted position brought at home care, it is to be explained that, even the current scheme adopts a plurality of millimeter wave radars to cover, also can cause the false alarm because of the multipath effect, still can not be solved under the actual scene of circumstances such as wind blows (window) curtain, shower and the false judgement that the scene caused, the accuracy of the intelligent robot of the warning of the family formula of falling detection of this scheme is more than 99%.
The millimeter wave radar sensor provided by the scheme comprises a transmitter for transmitting millimeter wave signals, a multiple-input multiple-output antenna array for radiating and receiving the millimeter wave signals, and a signal processing unit for processing and analyzing the signals.
As shown in fig. 2, in the step of acquiring a 3D high-altitude point cloud signal acquired by a millimeter wave radar sensor by a main control board, processing the 3D high-altitude point cloud signal to obtain point cloud data including a distance, a horizontal angle, a vertical angle and a speed of a target, the millimeter wave radar sensor transmits a frequency modulation continuous wave signal to the outside and receives data by using an internal antenna array, processes the received data of each horizontal receiving antenna in the antenna array to obtain a distance horizontal direction heat map, detects a target point based on the distance horizontal direction heat map, calculates a space matrix of all antennas in the antenna array on each target point, generates a vertical direction heat map of the target on the space matrix by BF in a vertical direction, calculates a BF vector on the distance, the horizontal angle and the vertical angle of the target on the vertical direction heat map, acquires a doppler spectrum based on the BF vector, acquires a speed of the target on the doppler spectrum by a peak, and further obtains point cloud data including the distance, the horizontal angle, the vertical angle and the speed of the target.
In some embodiments, the antenna array is composed of antennas of horizontal receiving antennas and vertical receiving antennas arranged in an array. According to the scheme, after one-dimensional windowed fast Fourier transform is carried out on the received data of each horizontal receiving antenna, static clutter removal is carried out on the received data in the horizontal direction to obtain horizontal data, the horizontal data of the horizontal receiving antennas in all horizontal directions are taken for calculating a horizontal space matrix, and a distance horizontal direction heat map is generated by calculating the horizontal space matrix through Capon BF. Capon BF refers to Capon beamforming, which is a high resolution signal processing technique that can be used to extract directional information of a target.
The method comprises the steps of converting received data of a horizontal receiving antenna into frequency domain data after Fourier transformation, removing clutter signals in the frequency domain data through a static clutter removal technology to obtain horizontal data, grouping the horizontal data according to the distances of the horizontal receiving antenna to form a horizontal space matrix, taking the horizontal data at different distances as columns of the horizontal space matrix, and enabling each horizontal receiving antenna to correspond to one row of the horizontal space matrix.
In some embodiments, the target point is detected in a distance horizontal direction heat map by a two-dimensional CFAR. Specifically, defining windows and background areas on the heat map in the horizontal direction, calculating the pixel mean value and the pixel standard deviation of the background areas, traversing each window, calculating the pixel mean value of each window, and comparing the pixel mean value of the window with the background mean value to determine a target point.
In some embodiments, a spatial matrix of all antennas in the antenna array is calculated on each target point, where the spatial matrix describes spatial characteristics of the antennas in different directions, a beam weight of the target point in a vertical direction is calculated on the spatial matrix by a beam forming algorithm in a vertical direction, the calculated beam weight is applied to the spatial matrix to obtain a vertical direction heat map of the target, and the vertical direction heat map shows energy distribution of the target in the vertical direction.
In some embodiments, the vertical angle of the target is calculated by the peak on the vertical direction heat map, the distance and horizontal angle of the target are calculated by the peak on the horizontal direction heat map, and the BF vector is calculated by calculating the vertical angle, horizontal angle, distance of the target. The target distance bin is then spatially filtered with BF vectors and a doppler spectrum is computed, on which the velocity of the target is finally obtained by a peak search.
Because the point cloud data comprise the point cloud data of the distance, the horizontal intersection, the vertical angle and the speed of the targets, the targets can be clustered based on the point cloud data according to a Group Tracking algorithm, the targets are tracked and predicted, and the spatial position, the speed and the acceleration information of each target are generated, so that whether the wearer falls or is in a falling position is judged.
In some embodiments, whether the wearer has a rapid descending movement mode can be determined according to the acceleration information and the speed information of the target, whether the posture of the wearer has a tilting tendency is determined according to the spatial position of the target, and if the rapid descending movement mode is converted from a vertical posture to a transverse posture, the wearer is determined to be in a tilting posture. In some embodiments, the height information of the target is determined according to the spatial position of the target, the height differences of the target at different moments are compared, and if rapid height difference changes occur, the target is determined to be in a lying position.
In addition, in order to improve the performance of fall detection, the scheme needs to acquire the point cloud data which is as rich as possible, so that millimeter wave signals emitted by the millimeter wave radar sensor can be irradiated on the body of the wearer more, the scheme can irradiate the head, the trunk and the feet of the wearer according to the position of the wearer and rotate the millimeter wave radar sensor so that the main beam of the antenna surface of the millimeter wave radar sensor can irradiate on the head, the trunk and the feet of the wearer, and further the point cloud data which are rich are formed, so that the signal to noise ratio of detection is greatly improved, and the accuracy of fall detection is improved.
It should be noted that, although whether the user falls or is in a falling position can be primarily determined by using the millimeter wave radar sensor, similar point cloud data can be generated in an actual detection process, such as when the user sits on a sofa, sits on a toilet, lies on a bed, lies on the sofa, and the like, so that the millimeter wave radar sensor has a larger false alarm rate when detecting the falling behavior alone. And because prior art's millimeter wave sensor all installs in fixed position, this just has led to traditional millimeter wave sensor to exist the monitoring blind area, for this reason, this scheme further judges the absolute altitude that leaves the ground of wearer through 3D electromagnetic wave intensity location technique, combines absolute altitude to judge whether the wearer tumbles, has improved the rate of accuracy that tumbles detected, and the robot of this scheme is mobile robot trackable old man, and then has eliminated the monitoring blind area.
In the step of acquiring electromagnetic intensities of three directions of a 3D low-frequency antenna on a smart watch or a smart bracelet by a main control board, a 3D base station antenna of a main structure transmits a low-frequency signal to generate a vector electromagnetic field around a household fall alarm intelligent robot, and the vector electromagnetic field excites current on the 3D low-frequency antenna and is converted into the electromagnetic intensities of three directions. Specifically, the smart watch or the smart bracelet is internally provided with a 3D low-frequency antenna consisting of three mutually perpendicular low-frequency antennas, the three low-frequency antennas are arranged in an X/Y/Z axis three-way mode, a 3D base station of the main structure outwards transmits 125KHZ low-frequency signals through a sequential transmission module so as to generate a vector electromagnetic field around the household fall alarm intelligent robot, the vector electromagnetic field excites currents on the low-frequency antennas arranged in three directions, and the currents are converted into voltage quantities and into electromagnetic intensities in three directions through a hardware circuit.
In the step of calculating the absolute ground clearance of the wearer based on the electromagnetic intensities of three directions, the distance between the 3D low-frequency antenna and the robot in each direction is calculated based on the electromagnetic intensity of each direction, the three-dimensional coordinates of the 3D low-frequency antenna in each direction relative to the watch are obtained, the position of the intelligent watch or the intelligent bracelet is calculated based on the distance between the 3D low-frequency antenna in each direction and the robot and the three-dimensional coordinates relative to the watch, and the absolute ground clearance of the wearer is obtained based on the position of the intelligent watch or the intelligent bracelet.
Specifically, the calculation formulas of the electromagnetic intensity in each direction and the distance between the 3D low frequency antenna and the robot are as follows:
wherein RSSI is electromagnetic intensity, A is electric field intensity at 1m, n is transmission constant of signal, r is distance between 3D low frequency antenna and robot.
The formula for calculating the position of the wristwatch using the following ternary equation is as follows:
wherein R1 represents the distance between the 3D low-frequency antenna in the first direction and the robot, and (x 1, y1, z 1) represents the three-dimensional coordinates of the 3D low-frequency antenna in the first direction relative to the watch; r2 represents the distance between the 3D low frequency antenna in the second direction and the robot, (x 2, y2, z 2) represents the three-dimensional coordinates of the 3D low frequency antenna in the second direction relative to the wristwatch; r3 represents the distance between the 3D low frequency antenna in the third direction and the robot, (x 3, y3, z 3) represents the three-dimensional coordinates of the 3D low frequency antenna in the third direction relative to the wristwatch, and the position of the wristwatch is (x, y, z).
In some embodiments, the position of the smart watch or smart bracelet in the height direction is taken as the absolute ground clearance of the wearer. After the electromagnetic intensity in three directions is obtained by the intelligent watch or the intelligent bracelet, the sampling value is sent to the main control board of the main structure through Bluetooth signals, and the main control board calculates the absolute ground clearance of the wearer through the calculation method.
In some embodiments, if the absolute ground clearance is between 3 and 35 centimeters and the wearer is in a prone position, then the wearer is determined to fall. Preferably, the wearer is judged to fall when the absolute ground clearance is stabilized at about 20cm or below 20cm and the wearer is in a lying position.
In some preferred embodiments, the maintenance time of the current state is calculated in a state where the absolute ground clearance is below the set height and the wearer is in the prone position, and if the maintenance time is greater than the set threshold, the wearer is judged to fall.
It should be noted that the 3D low-frequency antenna mounted on the smart watch or the smart bracelet not only can be used for being matched with the robot to obtain the absolute ground clearance of the wearer, but also can be used as a signal for waking up the smart watch or the smart bracelet. Specifically, after the intelligent watch or the intelligent bracelet is close to the robot, the 3D low-frequency antenna is placed in a vector electromagnetic field generated by the robot to generate electromagnetic intensity, and at the moment, the 3D low-frequency antenna wakes up other functional components on the intelligent watch or the intelligent bracelet.
The mobile base of the intelligent household falling alarm robot is provided with the laser radar and/or the ultrasonic sensor, the laser radar calculates the distance of a target by emitting a laser beam and measuring the time from the laser radar to return, and the ultrasonic sensor calculates the distance of the target by emitting ultrasonic signals and measuring the round trip time of the ultrasonic signals. Whether the laser radar or the ultrasonic sensor acquires the distance of the target, the distance is used as a distance sensing signal to be transmitted to a main control board, the main control board constructs an environment map according to the distance sensing signal, and a path planning algorithm is utilized to determine the action track of the mobile chassis based on the obtained environment map, wherein the common path planning algorithm comprises Dijkstra algorithm, RRT (Rapid-Exploring Random Trees) and the like. In some embodiments, the variety of mobile bases includes, but is not limited to, wheeled robots, quadruped robots.
In some embodiments, a sensor for measuring basic physiological indexes including, but not limited to, heart rate, electrocardio, blood oxygen, blood sugar, blood pressure and the like is built in the smart watch or the smart bracelet, and the smart watch or the smart bracelet can transmit the monitored basic physiological indexes to a main control board of the robot so as to monitor the physiological indexes of the wearer.
It should be noted that, due to memory deterioration of the old, wearable devices such as an intelligent watch or an intelligent bracelet are easy to forget; on the other hand, the interest of the detected physiological index is lost after the detected physiological index is fresh for a period of time, so the physiological index can be monitored by adopting a non-inductive and non-contact detection technology.
At this time, as shown in fig. 3, the household type fall alarm intelligent robot provided by the scheme is provided with a UWB radar, a receiving and transmitting integrated antenna is arranged in the UWB radar, the UWB radar transmits pulse signals towards a user, the pulse signals touch the thoracic cavity to form reflected signals, and non-contact respiration data and heart rate data are obtained according to the reflected signals.
Specifically, the UWB radar of this scheme sends 10 ns's pulse signal outward, and UWB radar's receiving arrangement's center frequency is 6.8 GHz, and the bandwidth is 2.3 GHz, and transmitting arrangement's nominal output is-53 dBm/MHz, therefore harmless to health, and it provides 4 millimeter spatial resolution. Nanosecond pulses are achieved by a high order gaussian approximation pulse generator, the output center frequency and thus the relative bandwidth is configurable.
The transmitted pulse signals touch the thoracic cavity to form a reflection signal, the reflection signal is modulated by a respiratory signal of 1-3 cm and a heart rate signal of about 0.3cm of the thoracic cavity to obtain a modulated reflection signal, and respiratory data and heart rate data are obtained based on the modulated reflection signal. Specifically, the reflected signal is sampled by a high-speed ADC, each distance point is sampled, a matrix is formed by multiple times of sampling, firstly, the high-speed ADC collects and removes unnecessary clutter signals from the original signal, and each original signal waveform is stored after filtering and is combined into a matrix with the size of'm multiplied by n'. "m" represents the slow time length, and "n" represents the fast time axis along each waveform. The user may select the slow time index "m", with higher values of "m" resulting in better frequency resolution. n is the energy reflected from each distance representing a single pulse measurement, and m is the reflected signal energy representing multiple repeated detection measurements over time; an image formed by this mxn; the method can intuitively see the signal intensity change caused by the movement or the respiration of the human body, further process the signal, eliminate the conditions of random movement, stillness and the like through the algorithm of autocorrelation and the like, and further refine the highly alternating respiration data.
Of course, in order to realize accurate non-contact physical index monitoring, the user needs to be in a static state and close to the robot, generally, before detecting information such as respiration, heart picking and the like, the robot is adjusted to a proper position of the old, and when the old is resting on a bed or a sofa, the robot starts the physical index monitoring. If the correlation width of the obtained reflected signal display is lower than a certain threshold value, the user can be determined to move, so that the measurement of the physiological index is stopped, and the measurement of the breathing and the heartbeat of the inching motion is started again when the user becomes still again.
Regarding the main control board in the main body structure of the scheme, the MCU FS32K144 of NXP is used for realizing algorithms such as radar distance acquisition, motor control, path planning, obstacle avoidance, tracking and the like, the main control system corresponding to the main control board adopts the functions such as NXP SOC iMX6D, cortex-A9 core, 1Ghz main frequency, 4 cores, human body recognition, video recording, falling gesture analysis of video and the like, 5G audio-video conversation and the like.
The present application is not limited to the above-mentioned preferred embodiments, and any person who can obtain other various products under the teaching of the present application can make any changes in shape or structure, and all the technical solutions that are the same or similar to the present application fall within the scope of the present application.
Claims (10)
1. High-accuracy household type fall alarm intelligent robot, cooperation wear in the intelligent wrist-watch or intelligent bracelet on the wearer's hand use, wherein intelligent wrist-watch or intelligent bracelet monitor the basic physical index of wearer and integrated 3D low frequency antenna, its characterized in that, household type fall alarm intelligent robot includes:
the mobile chassis is provided with a laser radar and an ultrasonic sensor, and a main body structure arranged on the mobile chassis, wherein a 3D base station antenna, a millimeter wave radar sensor, a camera and a main control board are arranged in the main body structure;
the main control board acquires distance sensing signals fed back by the laser radar and/or the ultrasonic sensor, and adjusts and controls the walking track of the mobile chassis through the motor based on the distance sensing signals;
the method comprises the steps that a main control board obtains a 3D height point cloud signal collected by a millimeter wave radar sensor, the 3D height point cloud signal is processed to obtain point cloud data comprising the distance, horizontal angle, vertical angle and speed of a target, and whether a wearer falls or is in a falling position is judged based on the point cloud data;
the main control board obtains the electromagnetic intensity of three directions of the 3D low frequency antenna on the intelligent watch or the intelligent bracelet, calculates the absolute ground clearance of the wearer based on the electromagnetic intensity of three directions, and if the absolute ground clearance is lower than the set height and the wearer is in the sleeping position, then judges that the wearer falls.
2. The high-accuracy household intelligent fall alarm robot according to claim 1, wherein the millimeter wave radar sensor transmits frequency modulated continuous wave signals outwards and receives data by using a built-in antenna array, the received data of each horizontal receiving antenna in the antenna array is processed to obtain a distance horizontal direction heat map, a target point is detected based on the distance horizontal direction heat map, a space matrix of all antennas in the antenna array is calculated on each target point, a vertical direction heat map of a target is generated on the space matrix through BF in a vertical direction, BF vectors are obtained by calculating the distance, horizontal angle and vertical angle of the target on the vertical direction heat map and the distance horizontal direction heat map, a doppler spectrum is obtained based on the BF vectors, the speed of the target is obtained through a peak on the doppler spectrum, and point cloud data including the distance, horizontal angle, vertical angle and speed of the target is obtained.
3. The high-accuracy household intelligent falling alarm robot according to claim 1, wherein the intelligent falling alarm robot is characterized in that the intelligent falling alarm robot is used for clustering targets based on point cloud data according to a Group Tracking algorithm, tracking and predicting the targets to generate space position, speed and acceleration information of each target, judging the height information of the targets according to the space positions of the targets, comparing the height differences of the targets at different moments, and judging the intelligent falling alarm robot to be a horizontal position if rapid height difference changes occur.
4. The high-accuracy home-based fall alarm intelligent robot of claim 1, wherein the 3D base station antenna of the main body structure transmits a low frequency signal to generate a vector electromagnetic field around the home-based fall alarm intelligent robot, and the vector electromagnetic field excites a current on the 3D low frequency antenna and converts the current into electromagnetic intensities in three directions.
5. The high-accuracy household intelligent fall alarm robot according to claim 1, wherein the distance between the 3D low-frequency antenna and the robot in each direction is calculated based on the electromagnetic intensity in each direction, the three-dimensional coordinates of the 3D low-frequency antenna in each direction relative to the watch are obtained, the position of the intelligent watch or the intelligent bracelet is calculated based on the distance between the 3D low-frequency antenna in each direction and the robot and the three-dimensional coordinates relative to the watch, and the absolute ground clearance of the wearer is obtained based on the position of the intelligent watch or the intelligent bracelet.
6. The high-accuracy home-based fall alarm intelligent robot according to claim 5, wherein the calculation formula of the electromagnetic intensity of each direction and the distance between the 3D low-frequency antenna and the robot is as follows:
wherein RSSI is electromagnetic intensity, A is electric field intensity at 1m, n is transmission constant of signal, r is distance between 3D low frequency antenna and robot.
7. The high-accuracy home-based fall alarm intelligent robot of claim 5, wherein the formula for calculating the position of the wristwatch using the ternary equation is as follows:
wherein R1 represents the distance between the 3D low-frequency antenna in the first direction and the robot, and (x 1, y1, z 1) represents the three-dimensional coordinates of the 3D low-frequency antenna in the first direction relative to the watch; r2 represents the distance between the 3D low frequency antenna in the second direction and the robot, (x 2, y2, z 2) represents the three-dimensional coordinates of the 3D low frequency antenna in the second direction relative to the wristwatch; r3 represents the distance between the 3D low frequency antenna in the third direction and the robot, (x 3, y3, z 3) represents the three-dimensional coordinates of the 3D low frequency antenna in the third direction relative to the wristwatch, and the position of the wristwatch is (x, y, z).
8. The high-accuracy home-based fall alarm intelligent robot of claim 1, wherein if the absolute ground clearance is 3-35 cm and the wearer is in a prone position, the wearer is determined to fall.
9. The high-accuracy household fall alarm intelligent robot according to claim 1, wherein a sensor for measuring basic physiological indexes including, but not limited to, heart rate, electrocardio, blood oxygen, blood sugar and blood pressure is built in the intelligent watch or the intelligent bracelet, and the intelligent watch or the intelligent bracelet transmits the monitored basic physiological indexes to a main control board of the robot to monitor physiological indexes of a wearer.
10. The high-accuracy household intelligent robot for fall alarm according to claim 1, wherein a UWB radar is arranged on the household intelligent robot for fall alarm, a receiving and transmitting antenna is arranged in the UWB radar, the UWB radar transmits pulse signals towards a user, the pulse signals touch the chest to form reflected signals, and non-contact respiration data and heart rate data are obtained according to the reflected signals.
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| CN117831224A (en) * | 2024-02-29 | 2024-04-05 | 深圳市迈远科技有限公司 | Fall alarm method, device, equipment and medium based on millimeter radar |
| CN117831224B (en) * | 2024-02-29 | 2024-05-24 | 深圳市迈远科技有限公司 | Fall alarm method, device, equipment and medium based on millimeter radar |
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