CN113456368B - Gesture recognition method, system, device, terminal and storage medium - Google Patents
Gesture recognition method, system, device, terminal and storage medium Download PDFInfo
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- CN113456368B CN113456368B CN202111033034.7A CN202111033034A CN113456368B CN 113456368 B CN113456368 B CN 113456368B CN 202111033034 A CN202111033034 A CN 202111033034A CN 113456368 B CN113456368 B CN 113456368B
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61G—TRANSPORT, PERSONAL CONVEYANCES, OR ACCOMMODATION SPECIALLY ADAPTED FOR PATIENTS OR DISABLED PERSONS; OPERATING TABLES OR CHAIRS; CHAIRS FOR DENTISTRY; FUNERAL DEVICES
- A61G5/00—Chairs or personal conveyances specially adapted for patients or disabled persons, e.g. wheelchairs
- A61G5/10—Parts, details or accessories
- A61G5/1051—Arrangements for steering
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61G—TRANSPORT, PERSONAL CONVEYANCES, OR ACCOMMODATION SPECIALLY ADAPTED FOR PATIENTS OR DISABLED PERSONS; OPERATING TABLES OR CHAIRS; CHAIRS FOR DENTISTRY; FUNERAL DEVICES
- A61G2203/00—General characteristics of devices
- A61G2203/10—General characteristics of devices characterised by specific control means, e.g. for adjustment or steering
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61G—TRANSPORT, PERSONAL CONVEYANCES, OR ACCOMMODATION SPECIALLY ADAPTED FOR PATIENTS OR DISABLED PERSONS; OPERATING TABLES OR CHAIRS; CHAIRS FOR DENTISTRY; FUNERAL DEVICES
- A61G2203/00—General characteristics of devices
- A61G2203/30—General characteristics of devices characterised by sensor means
- A61G2203/34—General characteristics of devices characterised by sensor means for pressure
Abstract
The invention provides a gesture recognition method, a system, a device, a terminal and a storage medium, comprising the following steps: receiving pressure data for at least one wheelchair location; determining the sub-postures corresponding to the wheelchair parts according to the pressure data, and calibrating the sub-postures on the corresponding pressure data; importing the pressure data into a preset gesture recognition model, and determining a target gesture of a user; and under the condition that the target posture is within a preset dangerous posture range, sending an alarm signal or a control signal for controlling the wheelchair to realize target action to a target terminal to realize the recognition of the posture of a user on the wheelchair, and sending a related signal under the condition that the posture of the user is in a dangerous state to ensure the safety of the wheelchair user.
Description
Technical Field
The invention belongs to the technical field of wheelchairs, and particularly relates to a posture recognition method, a system, a device, a terminal and a storage medium.
Background
Along with the improvement of the degree of care of people for special crowds, the market of the wheelchair is gradually wide, users using the wheelchair comprise the old, patients and disabled people, the wheelchair can enable the lives of the users to be more convenient and free, but the users also have certain potential safety hazards on the wheelchair, such as the users are easy to lean backwards and fall backwards, are easy to slide downwards from a cushion or turn over easily, and the current wheelchair cannot avoid the safety problems.
Disclosure of Invention
In view of the above-mentioned shortcomings in the prior art, the present invention provides a gesture recognition method, system, device, terminal and storage medium to solve the above-mentioned technical problems.
In a first aspect, the present invention provides a gesture recognition method, comprising:
receiving pressure data for at least one wheelchair location;
determining the sub-postures corresponding to the wheelchair parts according to the pressure data, and calibrating the sub-postures on the corresponding pressure data;
importing the pressure data into a preset gesture recognition model, and determining a target gesture of a user;
and sending an alarm signal or a control signal for controlling the wheelchair to realize the target action to a target terminal under the condition that the target posture is within a preset dangerous posture range.
Further, the method further comprises:
and carrying out normalization processing on the pressure data according to the individual difference of the user.
Further, the method further comprises:
and sending an alarm signal to the target terminal under the condition that the target posture of the user is kept unchanged within a preset time range.
Further, the method further comprises:
predicting a trend gesture of the user according to the target gesture;
and transmitting a control signal to a control terminal of the wheelchair when the trend posture is within the dangerous posture range.
Further, the method further comprises:
and recording the change of the target posture of the current user at different time points, and generating a user behavior analysis chart according to the change.
In a second aspect, the present invention provides a gesture recognition system comprising:
a data receiving unit configured to receive pressure data of at least one wheelchair location;
the data processing unit is configured to determine a sub-posture corresponding to the wheelchair part according to the pressure data and calibrate the sub-posture on the corresponding pressure data;
the gesture determining unit is configured to import the pressure data into a preset gesture recognition model and determine a target gesture of the user;
and the signal transmitting unit is configured to transmit an alarm signal or a control signal for controlling the wheelchair to realize a target action to a target terminal under the condition that the target posture is within a preset dangerous posture range.
In a third aspect, the present invention provides a gesture recognition apparatus comprising: the system comprises a film sensor, a temperature sensor, a humidity sensor, a body parameter sensor, a communication module, a GPU information processing workstation, a controller and a display screen; the thin film sensor, the temperature sensor, the humidity sensor, the body parameter sensor, the controller and the display screen are in communication connection with the communication module, and the communication module is in communication connection with the GPU information processing workstation; the film sensor and the body parameter sensor are both arranged on the wheelchair;
the thin film sensor is used for measuring the pressure exerted on the wheelchair by the body of the user;
the temperature sensor is used for detecting the temperature of the environment where the wheelchair is located;
the humidity sensor is used for detecting the humidity of the environment where the wheelchair is located;
the body parameter sensor is used for measuring body parameters of a user, and the body parameters comprise: at least one of body temperature, blood pressure, blood oxygen, pulse, heart rate, and respiratory rate;
the GPU information processing workstation is used for processing data, recognizing the posture of a user on the wheelchair and sending out an alarm signal and a control signal;
the controller is used for receiving the control signal and controlling the wheelchair to realize the operation corresponding to the control signal;
the display screen is used for displaying the gesture recognized by the GPU information processing workstation and displaying information corresponding to the alarm signal.
In a fourth aspect, a terminal is provided, including:
a processor, a memory, wherein,
the memory is used for storing a computer program which,
the processor is used for calling and running the computer program from the memory so as to make the terminal execute the method of the terminal.
In a fifth aspect, a computer-readable storage medium is provided, having stored therein instructions, which, when run on a computer, cause the computer to perform the method of the above aspects.
The beneficial effect of the invention is that,
the invention provides a gesture recognition method, a system, a device, a terminal and a storage medium, which are characterized in that the method comprises the steps of receiving pressure data of at least one wheelchair part; determining the sub-postures corresponding to the wheelchair parts according to the pressure data, and calibrating the sub-postures on the corresponding pressure data; importing the pressure data into a preset gesture recognition model, and determining a target gesture of a user; and under the condition that the target posture is within a preset dangerous posture range, sending an alarm signal or a control signal for controlling the wheelchair to realize target action to a target terminal, solving the problem of unsafe wheelchair use, realizing the recognition of the user posture on the wheelchair, and sending a related signal under the condition that the user posture is in a dangerous state to ensure the safety of the wheelchair user.
In addition, the invention has reliable design principle, simple structure and very wide application prospect.
Drawings
In order to more clearly illustrate the embodiments or technical solutions in the prior art of the present invention, the drawings used in the description of the embodiments or prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
FIG. 1 is a schematic flow diagram of a method of one embodiment of the invention.
FIG. 2 is a schematic block diagram of a system of one embodiment of the present invention.
Fig. 3 is a schematic structural diagram of a terminal according to an embodiment of the present invention.
Detailed Description
In order to make those skilled in the art better understand the technical solution of the present invention, the technical solution in the embodiment of the present invention will be clearly and completely described below with reference to the drawings in the embodiment of the present invention, and it is obvious that the described embodiment is only a part of the embodiment of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
FIG. 1 is a schematic flow diagram of a method of one embodiment of the invention. Wherein, the execution subject of fig. 1 may be a gesture recognition system.
As shown in fig. 1, the method includes:
s110, receiving pressure data of at least one wheelchair part;
s120, determining a sub-posture corresponding to the wheelchair part according to the pressure data, and calibrating the sub-posture on the corresponding pressure data;
s130, importing the pressure data into a preset gesture recognition model, and determining a target gesture of a user;
and S140, sending an alarm signal or a control signal for controlling the wheelchair to realize target action to a target terminal under the condition that the target posture is within a preset dangerous posture range.
Optionally, as an embodiment of the present invention, the method further includes:
and carrying out normalization processing on the pressure data according to the individual difference of the user.
Optionally, as an embodiment of the present invention, the method further includes:
and sending an alarm signal to the target terminal under the condition that the target posture of the user is kept unchanged within a preset time range.
Optionally, as an embodiment of the present invention, the method further includes:
predicting a trend gesture of the user according to the target gesture;
and transmitting a control signal to a control terminal of the wheelchair when the trend posture is within the dangerous posture range.
Optionally, as an embodiment of the present invention, the method further includes:
and recording the change of the target posture of the current user at different time points, and generating a user behavior analysis chart according to the change.
In order to facilitate understanding of the present invention, a gesture recognition method provided by the present invention is further described below by using the principle of the gesture recognition method of the present invention and combining the process of controlling the wheelchair in the embodiments.
Specifically, the gesture recognition method includes:
s110, receiving pressure data of at least one wheelchair part.
In this embodiment, a single part of the wheelchair is used as a data source to obtain pressure data, which may be external force applied to the wheelchair part by the body of the user.
In one implementation, the wheelchair location may include: wheelchair cushion, wheelchair handle and wheelchair back, then pressure data is: cushion pressure from the user's hips to the cushion, handle pressure from the user's hands to the handles, and back pressure from the user's back to the back. The overall data format of a wheelchair can be 1 × 1024 matrix (1 row, 1024 columns), pressure data can be collected by using pressure sensors with the data format of 32 × 32 for the cushion pressure and the back, pressure data can be collected by using 8 × 16 pressure sensors for the handles on both sides, and then the received data format is as follows: [ cushion pressure (32 × 32) ], [ back pressure (32 × 32) ], [ handle pressure (8 × 16) ]. Wherein, the value formula of the pressure data is as follows:
and sum is the sum of the 10-time voltage values at two ends of the piezoresistor in the pressure sensor.
In one implementation, the method further comprises: and carrying out normalization processing on the pressure data according to the individual difference of the user.
In this embodiment, considering that differences exist between individuals of different users, that is, differences between individuals of all ages, men, women, old, young, tall, thin and the like, the response degrees of the pressure sensors in the same posture are different, and the pressure data collected by different users in the same posture are different, so that normalization processing can be performed on the pressure data, and the normalization processing may include the specific steps of: the largest pressure value in the matrix of pressure data is retrieved and all pressure data in the matrix is divided by the pressure value to obtain a first result, which is multiplied by 255 to obtain a normalized value between 0 and 255. In one implementation, a threshold range may be further set, where the threshold range is used to limit a data range of a received pressure data matrix, and only a pressure data range of a main force-bearing area is obtained, so as to reduce an increase of a data set caused by pressure areas of different users, thereby reducing an influence of an excessive data volume of pressure data due to individual differences, and improving work efficiency.
And S120, determining the sub-postures corresponding to the wheelchair parts according to the pressure data, and calibrating the sub-postures on the corresponding pressure data.
For the sub-postures of the wheelchair part, a pressure range can be preset, when the pressure data are in the pressure range, the sub-postures corresponding to the wheelchair part can be judged, each pressure data is labeled by adopting an enumeration method, and the sub-postures corresponding to the pressure data are labeled; for example [ cushion pressure (32 x 32), left side seat ].
In one implementation, the split position of the wheelchair cushion comprises: no signal is sent to the sitting posture, the left side sitting posture, the right side sitting posture, the left side leg raising sitting posture, the right side leg raising sitting posture and the cushion; the separated posture of the wheelchair handle comprises: the left hand is horizontally placed, the right hand is horizontally placed, the two hands are tightly held, the left hand is tightly held, the right hand is tightly held, and the handle has no signal; the separated posture of the wheelchair backrest comprises: positive, left, right, no signal on the back. It is worth to be noted that the recognition processes of the separated postures of the wheelchair seat cushion and the wheelchair backrest are not influenced mutually.
And S130, importing the pressure data into a preset gesture recognition model, and determining the target gesture of the user.
In this embodiment, the gesture recognition model is trained in advance, and the training process includes: and acquiring a certain amount of labeled pressure data, sending the labeled pressure data into a convolutional neural network, and performing model training, wherein in the convolutional neural network, the posture of a user is determined by the pressure data of all wheelchair parts together, and after the model training is completed, the posture recognition model is obtained and can be called by the wheelchairs in work together, so that the posture judgment of each wheelchair user is realized.
And S140, sending an alarm signal or a control signal for controlling the wheelchair to realize target action to a target terminal under the condition that the target posture is within a preset dangerous posture range.
The dangerous pose may include: the target terminal may include one of a body glide, a body rollover, and a body lean, the dangerous posture range being a threshold range where the pressure data is in a dangerous posture: at least one of an alarm device of a wheelchair, a mobile terminal of a manager, and a control terminal of the wheelchair, the control signal may include: slowly raising the front part of the cushion, turning the backrest forwards and raising the height of the handle. Illustratively, when the user has the risk of body gliding, the safety of the user is protected in a mode of slowly lifting the front part of the seat cushion and sending an early warning signal to a manager; in an implementation mode, the device can send out an early warning signal to prompt a user, informs the user that the current posture is dangerous, reminds the user to change to a safe posture, and sends control to a control terminal of a wheelchair to slowly raise the front part of a cushion to prevent the user from falling if the user still keeps the body gliding posture.
In one implementation, the method further comprises: predicting a trend gesture of the user according to the target gesture; and transmitting a control signal to a control terminal of the wheelchair when the trend posture is within the dangerous posture range. In the embodiment, the wheelchair can be controlled by the hardware part according to different posture change trends. In order to implement the above steps, before the above steps, the method may further include: and recording the target postures of the current user at different time points, generating a trend prediction model of the current user posture, and predicting the trend posture of the current target posture according to the trend prediction model, so that the influence of individual difference on the posture change trend is eliminated.
In one implementation, the method further comprises: and sending an alarm signal to the target terminal under the condition that the target posture of the user is kept unchanged within a preset time range. The preset time range, for example: and 2 minutes, if the user does not change the posture within 2 minutes, the user is possibly in danger of falling down, and an alarm signal needs to be sent to at least one of an alarm device of the wheelchair, a mobile terminal of a manager and a control terminal of the wheelchair.
In one implementation, the method further comprises: the recording and prediction of the posture change of the user are realized, and the user behavior is generated and can comprise the following steps: the behaviors of changing from sitting right to sitting left, from sitting left to sitting right, from sitting right to sitting right, being in a safe state, being in an unsafe state, leaving a wheelchair and the like are analyzed and recorded, and a user analysis chart can be generated.
As shown in fig. 2, the system 200 includes:
a data receiving unit 210 configured to receive pressure data of at least one wheelchair location;
the data processing unit 220 is configured to determine a sub-posture corresponding to the wheelchair part according to the pressure data, and calibrate the sub-posture on the corresponding pressure data;
a gesture determining unit 230 configured to import the pressure data into a preset gesture recognition model, and determine a target gesture of the user;
and a signal transmitting unit 240 configured to transmit an alarm signal or a control signal for controlling the wheelchair to realize a target action to the target terminal when the target posture is within a preset dangerous posture range.
The present embodiment provides a gesture recognition apparatus including: the system comprises a film sensor, a temperature sensor, a humidity sensor, a body parameter sensor, a communication module, a GPU information processing workstation, a controller and a display screen; the thin film sensor, the temperature sensor, the humidity sensor, the body parameter sensor, the controller and the display screen are in communication connection with the communication module, and the communication module is in communication connection with the GPU information processing workstation; the film sensor and the body parameter sensor are both arranged on the wheelchair;
the thin film sensor is used for measuring the pressure exerted on the wheelchair by the body of the user;
the temperature sensor is used for detecting the temperature of the environment where the wheelchair is located;
the humidity sensor is used for detecting the humidity of the environment where the wheelchair is located;
the body parameter sensor is used for measuring body parameters of a user, and the body parameters comprise: at least one of body temperature, blood pressure, blood oxygen, pulse, heart rate, and respiratory rate; measuring a physical parameter of the user monitors whether the physical state of the user is healthy.
The communication module adopts a wireless communication (such as 4G/5G/WiFi) mode and is mainly used for uploading data and sending control signals.
The GPU information processing workstation is used for processing data, recognizing the posture of a user on the wheelchair and sending out an alarm signal and a control signal; the GPU information processing workstation provides various communication interfaces to the outside, so that one GPU information processing workstation corresponds to the film sensors, the temperature sensors, the humidity sensors and the body parameter sensors on the plurality of wheelchairs, data processing of the plurality of wheelchairs is realized, data of different wheelchairs can be identified by adopting wheelchair ID codes, and unified management is realized.
The controller is used for receiving the control signal and controlling the wheelchair to realize the operation corresponding to the control signal; the controller mainly comprises various control mechanisms and is used for realizing intelligent control of the wheelchair, for example, when a user tends to slide down, the user prompts invalidity after sending an alarm signal to a target terminal, and the front side lifting device is used for stabilizing the posture of the human body and reducing the falling risk of the user.
The display screen is used for displaying the gesture recognized by the GPU information processing workstation and displaying information corresponding to the alarm signal; the device mainly comprises a visual screen and a plurality of prompting devices, and realizes real-time feedback of pressure data, human health parameters and human states.
Fig. 3 is a schematic structural diagram of a terminal 300 according to an embodiment of the present invention, where the terminal 300 may be used to execute a gesture recognition method according to the embodiment of the present invention.
Among them, the terminal 300 may include: a processor 310, a memory 320, and a communication unit 330. The components communicate via one or more buses, and those skilled in the art will appreciate that the architecture of the servers shown in the figures is not intended to be limiting, and may be a bus architecture, a star architecture, a combination of more or less components than those shown, or a different arrangement of components.
The memory 320 may be used for storing instructions executed by the processor 310, and the memory 320 may be implemented by any type of volatile or non-volatile storage terminal or combination thereof, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The executable instructions in memory 320, when executed by processor 310, enable terminal 300 to perform some or all of the steps in the method embodiments described below.
The processor 310 is a control center of the storage terminal, connects various parts of the entire electronic terminal using various interfaces and lines, and performs various functions of the electronic terminal and/or processes data by operating or executing software programs and/or modules stored in the memory 320 and calling data stored in the memory. The processor may be composed of an Integrated Circuit (IC), for example, a single packaged IC, or a plurality of packaged ICs connected with the same or different functions. For example, the processor 310 may include only a Central Processing Unit (CPU). In the embodiment of the present invention, the CPU may be a single operation core, or may include multiple operation cores.
A communication unit 330, configured to establish a communication channel so that the storage terminal can communicate with other terminals. And receiving user data sent by other terminals or sending the user data to other terminals.
The present invention also provides a computer storage medium, wherein the computer storage medium may store a program, and the program may include some or all of the steps in the embodiments provided by the present invention when executed. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM) or a Random Access Memory (RAM).
Thus, the present invention provides for receiving pressure data for at least one wheelchair location; determining the sub-postures corresponding to the wheelchair parts according to the pressure data, and calibrating the sub-postures on the corresponding pressure data; importing the pressure data into a preset gesture recognition model, and determining a target gesture of a user; when the target posture is within the preset dangerous posture range, an alarm signal or a control signal for controlling the wheelchair to realize the target action is sent to the target terminal, so that the problem of unsafe wheelchair use is solved, the user posture on the wheelchair is identified, and a relevant signal is sent out when the user posture is in a dangerous state, so that the safety of the wheelchair user is ensured.
Those skilled in the art will readily appreciate that the techniques of the embodiments of the present invention may be implemented as software plus a required general purpose hardware platform. Based on such understanding, the technical solutions in the embodiments of the present invention may be embodied in the form of a software product, where the computer software product is stored in a storage medium, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and the like, and the storage medium can store program codes, and includes instructions for enabling a computer terminal (which may be a personal computer, a server, or a second terminal, a network terminal, and the like) to perform all or part of the steps of the method in the embodiments of the present invention.
The same and similar parts in the various embodiments in this specification may be referred to each other. Especially, for the terminal embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant points can be referred to the description in the method embodiment.
In the embodiments provided by the present invention, it should be understood that the disclosed system, system and method can be implemented in other ways. For example, the above-described system embodiments are merely illustrative, and for example, the division of the units is only one logical functional division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. 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, systems or units, and may be in an electrical, mechanical or other form.
The 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 invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
Although the present invention has been described in detail by referring to the drawings in connection with the preferred embodiments, the present invention is not limited thereto. Various equivalent modifications or substitutions can be made on the embodiments of the present invention by those skilled in the art without departing from the spirit and scope of the present invention, and these modifications or substitutions are within the scope of the present invention/any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (7)
1. A method of gesture recognition, comprising:
a film sensor for measuring pressure exerted on the wheelchair by the user's body, a temperature sensor for detecting the temperature of the environment in which the wheelchair is located, a humidity sensor for detecting the humidity of the environment in which the wheelchair is located, a body parameter sensor for measuring body parameters of the user, the body parameters comprising: at least one of body temperature, blood pressure, blood oxygen, pulse, heart rate, and respiratory rate; the GPU information processing workstation is used for processing data, identifying the posture of a user on the wheelchair and sending out an alarm signal and a control signal; the controller is used for receiving the control signal and controlling the wheelchair to realize the operation corresponding to the control signal; the display screen is used for displaying the gesture recognized by the GPU information processing workstation and displaying the information corresponding to the alarm signal; the thin film sensor, the temperature sensor, the humidity sensor, the body parameter sensor, the controller and the display screen are in communication connection with the communication module, and the communication module is in communication connection with the GPU information processing workstation; the film sensor and the body parameter sensor are both arranged on the wheelchair;
the GPU information processing workstation processes data, identifies the posture of a user on the wheelchair, and sends out an alarm signal and a control signal, and the method comprises the following steps:
receiving pressure data for at least one wheelchair location; the wheelchair location may include: wheelchair cushion, wheelchair handle and wheelchair back, then pressure data is: cushion pressure from the buttocks of the user borne by the cushion, handle pressure from the hands of the user borne by the handle, and back pressure from the back of the user borne by the back;
determining the sub-postures corresponding to the wheelchair parts according to the pressure data, and calibrating the sub-postures on the corresponding pressure data;
importing the pressure data with the calibrated partial gestures into a preset gesture recognition model, and determining the target gesture of the user;
under the condition that the target posture is within a preset dangerous posture range, sending an alarm signal or a control signal for controlling the wheelchair to realize target action to a target terminal;
the method further comprises the following steps:
recording the target postures of the current user at different time points, generating a trend prediction model of the current user posture, and predicting the trend posture of the current target posture according to the trend prediction model;
and when the trend posture is within the dangerous posture range, sending a control signal to a control terminal of the wheelchair, wherein the control signal comprises: slowly lifting the front part of the cushion, turning the backrest forwards and lifting the height of the handle.
2. The method of claim 1, further comprising:
and carrying out normalization processing on the pressure data according to the individual difference of the user.
3. The method of claim 1, further comprising:
and sending an alarm signal to the target terminal under the condition that the target posture of the user is kept unchanged within a preset time range.
4. The method of claim 1, further comprising:
and recording the change of the target posture of the current user at different time points, and generating a user behavior analysis chart according to the change.
5. A gesture recognition system, comprising:
a film sensor for measuring pressure exerted on the wheelchair by the user's body, a temperature sensor for detecting the temperature of the environment in which the wheelchair is located, a humidity sensor for detecting the humidity of the environment in which the wheelchair is located, a body parameter sensor for measuring body parameters of the user, the body parameters comprising: at least one of body temperature, blood pressure, blood oxygen, pulse, heart rate, and respiratory rate; the GPU information processing workstation is used for processing data, identifying the posture of a user on the wheelchair and sending out an alarm signal and a control signal; the controller is used for receiving the control signal and controlling the wheelchair to realize the operation corresponding to the control signal; the display screen is used for displaying the gesture recognized by the GPU information processing workstation and displaying the information corresponding to the alarm signal; the thin film sensor, the temperature sensor, the humidity sensor, the body parameter sensor, the controller and the display screen are in communication connection with the communication module, and the communication module is in communication connection with the GPU information processing workstation; the film sensor and the body parameter sensor are both arranged on the wheelchair;
the GPU information processing workstation comprises:
a data receiving unit configured to receive pressure data of at least one wheelchair location; the wheelchair location may include: wheelchair cushion, wheelchair handle and wheelchair back, then pressure data is: cushion pressure from the buttocks of the user borne by the cushion, handle pressure from the hands of the user borne by the handle, and back pressure from the back of the user borne by the back;
the data processing unit is configured to determine a sub-posture corresponding to the wheelchair part according to the pressure data and calibrate the sub-posture on the corresponding pressure data;
the gesture determining unit is configured to import the pressure data with the calibrated partial gestures into a preset gesture recognition model and determine a target gesture of the user;
the signal sending unit is configured to send an alarm signal or a control signal for controlling the wheelchair to realize a target action to a target terminal under the condition that the target posture is within a preset dangerous posture range, and the control signal comprises: slowly lifting the front part of the cushion, turning the backrest forwards and lifting the height of the handle.
6. A terminal, comprising:
a processor;
a memory for storing instructions for execution by the processor;
wherein the processor is configured to perform the method of any one of claims 1-4.
7. 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 1-4.
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| JP2008023061A (en) * | 2006-07-20 | 2008-02-07 | Kaigo Brain:Kk | Sitting position retainer |
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| KR102072561B1 (en) * | 2019-06-26 | 2020-03-02 | 신중섭 | Method and system for health care service |
| CN111008671B (en) * | 2019-12-23 | 2023-08-18 | Oppo广东移动通信有限公司 | Gesture recognition method and apparatus, electronic device, and computer-readable storage medium |
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| JP2008023061A (en) * | 2006-07-20 | 2008-02-07 | Kaigo Brain:Kk | Sitting position retainer |
| WO2020045760A1 (en) * | 2018-08-31 | 2020-03-05 | 가톨릭관동대학교산학협력단 | Smart medical wheelchair and monitoring system |
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