CN113877157B - Hand function rehabilitation system combining data glove and VR technology - Google Patents
Hand function rehabilitation system combining data glove and VR technology Download PDFInfo
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B23/00—Exercising apparatus specially adapted for particular parts of the body
- A63B23/035—Exercising apparatus specially adapted for particular parts of the body for limbs, i.e. upper or lower limbs, e.g. simultaneously
- A63B23/12—Exercising apparatus specially adapted for particular parts of the body for limbs, i.e. upper or lower limbs, e.g. simultaneously for upper limbs or related muscles, e.g. chest, upper back or shoulder muscles
- A63B23/16—Exercising apparatus specially adapted for particular parts of the body for limbs, i.e. upper or lower limbs, e.g. simultaneously for upper limbs or related muscles, e.g. chest, upper back or shoulder muscles for hands or fingers
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B71/00—Games or sports accessories not covered in groups A63B1/00 - A63B69/00
- A63B71/06—Indicating or scoring devices for games or players, or for other sports activities
- A63B71/0619—Displays, user interfaces and indicating devices, specially adapted for sport equipment, e.g. display mounted on treadmills
- A63B71/0622—Visual, audio or audio-visual systems for entertaining, instructing or motivating the user
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B71/00—Games or sports accessories not covered in groups A63B1/00 - A63B69/00
- A63B71/06—Indicating or scoring devices for games or players, or for other sports activities
- A63B71/0619—Displays, user interfaces and indicating devices, specially adapted for sport equipment, e.g. display mounted on treadmills
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- A63B2071/0625—Emitting sound, noise or music
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B71/00—Games or sports accessories not covered in groups A63B1/00 - A63B69/00
- A63B71/06—Indicating or scoring devices for games or players, or for other sports activities
- A63B71/0619—Displays, user interfaces and indicating devices, specially adapted for sport equipment, e.g. display mounted on treadmills
- A63B71/0622—Visual, audio or audio-visual systems for entertaining, instructing or motivating the user
- A63B2071/0638—Displaying moving images of recorded environment, e.g. virtual environment
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Abstract
The invention discloses a hand function rehabilitation system combining data glove and VR technology, which comprises an upper computer, a control module, VR glasses (1), a glove body (2) and an evaluation module; the invention meets the requirements of patients in different cerebral apoplexy recovery stages, and with the help of the system, cerebral apoplexy patients can finish the rehabilitation training of the system, thereby greatly improving the training efficiency.
Description
Technical Field
The invention relates to the cerebral apoplexy rehabilitation field and the virtual reality field, in particular to a hand function rehabilitation system combining data glove and VR technology.
Background
With the advent of aging of population in China, cerebral apoplexy is one of the main diseases which endanger the life health and quality of life of the people. The traditional rehabilitation therapy mode is that a therapist assists the patient to recover, the training mode emphasizes single movement, the mode is boring, the efficiency and convenience are low, and the patient is easy to generate boring psychology for recovery. The game of supplementary rehabilitation training can be designed to this patent, utilizes virtual reality technique to render training scene, and reinforcing patient rehabilitation training's authenticity and interest improve rehabilitation training's efficiency.
Most of the existing robots for assisting rehabilitation training at home and abroad are complex in structure, inconvenient to wear and low in usability. The data glove used in the patent has small size and complete structure, and each part can be disassembled, so that the data glove can be adjusted according to the wearing actual conditions and can adapt to the needs of different crowds.
At present, research on robots and intelligent gloves for assisting rehabilitation training at home and abroad does not form a systematic method, and complete rehabilitation training functions are difficult to realize.
Disclosure of Invention
The invention aims to provide a hand function rehabilitation system combining data gloves and VR technology, which comprises an upper computer, a control module, VR glasses, a glove body and an evaluation module.
And the upper computer generates a training scheme according to the user information and sends the training scheme to the control module.
And the upper computer updates the training scheme according to the hand training degree evaluation result and sends the training scheme to the control module.
The process of generating the training scheme by the upper computer according to the user information comprises the following steps:
and the upper computer receives the user information sent by the control module and matches the user information database stored in the upper computer, if the user information is matched with the user information database, a training scheme is generated according to the last training progress, if the user information is not matched with the user information database, a training scheme is generated according to the user information, and the user information is stored in the user information database. And a plurality of user training information sets are stored in the user information database. Each user training information set comprises user information, the last training progress and a hand training degree evaluation result.
The user information includes user name, age, gender, medical history.
The upper computer stores m training schemes. The upper computer selects a training scheme according to the user information or the hand training degree evaluation result and sends the training scheme to the control module. The m training schemes have different hand strength requirements. The training program sequence number is proportional to the hand strength requirement.
And recording the current training scheme as a training scheme t, and selecting the training scheme from the training schemes with the sequence numbers of [1, t-1] by the upper computer when the hand training degree evaluation level is less than h. When the hand training degree evaluation level epsilon [ h, g ] is higher than the hand training degree evaluation level g, the upper computer maintains the current training scheme, and when the hand training degree evaluation level is higher than the hand training degree evaluation level g, the upper computer selects the training scheme from the training schemes with the sequence numbers of [ t+1, m ].
And the control module controls the VR glasses to display the virtual scene according to the training scheme.
The user wears VR glasses and glove bodies, and training gestures are completed in the virtual scene.
Nine-axis inertial sensors and finger bending sensors are attached to the glove body.
The glove body includes a palm portion and a finger portion. The nine-axis inertial sensor is attached to the palm. A plurality of bending sensors are attached to the finger.
The nine-axis inertial sensor and the bending sensor are detachable.
The nine-axis inertial sensor monitors hand displacement, wrist rotation angle and hand residence time and sends the hand displacement, wrist rotation angle and hand residence time to the evaluation module.
The bending sensor monitors the bending degree of different fingers and sends the bending degree to the evaluation module.
The assessment module stores a training assessment model.
The evaluation module inputs all hand displacements, wrist rotation angles, hand residence time and bending degrees of different fingers in one training process into the training evaluation model, evaluates the hand training degree of a user and sends the hand training degree evaluation result to the upper computer.
The step of the evaluation module for evaluating the hand training degree of the user comprises the following steps:
1) The evaluation module recognizes the current gesture of the user according to the hand displacement, the wrist rotation angle, the hand residence time and the bending degree of different fingers, and the current gesture is matched with a standard gesture database stored in the evaluation module to judge the accuracy of the current gesture of the user. The evaluation module stores n hand training degree evaluation grades, and each hand training degree evaluation grade is matched with a gesture average accuracy rate interval.
2) After all training tasks of one training scheme are completed, the evaluation module calculates the average accuracy of all gestures.
3) And the evaluation module is used for matching the average accuracy and the hand training degree evaluation level, so that the hand training degree evaluation level which is successfully matched is used as a hand training degree evaluation result.
The hand function rehabilitation system combining the data glove and the VR technology further comprises a communication module. The nine-axis inertial sensor, the finger bending sensor, the evaluation module and the control model conduct data interaction through the communication module.
The invention has the technical effects that the training task is designed according to the rehabilitation stage of the cerebral apoplexy patient, a training mode which is suitable for individual characteristics is provided, and the function of targeted rehabilitation training is systematically completed.
The invention provides a hand function rehabilitation system combining data gloves and VR technology, which comprises VR glasses, glove bodies, a control module, a communication module and an evaluation module, wherein the gloves are provided with inertial sensors and finger bending sensors, the control module selects game categories and difficulties according to hemiplegia recovery stages of cerebral apoplexy patients, and the evaluation module calculates training subtask scores and comprehensive evaluation. The modules and the instruments are connected by a control module and are managed in a unified way.
The system comprises an auxiliary training game with reality, interestingness and challenge, the virtual reality technology enhances the visual sense of presence, and the system also stimulates the game forward to the patient by adopting the relaxed background music and success/failure prompt tone, thereby enhancing the immersion of training. The game of auxiliary training comprises different checkpoints, and all is that the action in real life migrates to form, provides simple and easy to difficult training task option, selects corresponding training task according to practicality and patient's motion function recovery stage, has practicality and challenging.
The system meets the requirements of patients in different cerebral apoplexy recovery stages, and under the help of the system, cerebral apoplexy patients can complete rehabilitation training of the system, so that training efficiency is greatly improved.
Drawings
FIG. 1 is a block diagram of a hand function rehabilitation system incorporating data glove and VR techniques;
FIG. 2 is a schematic diagram of a training scenario for stroke patients;
FIG. 3 is a diagram of a data glove body;
FIG. 4 is a schematic diagram of 13 basic hand functions of a first stage training;
fig. 5 is a schematic view of a scenario of a second stage of watering training.
Detailed Description
The present invention is further described below with reference to examples, but it should not be construed that the scope of the above subject matter of the present invention is limited to the following examples. Various substitutions and alterations are made according to the ordinary skill and familiar means of the art without departing from the technical spirit of the invention, and all such substitutions and alterations are intended to be included in the scope of the invention.
Example 1:
referring to fig. 1 to 5, a hand function rehabilitation system combining data glove and VR technology comprises an upper computer, a control module, VR glasses 1, a glove body 2 and an evaluation module.
And the upper computer generates a training scheme according to the user information and sends the training scheme to the control module.
And the upper computer updates the training scheme according to the hand training degree evaluation result and sends the training scheme to the control module.
The process of generating the training scheme by the upper computer according to the user information comprises the following steps:
and the upper computer receives the user information sent by the control module and matches the user information database stored in the upper computer, if the user information is matched with the user information database, a training scheme is generated according to the last training progress, if the user information is not matched with the user information database, a training scheme is generated according to the user information, and the user information is stored in the user information database. And a plurality of user training information sets are stored in the user information database. Each user training information set comprises user information, the last training progress and a hand training degree evaluation result.
The user information includes user name, age, gender, medical history.
The upper computer stores m training schemes. The upper computer selects a training scheme according to the user information or the hand training degree evaluation result and sends the training scheme to the control module. The m training schemes have different hand strength requirements. The training program sequence number is proportional to the hand strength requirement.
And recording the current training scheme as a training scheme t, and selecting the training scheme from the training schemes with the sequence numbers of [1, t-1] by the upper computer when the hand training degree evaluation level is less than h. When the hand training degree evaluation level epsilon [ h, g ] is higher than the hand training degree evaluation level g, the upper computer maintains the current training scheme, and when the hand training degree evaluation level is higher than the hand training degree evaluation level g, the upper computer selects the training scheme from the training schemes with the sequence numbers of [ t+1, m ].
In the embodiment, when the hand training degree evaluation level is smaller than h, the upper computer selects a training scheme t-1; when the hand training degree evaluation level epsilon [ h, g ], the upper computer maintains the current training scheme, and when the hand training degree evaluation level > g, the upper computer selects the training scheme t+1.
The control module controls the VR glasses 1 to display the virtual scene according to the training scheme.
The user wears the VR glasses 1 and the glove bodies 2, and training gestures are completed in the virtual scene.
Nine-axis inertial sensors and finger bending sensors are attached to the glove body 2.
The glove body 2 includes a palm portion and a finger portion. The nine-axis inertial sensor is attached to the palm. A plurality of bending sensors are attached to the finger.
The nine-axis inertial sensor and the bending sensor are detachable.
The nine-axis inertial sensor monitors hand displacement, wrist rotation angle and hand residence time and sends the hand displacement, wrist rotation angle and hand residence time to the evaluation module.
The bending sensor monitors the bending degree of different fingers and sends the bending degree to the evaluation module.
The assessment module stores a training assessment model.
The evaluation module inputs all hand displacements, wrist rotation angles, hand residence time and bending degrees of different fingers in one training process into the training evaluation model, evaluates the hand training degree of a user and sends the hand training degree evaluation result to the upper computer.
The step of the evaluation module for evaluating the hand training degree of the user comprises the following steps:
1) The evaluation module recognizes the current gesture of the user according to the hand displacement, the wrist rotation angle, the hand residence time and the bending degree of different fingers, and the current gesture is matched with a standard gesture database stored in the evaluation module to judge the accuracy of the current gesture of the user. The evaluation module stores n hand training degree evaluation grades, and each hand training degree evaluation grade is matched with a gesture average accuracy rate interval.
2) After all training tasks of one training scheme are completed, the evaluation module calculates the average accuracy of all gestures.
3) And the evaluation module is used for matching the average accuracy and the hand training degree evaluation level, so that the hand training degree evaluation level which is successfully matched is used as a hand training degree evaluation result.
The hand function rehabilitation system combining the data glove and the VR technology further comprises a communication module. The nine-axis inertial sensor, the finger bending sensor, the evaluation module and the control model conduct data interaction through the communication module.
Example 2:
the embodiment discloses a hand function rehabilitation system based on combination of data glove and VR, which forms a complete training process of training, evaluating, feeding back and improving four parts. In the system, the data glove is provided with a nine-axis inertial sensor and a finger bending sensor, so that hand motions can be sensed, and hand displacement changes can be tracked. The auxiliary training game developed based on UnityVR can simulate real life scenes, provide basic hand functions and enhance hand function training.
The system consists of four parts including VR glasses, a glove body, a control module, a communication module and an evaluation module, wherein the glove body is provided with a nine-axis inertial sensor and a finger bending sensor, the control module uses a computer to control training content and difficulty and connects and uniformly manages the VR glasses, the glove body, the communication module and the evaluation module, the communication module comprises a Bluetooth-based communication module and a wired serial port communication module, and the evaluation module calculates training scores according to hand data of a patient by using a preset algorithm for doctors to analyze and improve training schemes.
The data glove is provided with a nine-axis inertial sensor and a finger bending sensor, so that hand data of a cerebral apoplexy patient can be tracked in real time, time delay is reduced, and recognition rate is improved. The data glove is detachable and can be adjusted according to the hand characteristics of the patient.
The control module connects the VR glasses, the glove body, the communication module and the evaluation module, and can finish the functions of user login, information input and the like; the type and the difficulty of the auxiliary training game can be selected according to the rehabilitation hemiplegia recovery stage of the cerebral apoplexy patient, the rehabilitation training requirement is met, and the cerebral apoplexy patient is protected from secondary injury.
The evaluation module records hand displacement, wrist rotation angle and hand residence time data in the rehabilitation training process of the cerebral apoplexy patient in real time, calculates training comprehensive scores by using a preset algorithm, and ranks the performance of the cerebral apoplexy patient; the data may be archived for analysis by a physician and for presentation of training improvement advice.
Example 3:
the application method of the hand function rehabilitation system based on the combination of the data glove and the VR comprises the following steps:
1) If the user logs in the rehabilitation training system for the first time, basic information needs to be input, such as: patient name, age, sex, medical history, personal condition description, etc.; if the login is not the first time, the system automatically loads the last training progress, and the doctor/user can also reselect the training progress to finish the login.
2) The first stage is a basic hand function training stage, and at the beginning of training, the VR glasses sequentially display 13 basic rehabilitation gestures shown in fig. 3, and the user wears the data glove and the VR glasses to sequentially complete the designated rehabilitation gestures within a specified time. The data of displacement, rotation angle, residence time and the like acquired by the nine-axis inertial sensor of the hand of the data glove and the bending sensor of the finger are transmitted to an evaluation module through a communication module, and the evaluation module recognizes gestures of a patient based on the existing dynamic gesture recognition algorithm and calculates the action accuracy. The assessment module calculates the patient training score for this stage using a preset algorithm.
3) As shown in fig. 4, the second stage is a training stage for enhancing hand functions, and the training stage is used as a first stage of advanced training and is an auxiliary training planting sapling game with comprehensiveness, practicability and interestingness. Before starting the game, the patient/doctor selects the sub-game category and difficulty according to the score and training requirement of the first stage patient, and the sub-game comprises: 1) grabbing seeds for training, the patient needs to finish finger grabbing actions, and moving arms to move seeds in a certain place to a destination 2) cutting branch for training, the patient needs to finish actions of scissors hands and other specified fingers and stay for a certain time to finish cutting branch tasks 3) watering training, moving a motion track in real life into training, and the patient needs to finish three basic actions of forearm rotation, forearm rotation back and neutral position, so that the purpose of watering is achieved. The difficulty division basis is as follows: wrist bending angle, finger bending angle, arm rest time, time required to complete a task.
3.1 Gripping seeds, and the action basis is a gripping gesture in basic rehabilitation gestures, including spherical gripping, columnar gripping and spherical fingertip gripping. The game starts, the patient grasps the seeds placed in basket a and moves the arm to the morning of designated basket B, rotates the wrist to place the seeds into basket B, and the game fails when fingers are required to be held tightly during the movement, and the fingers are released or the designated basket B is not placed. After training, the computer calculates the training score of the patient according to the game time and the hand displacement recorded by the sensor.
3.2 Training the cutting branch, wherein the action basis is lateral pinching and dynamic operation in basic rehabilitation gestures. The game is started, the patient needs to finish the lateral pinching gesture to obtain scissors placed on the table, then the patient performs dynamic operations such as opening and closing of two fingers, hooking and pulling and the like to achieve the aim of cutting branches, training is finished when the branches are cut within a specified time, and the computer calculates a training score of the patient according to the game time and the task completion rate.
3.3 Training water, the sub-game integrates the games. The game trains the forearm joint action of the patient, including forearm pronation, forearm supination and neutral position, and the patient can quickly transfer the motion trail in the game to real life. Starting the game, a plurality of plants with different growth periods appear in the VR glasses of the patient, and the kettle is placed on a table and initialized to be full of water. The patient carries out the action of holding the kettle and the rotation action of the forearm, the sensor in the data glove enables the kettle to be synchronous with the action of the forearm of the patient, the kettle starts to discharge water after rotating for a certain angle, and the patient can complete the watering task once after keeping the action for a certain time. The water amount (i.e. the maintenance action time) and the rotation angle required by the plant can be displayed above different plants, and the patient can finish the game after completing the watering task of all plants. The doctor can set the water required by different plants and the rotation angle so as to change the game difficulty, and after the game is finished, the computer calculates the training score according to the rotation angle of the arms of the patient, the residence time and the number of the plants for further analysis.
4) And in the evaluation stage, after the patient finishes all training tasks preset by the system, the evaluation module takes the scores of all subtasks as input, and calculates the total score of the complete training of the patient through a preset algorithm to form comprehensive evaluation. The rehabilitation system finally presents the time, score and comprehensive evaluation of each subtask to a doctor through a data visualization means, and files all data of the training so as to enable the doctor to improve the rehabilitation training scheme of the next stage.
Claims (6)
1. The hand function rehabilitation system combining the data glove and the VR technology is characterized by comprising an upper computer, a control module, VR glasses (1), a glove body (2) and an evaluation module;
the upper computer generates a training scheme according to the user information and sends the training scheme to the control module;
the upper computer updates a training scheme according to the hand training degree evaluation result and sends the training scheme to the control module;
the control module controls the VR glasses (1) to display the virtual scene according to the training scheme;
the user wears VR glasses (1) and glove bodies (2), and training gestures are completed in a virtual scene;
nine-axis inertial sensors and finger bending sensors are attached to the glove body (2);
the nine-axis inertial sensor monitors hand displacement, wrist rotation angle and hand residence time and sends the hand displacement, wrist rotation angle and hand residence time to the evaluation module;
the bending sensor monitors the bending degree of different fingers and sends the bending degree to the evaluation module;
the evaluation module stores a training evaluation model;
the evaluation module inputs all hand displacement, wrist rotation angle, hand residence time and bending degrees of different fingers in one training process into a training evaluation model, evaluates the hand training degree of a user and sends a hand training degree evaluation result to the upper computer;
the upper computer stores m training schemes; the upper computer selects a training scheme according to user information or hand training degree evaluation results and sends the training scheme to the control module; the m training schemes have different requirements on hand strength; the training scheme sequence number is in direct proportion to the hand strength requirement degree;
the step of the evaluation module for evaluating the hand training degree of the user comprises the following steps:
1) The evaluation module recognizes the current gesture of the user according to the hand displacement, the wrist rotation angle, the hand residence time and the bending degree of different fingers, and the current gesture is matched with a standard gesture database stored in the evaluation module to judge the accuracy of the current gesture of the user; the evaluation module stores n hand training degree evaluation grades, and each hand training degree evaluation grade is matched with a gesture average accuracy rate interval;
2) After all training tasks of one training scheme are completed, the evaluation module calculates the average accuracy of all gestures;
3) The evaluation module is used for matching the average accuracy and the hand training degree evaluation level, and the hand training degree evaluation level which is successfully matched is used as a hand training degree evaluation result;
recording the current training scheme as a training scheme t, and selecting the training scheme from the training schemes with the sequence numbers of [1, t-1] by the upper computer when the hand training degree evaluation level is less than h; when the hand training degree evaluation level epsilon [ h, g ] is higher than the hand training degree evaluation level g, the upper computer maintains the current training scheme, and when the hand training degree evaluation level is higher than the hand training degree evaluation level g, the upper computer selects the training scheme from the training schemes with the sequence numbers of [ t+1, m ].
2. The hand function rehabilitation system combining data glove and VR technology of claim 1, wherein: the glove body (2) comprises a palm part and a finger part; the nine-axis inertial sensor is attached to the palm part; a plurality of bending sensors are attached to the finger.
3. The hand function rehabilitation system combining data glove and VR technology of claim 2, wherein: the nine-axis inertial sensor and the bending sensor are detachable.
4. The hand function rehabilitation system combining data glove and VR technology of claim 1, wherein: the communication module is also included; the nine-axis inertial sensor, the finger bending sensor, the evaluation module and the control model conduct data interaction through the communication module.
5. The hand function rehabilitation system combining data glove and VR technology of claim 1, wherein: the process of generating the training scheme by the upper computer according to the user information comprises the following steps:
the upper computer receives the user information sent by the control module and matches the user information database stored in the upper computer, if the user information is matched with the user information database, a training scheme is generated according to the last training progress, if the user information is not matched with the user information database, a training scheme is generated according to the user information, and the user information is stored in the user information database; storing a plurality of user training information sets in the user information database; each user training information set comprises user information, the last training progress and a hand training degree evaluation result.
6. The hand function rehabilitation system combining data glove and VR technology of claim 1, wherein: the user information includes user name, age, gender, medical history.
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