An upper limb rehabilitation training system based on virtual reality

Abstract

The present invention relates to an upper limb rehabilitation training system based on virtual reality, and relates to the field of medical rehabilitation, and includes: an upper limb motion data acquisition module, a target mode selection module, a motion posture generation module, and a motion posture display module; the target mode selection module is used to select an upper limb teaching action mode from a plurality of preset upper limb teaching action modes as a target mode; the upper limb motion data acquisition module is used to collect the upper limb motion data of a trainee, and send the collected upper limb motion data to the motion posture generation module; the motion posture generation module is used to generate the motion posture of the trainee according to the upper limb motion data; the motion posture display module is used to display the upper limb teaching action corresponding to the target mode, and the motion posture display module is also used to virtually display the upper limb action of the trainee according to the motion posture of the trainee, and synchronously display the upper limb teaching action corresponding to the target mode. The present invention reduces the cost of rehabilitation training.

Description

Technical Field

[0001] The present invention relates to the field of medical rehabilitation technology, and in particular to an upper limb rehabilitation training system based on virtual reality. Background Art

[0002] Stroke is a common cerebrovascular disease with high incidence, high recurrence rate and high disability rate. In China, there are up to 2 million new stroke patients each year, with a mortality rate of 20% and a disability rate of over 70%. Motor dysfunction is one of the sequelae of most stroke patients, which greatly affects the quality of life of patients and also brings a heavy burden to society. Rehabilitation therapy can promote the reorganization of brain function, stimulate the remaining brain cells to replace the damaged cells to perform functions, and enable patients to obtain maximum functional improvement and self-care ability.

[0003] Traditional upper limb rehabilitation training methods for stroke patients, such as neurodevelopmental therapy, motor relearning, proprioceptive neuromuscular facilitation technology, etc., have problems such as high repetitiveness, low patient compliance with rehabilitation plans, and efficacy limited by the level of therapists, making it difficult to meet existing rehabilitation needs.

[0004] The rise of virtual reality technology has provided a new way for upper limb functional rehabilitation of stroke patients. However, the existing upper limb rehabilitation treatment programs based on virtual reality lack a complete set of training and teaching models and a unified upper limb rehabilitation exercise evaluation system, resulting in different rehabilitation effects of different training programs, which is not conducive to the development of related research. Summary of the invention

[0005] The purpose of the present invention is to provide an upper limb rehabilitation training system based on virtual reality, which reduces the cost of rehabilitation training.

[0006] To achieve the above object, the present invention provides the following solutions:

[0007] A virtual reality-based upper limb rehabilitation training system, comprising: an action library, an upper limb rehabilitation mode selection module, a first motion posture generation module, a second motion posture generation module, an upper limb motion data acquisition module and a motion posture display module; the action library is connected to the upper limb rehabilitation mode selection module, the first motion posture generation module is respectively connected to the upper limb rehabilitation mode selection module and the motion posture display module, the upper limb motion data acquisition module is connected to the second motion posture generation module, and the second motion posture generation module is connected to the motion posture display module;

[0008] The action library is used to store multiple upper limb teaching actions and upper limb action parameters corresponding to each of the upper limb teaching actions;

[0009] The upper limb rehabilitation mode selection module is used to select an upper limb teaching action from the action library as a target training upper limb teaching action;

[0010] The first motion posture generation module is used to generate an upper limb motion posture of the teaching doctor model according to the upper limb motion parameters corresponding to the target training upper limb teaching motion;

[0011] The upper limb motion data acquisition module is used to collect the upper limb motion data of the trainee, and send the collected upper limb motion data to the second motion posture generation module;

[0012] The second motion posture generating module is used to generate the upper limb motion posture of the training personnel model according to the upper limb motion data;

[0013] The movement posture display module is used to display the upper limb movement posture of the teaching doctor model based on virtual reality according to the upper limb teaching action selected by the upper limb rehabilitation mode selection module. The movement posture display module is also used to overlap the upper limb movement posture of the teaching doctor model when displaying the upper limb movement posture of the trainer model based on virtual reality. The trainer model and the teaching doctor model are both virtual human body models.

[0014] Optionally, the movement posture display module is also used to display the teaching doctor model and the training staff model in different colors when the upper limb movement posture of the training staff model and the upper limb movement posture of the teaching doctor model are displayed overlappingly.

[0015] Optionally, the upper limb motion parameters include shoulder joint motion parameters, elbow joint motion parameters and wrist joint motion parameters, the shoulder joint motion parameters include shoulder flexion angle, shoulder extension angle, shoulder abduction angle, shoulder internal rotation angle and shoulder external rotation angle, the elbow joint motion parameters include elbow flexion and extension angle, elbow pronation angle and elbow supination angle, and the wrist joint motion parameters include wrist extension angle, wrist flexion angle, wrist ulnar deviation angle and wrist radial deviation angle.

[0016] Optionally, the motion posture display module is further used to display the upper limb movement parameters of the trainee according to the upper limb motion data collected by the upper limb motion data collection module;

[0017] The movement posture display module is also used to display the upper limb movement parameters corresponding to the target training upper limb teaching movement.

[0018] Optionally, it also includes an action parameter adjustment module, which is connected to the action library and is used to input upper limb teaching actions, add upper limb action parameters corresponding to each upper limb teaching action, and modify the upper limb action parameters corresponding to each upper limb teaching action.

[0019] Optionally, the movement posture display module is also used to store the virtual display process of the trainee's upper limb movements and the trainee's upper limb movement parameters.

[0020] Optionally, the upper limb rehabilitation mode selection module, the first movement posture generation module, the second movement posture generation module and the movement posture display module are deployed in a computer or a mobile phone.

[0021] Optionally, the upper limb motion data acquisition module includes three inertial navigation sensors, and one inertial navigation sensor is respectively arranged at the wrist joint, elbow joint and shoulder joint of the trainee's upper limb, each inertial navigation sensor corresponds to a physical address, and each inertial navigation sensor sends the collected upper limb motion data to the first motion posture generation module via Bluetooth.

[0022] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0023] The present invention discloses an upper limb rehabilitation training system based on virtual reality, which realizes the visualization display of the upper limb motor ability of the trainee by overlappingly displaying the upper limb movements of the trainee and the upper limb teaching movements of a teaching doctor model through a motion posture display module, and evaluates the upper limb motor ability of the trainee through multiple upper limb teaching movement patterns, thereby reducing the cost of rehabilitation training. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0025] Figure 1 It is a structural schematic diagram of an upper limb rehabilitation training system based on virtual reality of the present invention;

[0026] Figure 2 A schematic diagram of the position of the inertial navigation sensor worn by the trainee on the upper limbs of the present invention;

[0027] Figure 3 A schematic diagram showing overlapping display of a virtual doctor and a trainer of the present invention;

[0028] Explanation of symbols:

[0029] 1-shoulder joint sensor wearing position, 2-elbow joint sensor wearing position, 3-wrist joint sensor wearing position. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] The purpose of the present invention is to provide an upper limb rehabilitation training system based on virtual reality, which reduces the cost of rehabilitation training.

[0032] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0033] Figure 1 FIG. 1 is a schematic diagram of the structure of the upper limb rehabilitation training system based on virtual reality of the present invention. Figure 1 As shown, a virtual reality-based upper limb rehabilitation training system includes: an action library 101, an upper limb rehabilitation mode selection module 102, a first motion posture generation module 103, a second motion posture generation module 105, an upper limb motion data acquisition module 104 and a motion posture display module 106; the action library 101 is connected to the upper limb rehabilitation mode selection module 102, the first motion posture generation module 103 is respectively connected to the upper limb rehabilitation mode selection module 102 and the motion posture display module 106, the upper limb motion data acquisition module 104 is connected to the second motion posture generation module 105, and the second motion posture generation module 105 is connected to the motion posture display module 106.

[0034] The action library 101 is used to store multiple upper limb teaching actions and upper limb action parameters corresponding to each of the upper limb teaching actions.

[0035] The upper limb rehabilitation mode selection module 102 is used to select an upper limb teaching action from the action library 101 as a target training upper limb teaching action.

[0036] The first motion posture generating module 103 is used to generate the upper limb motion posture of the teaching doctor model according to the upper limb motion parameters corresponding to the target training upper limb teaching motion.

[0037] The upper limb motion data acquisition module 104 is used to acquire the upper limb motion data of the trainee, and send the acquired upper limb motion data to the second motion posture generation module 105 .

[0038] The second motion posture generating module 105 is used to generate the upper limb motion posture of the training person model according to the upper limb motion data.

[0039] The movement posture display module 106 is used to display the upper limb movement posture of the teaching doctor model based on virtual reality according to the upper limb teaching action selected by the upper limb rehabilitation mode selection module 102. The movement posture display module 106 is also used to overlap the upper limb movement posture of the teaching doctor model when displaying the upper limb movement posture of the trainer model based on virtual reality. The trainer model and the teaching doctor model are both virtual human models. Figure 3 shown.

[0040] The motion posture display module 106 is used to virtually display the upper limb movements of the trainee. The motion posture display module 106 realizes the motion display of the virtual person model in the three-dimensional motion space.

[0041] As a specific implementation, the motion posture display module 106 includes a display screen, which includes an upper limb teaching movement selection button. The upper limb teaching movements include shoulder extension 20°, natural drooping of the shoulder joint, shoulder extension 30°, shoulder external rotation abduction 25°, shoulder external rotation abduction 50°, shoulder external rotation abduction 70°, elbow horizontal flexion 30°, elbow horizontal flexion 60°, elbow horizontal flexion 90°, elbow horizontal flexion 90° and wrist extension 42°, elbow horizontal flexion 90° and wrist remains horizontal, elbow horizontal flexion 90° and wrist flexion 42°, elbow horizontal flexion 90° and lift 30°, and elbow horizontal flexion 90° and swing 30°.

[0042] The motion posture display module 106 is also used for displaying the upper limb motion posture of the training personnel model and the upper limb motion posture of the teaching doctor model when they overlap and display. Figure 3 As shown, the teaching doctor model and the training staff model are displayed in different colors.

[0043] The upper limb motion parameters include data of joint angles, specifically shoulder joint motion parameters, elbow joint motion parameters and wrist joint motion parameters. The shoulder joint motion parameters include shoulder flexion angle, shoulder extension angle, shoulder abduction angle, shoulder internal rotation angle and shoulder external rotation angle. The elbow joint motion parameters include elbow flexion and extension angle, elbow pronation angle and elbow supination angle. The wrist joint motion parameters include wrist extension angle, wrist flexion angle, wrist ulnar deviation angle and wrist radial deviation angle.

[0044] Shoulder flexion angle range is 0-180°, shoulder extension angle range is 0-50°, shoulder abduction angle range is 0-180°, shoulder internal rotation angle range is 0-90°, shoulder external rotation angle range is 0-90°, elbow flexion and extension angle range is 0-150°, elbow pronation angle range is 0-90°, elbow supination angle range is 0-90°, wrist extension angle range is 0-70°, wrist flexion angle range is 0-90°, wrist ulnar deviation angle range is 0-55°, and wrist radial deviation angle range is 0-55°.

[0045] The motion posture display module 106 is further used to display the upper limb movement parameters of the trainee according to the upper limb motion data collected by the upper limb motion data collection module 104 .

[0046] The movement posture display module 106 is also used to display the upper limb movement parameters corresponding to the target training upper limb teaching movement.

[0047] An upper limb rehabilitation training system based on virtual reality also includes a motion parameter adjustment module, which is connected to the motion library 101. The motion parameter adjustment module is used to input upper limb teaching movements, add upper limb movement parameters corresponding to each upper limb teaching movement, and modify the upper limb movement parameters corresponding to each upper limb teaching movement.

[0048] The motion posture display module 106 is also used to store the virtual display process of the trainee's upper limb movements and the trainee's upper limb movement parameters. The rehabilitation training data stored in the motion posture display module 106 is sent to the cloud platform in real time, and the doctor can access it at any time to understand the patient's rehabilitation effect.

[0049] The upper limb rehabilitation mode selection module 102, the first movement posture generation module 103, the second movement posture generation module 105 and the movement posture display module 106 are deployed in a computer or a mobile phone.

[0050] The upper limb motion data acquisition module 104 includes three inertial navigation sensors, Figure 2 The shoulder joint sensor wearing position 1, the elbow joint sensor wearing position 2 and the wrist joint sensor wearing position 3 are shown. Figure 2 As shown, an inertial navigation sensor is respectively arranged at the wrist joint, elbow joint and shoulder joint of the trainee's upper limb. The reference measurement axis directions of each inertial navigation sensor on an arm point to the same direction and are on the same straight line when the arm is straightened. Each inertial navigation sensor corresponds to a physical address, and each inertial navigation sensor sends the collected upper limb motion data to the first motion posture generation module 103 via Bluetooth.

[0051] Each of the inertial navigation sensors corresponds to a physical address (Media Access Control Address, MAC), which is used to distinguish the inertial navigation sensors. Each of the inertial navigation sensors sends the collected motion data to the motion posture generation module via Bluetooth. The human posture is solved for the incoming inertial navigation sensor data through the virtual personnel model on the personal computer (PC) side; and different application scenarios are set for different sensor control modes on the PC side, so that users can choose different virtual human body mapping scenarios and control modes. Connect the inertial navigation sensors according to different MAC addresses to obtain motion data.

[0052] The present invention provides a wearable inertial navigation sensor wearing method, wherein the inertial navigation sensor is located on a wristband, and the wristband is used to fix the inertial navigation sensor on a wrist joint, an elbow joint and a shoulder joint. The wristband adopts medical-grade silicone. Due to the elasticity of silicone, the wristband can be well fixed whether it is worn on a bare arm or outside a sleeve, so that the reference measurement axes of the three inertial navigation sensors are consistent, which is convenient for subsequent modeling and ensures the accuracy of the calculated angle data between joints.

[0053] The use process of the upper limb rehabilitation training system based on virtual reality by a trainer according to the present invention includes:

[0054] The wearable positioning sensor is fixed on the shoulder joint, elbow joint and wrist joint of the upper limb of the human body through a strap.

[0055] The computer is connected via the Bluetooth MAC address of the wearable positioning sensor to initialize the internal data of the wearable positioning sensor.

[0056] Select one of multiple upper limb teaching movements as the target upper limb teaching movement for training, and change the arm posture of the teaching model through the built-in data.

[0057] According to the corresponding rehabilitation action (target training upper limb teaching action) in the mode selected by the trainee, the computer processes the collected trainee motion data and maps the trainee's upper limb motion state to the virtual scene. The trainee follows the teaching doctor model to move, and the computer obtains the posture data at multiple joint positions accordingly. The received posture data is analyzed and processed to obtain the motion posture vectors at the shoulder joint, elbow joint and wrist joint. Finally, in the program, the corresponding sensor analysis data is assigned to the variables on each joint of the virtual arm model to achieve synchronous movement of the virtual arm and the sensor.

[0058] The differences in movements between the user's arm model and the teaching doctor in the virtual scene are demonstrated to the trainees, who then adjust their movements on their own.

[0059] The trainee's joint angle data (upper limb movement parameters) are compared with the standard joint angle data to evaluate the quality of the rehabilitation exercises performed by the trainee.

[0060] The upper limb rehabilitation training system based on virtual reality of the present invention also includes a scoring module, which is used to calculate the angle error between the joint angle of the trainer model and the standard joint angle corresponding to the teaching doctor model, divide each angle error by a set threshold to obtain a score for each joint angle, and multiply the score of each joint angle by the weight of each joint angle to obtain a final score. The rehabilitation effect of the trainee is evaluated by the final score.

[0061] The present invention realizes an upper limb rehabilitation training auxiliary system based on virtual reality through an inertial navigation sensor and an application in a personal computer or a mobile phone, so that the person to be rehabilitated can perform rehabilitation training at home, and the degree of rehabilitation can be evaluated by comparing the virtual display of the upper limb movements of the trainee and the upper limb teaching movements. Based on the upper limb rehabilitation training auxiliary system based on virtual reality of the present invention, the trainee does not need a nursing staff to follow during rehabilitation training, the personnel interference during rehabilitation training is small, and the space occupied is small, which reduces the cost of rehabilitation training.

[0062] In addition, the present invention enables users to analyze their body movement functions by themselves using mobile phones or computers, and to discover their upper limb movement abilities as early as possible. Users can make different upper limb movement postures based on the virtual reality upper limb rehabilitation training system of the present invention, and compare them with the preset upper limb teaching movements, so as to more intuitively evaluate their upper limb joint mobility, with a better human-computer interaction interface, making the overall effect visual.

[0063] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0064] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. An upper limb rehabilitation training system based on virtual reality, characterized in that: include: An action library, an upper limb rehabilitation mode selection module, a first motion posture generation module, a second motion posture generation module, an upper limb motion data acquisition module and a motion posture display module; the action library is connected to the upper limb rehabilitation mode selection module, the first motion posture generation module is respectively connected to the upper limb rehabilitation mode selection module and the motion posture display module, the upper limb motion data acquisition module is connected to the second motion posture generation module, and the second motion posture generation module is connected to the motion posture display module; The action library is used to store multiple upper limb teaching actions and upper limb action parameters corresponding to each of the upper limb teaching actions; The upper limb rehabilitation mode selection module is used to select an upper limb teaching action from the action library as a target training upper limb teaching action; The first motion posture generation module is used to generate an upper limb motion posture of the teaching doctor model according to the upper limb motion parameters corresponding to the target training upper limb teaching motion; The upper limb motion data acquisition module is used to collect the upper limb motion data of the trainee, and send the collected upper limb motion data to the second motion posture generation module; The second motion posture generating module is used to generate the upper limb motion posture of the training personnel model according to the upper limb motion data; The motion posture display module is used to display the upper limb motion posture of the teaching doctor model based on virtual reality according to the upper limb teaching action selected by the upper limb rehabilitation mode selection module. The motion posture display module is also used to overlap and display the upper limb motion posture of the teaching doctor model when displaying the upper limb motion posture of the trainer model based on virtual reality. Both the trainer model and the teaching doctor model are virtual human models. An upper limb rehabilitation training system based on virtual reality also includes a scoring module, which is used to calculate the angle error between the joint angle of the trainer model and the standard joint angle corresponding to the teaching doctor model, divide each angle error by a set threshold to obtain a score for each joint angle, multiply the score of each joint angle by the weight of each joint angle to obtain a final score; and evaluate the rehabilitation effect of the trainer through the final score; The upper limb movement parameters include angle data of each joint; The upper limb rehabilitation training system based on virtual reality also includes an action parameter adjustment module, which is connected to the action library and is used to input upper limb teaching actions, add upper limb action parameters corresponding to each upper limb teaching action, and modify the upper limb action parameters corresponding to each upper limb teaching action; The upper limb motion data acquisition module includes three inertial navigation sensors, one of which is respectively arranged at the wrist joint, elbow joint and shoulder joint of the trainee's upper limb, each of which corresponds to a physical address, and each of which sends the collected upper limb motion data to the second motion posture generation module via Bluetooth; The motion posture display module is also used to display the upper limb movement parameters of the trainee according to the upper limb motion data collected by the upper limb motion data collection module; The movement posture display module is also used to display the upper limb movement parameters corresponding to the target training upper limb teaching movement.

2. The upper limb rehabilitation training system based on virtual reality according to claim 1, characterized in that: The movement posture display module is also used to display the teaching doctor model and the training personnel model in different colors when the upper limb movement posture of the training personnel model and the upper limb movement posture of the teaching doctor model are displayed overlappingly.

3. The upper limb rehabilitation training system based on virtual reality according to claim 1, characterized in that: Each joint angle data includes shoulder joint motion parameters, elbow joint motion parameters and wrist joint motion parameters. The shoulder joint motion parameters include shoulder flexion angle, shoulder extension angle, shoulder abduction angle, shoulder internal rotation angle and shoulder external rotation angle. The elbow joint motion parameters include elbow flexion and extension angle, elbow pronation angle and elbow supination angle. The wrist joint motion parameters include wrist extension angle, wrist flexion angle, wrist ulnar deviation angle and wrist radial deviation angle.

4. The upper limb rehabilitation training system based on virtual reality according to claim 1, characterized in that: The motion posture display module is also used to store the virtual display process of the trainee's upper limb movements and the trainee's upper limb movement parameters.

5. The upper limb rehabilitation training system based on virtual reality according to claim 1, characterized in that: The upper limb rehabilitation mode selection module, the first movement posture generation module, the second movement posture generation module and the movement posture display module are deployed in a computer or a mobile phone.

Images