VR-based audio-video-touch sense multi-mode hand function rehabilitation training method

A multi-modal, hand-functional technology, applied in the direction of mechanical mode conversion, input/output process of data processing, input/output of user/computer interaction, etc., can solve the problem of long training time, low recovery efficiency, and difficulty in mobilizing patients Training enthusiasm and other issues to achieve the effect of improving the rehabilitation process and enhancing training enthusiasm

Pending Publication Date: 2018-08-17
SHANGHAI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the traditional therapy takes a long time to train, the effect is slow, and the process is boring. It is difficult to mobilize the enthusiasm of patients for training, so the recovery efficiency is not high.

Method used

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  • VR-based audio-video-touch sense multi-mode hand function rehabilitation training method
  • VR-based audio-video-touch sense multi-mode hand function rehabilitation training method
  • VR-based audio-video-touch sense multi-mode hand function rehabilitation training method

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Experimental program
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Effect test

Embodiment 1

[0038] see Figure 1-7 This VR-based audio-visual and tactile multimodal hand function rehabilitation training method adopts an EEG signal acquisition and processing system composed of users, electrode caps and signal amplifiers and a computer-based virtual reality multimodal feedback training system for training. Its characteristics In that: the hand function rehabilitation method comprises the following four steps:

[0039] (1) Acquisition and processing of EEG signals: use the electrode cap to collect the EEG signal of the user, after preprocessing, use the common space mode CSP algorithm to extract the features of the collected signal;

[0040] (2) Training scene selection interface design: In order to avoid the rehabilitation training environment being too single, this system designed three training scenes of indoor, beach and tennis court, and completed the grasping and comparison with six different 3D virtual human models. There are three clinical rehabilitation traini...

Embodiment 2

[0043] Embodiment 2: This embodiment is basically the same as Embodiment 1, and the special features are as follows:

[0044] A virtual reality multi-modal feedback training system based on EEG has been built, which can receive brain motor imagination intentions, and through audio-visual and tactile multi-modal feedback, it can carry out personalized hand function active and immersive rehabilitation training. Its specific functions are:

[0045] (1) Realization of the communication function of receiving brain intentions: each device relies on the TCP / IP communication protocol to realize the function of transmitting information; when performing rehabilitation training, the user must wear an electrode cap or other EEG signal acquisition device in advance, and when performing motor imagination Collect its EEG signal, analyze and process the motion intention, and send it to the training system in real time using the TCP / IP protocol, and cooperate with the Unity control command to j...

Embodiment 3

[0049] see figure 1 and figure 2 , the operation of this VR-based audition tactile multimodal hand function rehabilitation training method includes the following steps:

[0050] (1) Users should wear electrode caps and related EEG signal acquisition devices in advance during rehabilitation training;

[0051] (2) When starting training, first enter the training scene selection interface of the system (see Figure 7 ), the user independently selects the training scene and the trained 3D virtual human model, and clicks to enter the training scene;

[0052] (3) Carry out motor imagery according to the prompts, and the user collects EEG signals through motor imagery;

[0053] (4) The system performs signal processing on the collected EEG signals, feature extraction and feature recognition to convert them into control commands that the system can recognize;

[0054] (5) The identified EEG signal is processed and sent to the training system in real time using the TCP / IP protocol...

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Abstract

The invention relates to a VR-based audio-video-touch sense multi-mode hand function rehabilitation training method. The employed system is composed of a user and electroencephalogram signal acquisition and processing system and a virtual reality multi-mode feedback training system. The user and electroencephalogram signal acquisition and processing system collects a brain wave signal of a user inreal time, carries out filter preprocessing on the signal, carries out feature extraction by using a common space mode algorithm, analyzes whether the user has a motion imagination intention, and transmits a classification result to the virtual reality multi-mode feedback training system by TCP / IP communication. The virtual reality multi-mode feedback training system is used for designing a VR training scene and realizing audio-video-touch sense multi-mode feedback. Besides, during the training, background music can be selected; and with an electric stimulator, a touch feeling is formed and thus audio-video-touch sense multi-mode feedback is realized.

Description

technical field [0001] In this paper, a VR-based audiovisual and tactile multimodal hand function rehabilitation training method is designed for hand dysfunction caused by stroke. . It can be combined with brain-computer interface technology to promote the remodeling of the central nervous system and provide a new training mode for hand function rehabilitation. Background technique [0002] Stroke is a disease of cerebral blood circulation disorder. It is a frequently-occurring and common disease. In recent years, the incidence rate has been increasing every year, and the incidence of stroke is becoming younger. It has become an important factor causing upper limb motor dysfunction in patients. The clinical manifestations of patients with impaired upper limb function are difficulty in hand joint movement and loss of motion perception feedback function, resulting in the inability of the patient to complete fine hand motor functions such as grasping and finger alignment, and ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H20/30G06F3/01
CPCG06F3/013G06F3/015G06F2203/011G16H20/30
Inventor 杨帮华王伟李博胡晨潇汪金龙
Owner SHANGHAI UNIV
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