Movement imagery brain-computer interface-based hand function rehabilitation method

A technology of motor imagery and rehabilitation methods, applied in the input/output of user/computer interaction, computer components, mechanical mode conversion, etc., can solve the problems of lack of interesting patient active participation, family and social burden, and large manpower. Achieve the effect of improving training enthusiasm and fun, conducive to remodeling, and high safety

Inactive Publication Date: 2017-02-01
SHANGHAI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

According to reports, more than 48% of patients still have hand dysfunction after entering the chronic phase and cannot live independently, causing a heavy burden to the family and society
The current hand function rehabilitation methods, such as cold therapy, electrical stimulation therapy, rehabilitation robots, and exercise therapy and occupational therapy relying on therapists, not only consume a lot of manpower, but lack interest and active participation of patients. The direct participation of the motor nervous system in the brain makes the repair of the functional control connection between the external limbs and the brain limited, and the rehabilitation effect is not satisfactory

Method used

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  • Movement imagery brain-computer interface-based hand function rehabilitation method
  • Movement imagery brain-computer interface-based hand function rehabilitation method
  • Movement imagery brain-computer interface-based hand function rehabilitation method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0030] see figure 1 , the hand function rehabilitation method based on motor imagery brain-computer interface, including the following steps:

[0031] (1) Offline training: The patient performs offline training. After the training, the EEG signals collected during the motor imagery period of the left and right hands of the patient are established for the first recognition model and provided for update training;

[0032] (2) Update training: The patient performs update training, analyzes the EEG signals during the motor imagination of the patient's left and right hands according to the first recognition model, presents the hand movement video, and feeds back to the patient to generate more recognizable EEG signals. After the training, the collected Create an updated recognition model based on the EEG signal and provide it for virtual reality online training;

[0033] (3) Virtual reality online training: the patient imagines the movement of the left and right hands, analyzes th...

Embodiment 2

[0035] Embodiment 2: This embodiment is basically the same as Embodiment 1, and the special features are as follows:

[0036] see image 3 , the single training process of offline training in step (1) is as follows:

[0037] (1-1) A black screen appears for 2s, prompting the patient to rest;

[0038] (1-2) 2s random left or right hand action video presentation, prompting patients to get ready and guiding motor imagery actions;

[0039] (1-3) Arrows in the same direction as the left and right hands in the video are presented in 4s. The left arrow represents the motor imagination of the left hand, and the right arrow represents the motor imagination of the right hand. The patient performs the corresponding motor imagination task according to the arrow prompts.

[0040] see Figure 4 , the single training process of the update training in the step (2) is as follows:

[0041] (2-1) 2s black appears, prompting the patient to rest;

[0042] (2-2) Random left / right arrow present...

Embodiment 3

[0044] Embodiment three: this embodiment is basically the same as embodiment two, and the special features are as follows:

[0045] see Figure 5 , the interface diagram of hand function rehabilitation method based on motor imagery brain-computer interface, including offline training interface diagram (1), update training interface diagram (2), virtual reality online training interface diagram (3), the specific operation steps are as follows:

[0046] see Figure 6 , the specific operation steps of offline training are as follows:

[0047] 1) Parameter setting: set the IP address, port number and training time of the TCP / IP protocol in interface (1);

[0048] 2) Communication connection: click the "Start Monitoring" button, and the offline training subsystem will monitor the connection of the signal acquisition-processing system;

[0049] 3) Offline training: Click the "Start Timing" button to start offline training, and control the acquisition of EEG signals by the signal ...

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Abstract

The invention relates to a movement imagery brain-computer interface-based hand function rehabilitation method. The method comprises the following steps of (1) performing offline training: performing the offline training on a patient, and after the training is finished, building a first-time identification model by an acquired electroencephalogram signal during a left and right hand movement imagery period of the patient; (2) performing update training: performing the update training on the patient, analyzing the electroencephalogram signal during the left and right hand movement imagery period of the patient according to the first-time identification model, presenting a hand action video, feeding back the hand action video to the patient, generating an electroencephalogram signal easier to identify, and after the training is finished, building an update identification model by the acquired electroencephalogram signal; and (3) performing virtual reality online training: performing left and right hand movement imagery of the patient, analyzing the electroencephalogram signal of the patient according to the update identification model, and controlling a left and right hand movement of a 3D character in real time. The method has the characteristics of high safety, manpower saving, interestingness and multiple levels. The method can serve as a hand function rehabilitation method for cerebral stroke patients, is simple in operation, and lays a foundation for family-mode training.

Description

technical field [0001] The invention relates to a hand function rehabilitation method based on a motor imagery brain-computer interface, which can provide offline training, update training and virtual reality online training for the hand function rehabilitation of stroke patients. It has the characteristics of high safety, saving manpower, fun and multi-level. Background technique [0002] Stroke is listed as one of the three major diseases threatening human health. According to reports, more than 48% of patients still have hand dysfunction after entering the chronic phase and cannot live independently, causing a heavy burden to the family and society. The current hand function rehabilitation methods, such as cold therapy, electrical stimulation therapy, rehabilitation robots, and exercise therapy and occupational therapy relying on therapists, not only consume a lot of manpower, but lack interest and active participation of patients. The direct participation of the motor ...

Claims

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Application Information

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IPC IPC(8): G06F3/01
CPCG06F3/015
Inventor 杨帮华张桃段凯文唐健真韩旭
Owner SHANGHAI UNIV
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