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An action recognition method for hand rehabilitation training of stroke patients based on array myoelectricity

A technology for rehabilitation training and action recognition, which is applied in the fields of medical science, diagnosis, diagnostic recording/measurement, etc. It can solve the problems of poor recognition accuracy and achieve the effect of improving recognition accuracy and avoiding information redundancy or loss

Active Publication Date: 2022-04-12
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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  • Abstract
  • Description
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Problems solved by technology

[0007] Aiming at the above-mentioned deficiencies in the prior art, the present invention provides an action recognition method for hand rehabilitation training of stroke patients based on array myoelectricity, which solves the problem of poor recognition accuracy of the existing methods

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  • An action recognition method for hand rehabilitation training of stroke patients based on array myoelectricity
  • An action recognition method for hand rehabilitation training of stroke patients based on array myoelectricity
  • An action recognition method for hand rehabilitation training of stroke patients based on array myoelectricity

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Embodiment Construction

[0041] The specific embodiments of the present invention are described below so that those skilled in the art can understand the present invention, but it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art, as long as various changes Within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions and creations using the concept of the present invention are included in the protection list.

[0042] Such as figure 1 As shown, the method for recognition of stroke patient's hand rehabilitation training action based on array myoelectricity includes the following steps:

[0043] S1. Wrap an m×n array EMG sensor on the patient's forearm to obtain the EMG data during the patient's rehabilitation training; where m represents the number of electrodes in the axial direction of the forearm, and n represents the number of ...

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Abstract

The invention discloses a hand rehabilitation training action recognition method for stroke patients based on array myoelectricity. The invention uses an array type myoelectric sensor to collect the myoelectric sequence data of the patient's forearm during the training process, and retains the synergy information and information of muscles in physical space. Muscle activity changes over time; establish a parallel convolutional neural network to automatically extract the spatial features of myoelectric data at different times; establish a long-term short-term memory network to automatically learn time-dependent features of myoelectricity. Classification and recognition are performed after fusing EMG spatiotemporal features to avoid information redundancy or loss caused by artificial feature engineering, which can effectively improve the accuracy of hand movement recognition.

Description

technical field [0001] The invention relates to the field of rehabilitation action recognition, in particular to a method for recognizing hand rehabilitation training actions of stroke patients based on array myoelectricity. Background technique [0002] Rehabilitation training uses the plasticity of the central system to help stroke patients recover their motor functions to a certain extent. The recognition of rehabilitation training actions for patients is of great significance. The recognition results can be used as control signals for auxiliary training equipment in clinical practice to control the movement of artificial limbs. Assist patients with physical impairments to complete motor functions similar to real limbs; or use training action recognition results as the basis for motor function assessment; also realize intelligent rehabilitation training in remote interactive rehabilitation or assist physicians in remote monitoring of training conditions, etc. [0003] Mos...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): A61B5/11A61B5/389A61B5/397A61B5/00
CPCA61B5/11A61B5/1121A61B5/1123A61B5/7264
Inventor 杨尚明任志扬刘勇国李巧勤
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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