Rehabilitation training system of amputation upper limb based on virtual reality

Abstract

The invention relates to a rehabilitation training system of amputation upper limb based on virtual reality, comprising the following parts: myoelectric signal detection and processing, amputation upper limb modeling and virtual reality scene interaction. The myoelectric signal detection and processing is realized by the steps of extracting, amplifying, filtering, A / D-transferring and multipath-acquiring myielectric signals on a stump by using a myoelectric tester ; extracting, extracting Rubust features of the myielectric signals and recognizing a fast and effective upper limb movement gesture together with an on-line learning method; the amputation upper limb modeling is realized by the steps of carrying out three-dimensional reconstruction on the amputation upper limb by adopting a three-dimensional parametric grid model and using a photo of a healthy upper limb, and realizing motion simulation of a virtual hand by taking the tracked upper limb movement parameters as model driven data; and the virtual reality scene interaction is realized by the steps of carrying out real three-dimensional interactional scene modeling and realizing real time interaction between the stump musclemovement and the three-dimensional scene through myoelectricity. The rehabilitation training system is mainly used to assist an upper limb amputated patient to carry out necessary adaptive training before installing an artificial limb so as to help the patient to adapt to the usage of the artificial limb as soon as possible.

Description

technical field [0001] The invention relates to the technical field of electromyographic signal processing and image processing, in particular to feature extraction and identification of electromyographic signals and a human-computer interaction technology method. Background technique [0002] The amputated upper limb controls the myoelectric prosthetic hand through myoelectric signals. The EMG signal contains the movement characteristics of the amputated upper limb, and the movement information of the patient can be further accurately obtained through the analysis of the movement characteristics. Before the patient can flexibly control the prosthetic limb, he first needs to master the control of the EMG signal of the upper limb of the amputated limb. It takes a long period of training and adaptation to gradually adapt and control it. Using myoelectric signals as input data, a virtual rehabilitation environment is constructed. In this virtual environment, the system gives s...

AI Technical Summary

Problems solved by technology

[0004] In terms of practicality, the existing technology lacks a complete and effective solution for the combination of EMG signal recognition, real hand 3D model creation, and immersive human-computer interaction training system

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