北京生物醫(yī)學工程

基于肌動圖與肌電圖信號的假肢控制系統(tǒng)的研究

A Prosthesis Control System Based on Both of Mechanomyography and Electromyography

作者：游淼鄒國棟林婉華余龍

單位：中南大學地球科學與信息物理工程學院（長沙410083）

分類號：

出版年·卷·期（頁碼）：2011·30·6（574-577）

摘要：

目的驗證使用肌動圖（mechanomyography，MMG）和肌電圖（electromyography，EMG）兩種信號共同作為假肢控制信號時，是否能提高假肢控制系統(tǒng)分類的準確度。方法本文采用信號融合方法，通過融合6通道的MMG信號與2通道的EMG信號，以及基于模式識別的線性判別分析（linear discriminant analysis，LDA）算法，研制了基于MMG和EMG信號的假肢控制系統(tǒng)。結(jié)果該系統(tǒng)能對采集到的信號進行處理并得出動作分類結(jié)果，然后控制假肢完成相應動作。對6位測試者的腕屈、腕伸、張開、握拳4類動作以及靜止狀態(tài)進行假肢控制的動作分類準確度實驗，準確度達94.6%，比單獨用MMG信號的精度88.5%或EMG信號精度90.4%效果更好。結(jié)論基于MMG與EMG信號的假肢控制系統(tǒng)可以更好地實現(xiàn)假肢控制動作的有效分類，未來可應用于上臂截肢的殘疾人。

Objective To improve the accuracy of classification for a prosthesis control system by using of mechanomyography（MMG）and electromyography（EMG）as prosthesis control signals.Methods A prosthesis control system based on MMG and EMG was developed by using a signal fusion method.Six channels of MMG and two channels of EMG were fused，and combined with linear discriminant analysis（LDA）algorithm based on pattern recognition，which were applied for the test of the classification precision of prosthesis control system.Six volunteers were enrolled in the test including four kinds of activities and static status through this system.The precision reached to 94.6%，which is better than the accuracy when MMG signal（88.5%）or EMG signal（90.4%）was adopted solo.Conclusions The system based on both of MMG and EMG signals can classify the prosthesis controlling action efficiently，and control the prosthesis independently.This prosthesis control system is expected to be applied to the disabled upper arm amputated in the near future.

參考文獻：

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