Objective To provide myoelectric signal of electronic artificial limb via examination and assessment of the myoelectric signals given by upper extremity muscles in light contraction.
目的通过对上肢肌群肌肉轻收缩时肌电信号的检测与分析，提供电子假肢信号源。
Classifying myoelectric signals using hidden Markov model and support vector machine to process myoelectric signals, with the task of discrimination five classes of multifunction prosthesis movement.
利用隐马尔克夫模型与支持向量机相结合，对站立和行走过程中的下肢表面肌电信号进行分类，用来控制多功能假肢。
Result The software is capable of making realtime acquisition and display of four channels of myoelectric potential signals and one channel of operation signal synchronously.
结果它能对四路肌电信号、一路操作控制信号进行实时、同步地采集、显示以及离线分析、处理。
应用推荐