食指肌电图分类比较

Eda Capa, Y. Cotur, Caner Gumus, E. Kaplanoglu, M. Ozkan
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引用次数: 2

摘要

本研究以两种不同的方法对食指运动所获得的肌电图(EMG)信号进行分析和分类,并将结果进行比较,作为灵巧拟人化假肢项目的前期研究。食指与其他手指的不同之处在于它的肌腱结构和更高的活动能力。肌电图信号与食指运动之间的关系是理解手指如何执行抓握和姿势等任务的关键。信号来自两个不同的肌肉群,并根据抓握和位置进行分类。使用有限状态机(FSM)和人工神经网络(ANN)进行分类。此外,该研究还表明,来自食指运动的信号对肌电控制假手的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparative EMG classification of index finger
In this study electromyography (EMG) signals obtained from index finger movements are analysed and classified in two separated methods and results are compared as a pre-study of dexterous anthropomorphic prosthesis hand project. The index finger differs from other hand digits for its tendon structure and higher mobility capabilities. The relation between the EMG signal and movement of the index finger is a key to understanding how the finger performs the tasks such as grasping and postures. Signals are measured from two different muscle groups and classified by grasping and positions. Finite State Machine (FSM) and Artificial Neural Network (ANN) are used for classification. Also the study indicates the effects of signals from index finger motions on a myoelectric controlled prosthetic hand.
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