Effect of Two Adjacent Muscles of Flexor and Extensor on Finger Pinch and Hand Grip Force

W. W. Daud, N. Abas, M. Tokhi
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引用次数: 5

Abstract

Hand grip force and motion pattern classification using bio signal such as Electromyogram (EMG) has been very important in current studies. EMG based pattern classification has gain the utmost consideration especially in the commercial prostheses. Developing an intuitive hand control with fast response both in time and space are the major challenges. These challenges are due to the lack of information gathered from adjacent muscles. The study of adjacent muscles is crucially needed as it will allow to provide optimised hand grip and motion pattern classification without redundancy in the use of muscle information. The main aim of this paper is to investigate the effect of two adjacent flexor muscles; flexor digitorum superficial (FDS) and flexor carpi radialis (FCR), two adjacent extensor muscles: extensor carpi radialis longus (ECRL) and extensor digitorum communis (EDC) providing the perspective view of individual muscle performance compared to their adjacent muscle with respect to finger pinch and hand grip force. Practical classification results prove the significance of the study, both adjacent muscles perform almost similar with approximately >95% of similarities across different subjects. The results achieved lead to the conclusion, that the use of adjacent muscles can be reduced to only single muscle channel providing an optimised data for pattern recognition or classification.
屈伸肌相邻两肌对手指捏握力的影响
利用肌电图等生物信号对手部握力和运动模式进行分类是目前研究的重要内容。基于肌电图的模式分类尤其在商业假肢中得到了极大的重视。开发一种在时间和空间上都具有快速响应的直观手控是主要挑战。这些挑战是由于缺乏从邻近肌肉收集的信息。邻近肌肉的研究是至关重要的,因为它将允许提供优化的手握和运动模式分类,而不会冗余地使用肌肉信息。本文的主要目的是研究两个相邻屈肌的作用;指浅屈肌(FDS)和桡侧腕屈肌(FCR),两个相邻的伸肌:桡侧腕长伸肌(ECRL)和指共伸肌(EDC)提供了个体肌肉表现的视角,将其与相邻肌肉在手指按压和手握力方面进行比较。实际的分类结果证明了研究的意义,两个相邻的肌肉表现几乎相似,在不同的受试者中相似度约为95%。研究结果表明,相邻肌肉的使用可以减少到只有单个肌肉通道,为模式识别或分类提供了优化的数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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