使用表面肌电图进行手势检测

L. Pomšár, Norbert Ferenčík, Miroslav Jaščur, M. Bundzel
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引用次数: 1

摘要

在本文中,我们介绍了目前关于肌电数据测量和处理随后用于手势检测的应用研究。近年来,康复领域取得了巨大的进步。这是由于各种残疾患者人数的增加、技术进步和大量可用设备的缘故。其中一个康复子领域是运动障碍患者的康复。这种类型的康复通常涉及不同的虚拟现实或增强现实系统。这种系统需要精确、廉价和用户友好的设备作为控制器。在本文中,我们提出了一个由肌电图控制的系统。该系统旨在帮助手指控制和运动受损的患者康复。在离线训练过程中,肌电数据由Myo手环测量,支持向量机分类器进行处理和分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using surface electromyography for gesture detection
In this article, we present our current application research regarding measurement and processing of Electromyography data subsequently used for gesture detection. The rehabilitation area has been experiencing a huge progress in recent years. This is due to an increase in the number of patients with various types of disability, technological advance and large number of available devices. One of the rehabilitation sub-areas is the rehabilitation of patients with motor impairment.This type of rehabilitation often involves different virtual reality or augmented reality systems. Such systems are in need of accurate, inexpensive and user-friendly devices acting as controllers. In this paper we propose a system controlled via electromyography. This system is designed to aid rehabilitation of patients with impaired finger control and movements. The electromyography data are measured by Myo bracelet, processed and classified by support vector machines classifier during the offline training.
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