基于表面肌电信号的按键手势识别与交互

Juan Cheng, Xiang Chen, Zhiyuan Lu, Kongqiao Wang, M. Shen
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引用次数: 13

摘要

本文研究了基于表面肌电图(surface electromyographic, SEMG)信号的按键手指手势模式识别以及按键手势交互应用的可行性。首先设计了两类识别实验,探讨了基于表面肌电信号分类的16种与右手相关的手指按键手势和4种控制手势的可行性和可重复性,并参照标准PC键盘定义了按键手势。根据实验结果,选择10个识别度较高的按键手势作为模拟手机的数字输入键,并将4个控制手势映射到4个控制键上。然后进行了音量设置和短信发送两种类型的使用测试,调查了基于手势的交互性能和用户对该技术的态度,测试结果表明用户能够以全新的体验接受这种新颖的输入策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Key-press gestures recognition and interaction based on SEMG signals
This article conducted research on the pattern recognition of keypress finger gestures based on surface electromyographic (SEMG) signals and the feasibility of key -press gestures for interaction application. Two sort of recognition experiments were designed firstly to explore the feasibility and repeatability of the SEMG -based classification of 1 6 key-press finger gestures relating to right hand and 4 control gestures, and the key -press gestures were defined referring to the standard PC key board. Based on the experimental results, 10 quite well recognized key -press gestures were selected as numeric input keys of a simulated phone, and the 4 control gestures were mapped to 4 control keys. Then two types of use tests, namely volume setting and SMS sending were conducted to survey the gesture-base interaction performance and user's attitude to this technique, and the test results showed that users could accept this novel input strategy with fresh experience.
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