有效的基于电肌图的打字系统:向HCI文本输入的新方法
概括
这项研究引入了一种新的电肌图 (EMG) 打字系统,用于实时交互. 这种新的方法实现了准确的无键盘打字和快速反,证明了它对先进的人机交互的潜力.
科学领域:
- 生物医学工程 生物医学工程
- 人与计算机的交互
- 信号处理 信号处理
背景情况:
- 电肌图 (EMG) 对静态手势和医疗用途是有效的.
- 实时EMG应用程序,如打字,由于持续的信号对离散输出转换而具有挑战性.
- 现有的方法在交互式打字所需的准确性和速度方面扎.
研究的目的:
- 开发一种新的EMG打字系统,用于实时,无键盘交互.
- 为了应对连续EMG信号处理对离散打字输出的挑战.
- 为了提高基于EMG的打字系统的准确性和响应时间.
主要方法:
- 利用连接器时间分类 (CTC) 进行高效的连续EMG信号识别.
- 实施并行推断方法以提高识别准确性.
- 开发并测试了一种原型EMG打字系统.
主要成果:
- 在测试组中实现了3.8%的字符错误率.
- 报告了一个词错误率为7.1%.
- 证明系统响应时间小于100毫秒.
结论:
- 新的EMG打字系统可实现实时,无键盘交互.
- 该系统显示了推进人机交互的巨大潜力.
- 通过CTC和并行推断的结合,可以有效地处理连续的EMG信号来打字.
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