一种基于肌电图的通过动态时间规整的笔迹识别方法。
An EMG-based handwriting recognition through dynamic time warping.
作者信息
Huang Gan, Zhang Dingguo, Zheng Xidian, Zhu Xiangyang
机构信息
State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, China, 200240.
出版信息
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:4902-5. doi: 10.1109/IEMBS.2010.5627246.
In this paper, an electromyography (EMG)-based handwriting recognition method was proposed for a latent tendency of natural user interface. The subjects wrote the characters at a normal speed, and six channels of EMG signals were recorded from forearm muscles. The dynamic time warping (DTW) algorithm was used to eliminate the time axis variance during writing. The process for template making and matching was illustrated diagrammatically. The results showed that no more than ten training trials per character could make an accuracy of above 90%. The recognition performance was compared in three character sets: digits, Chinese characters and capital letters.
本文针对自然用户界面的潜在趋势，提出了一种基于肌电图（EMG）的手写识别方法。受试者以正常速度书写字符，并从前臂肌肉记录六个通道的肌电信号。采用动态时间规整（DTW）算法消除书写过程中的时间轴差异。以图表形式说明了模板制作和匹配的过程。结果表明，每个字符的训练试验次数不超过十次，准确率即可达到90%以上。在数字、汉字和大写字母三个字符集上对识别性能进行了比较。
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