An EMG-based handwriting recognition through dynamic time warping

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) algorith...

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Published in2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Vol. 2010; pp. 4902 - 4905
Main Authors Huang, Gan, Zhang, Dingguo, Zheng, Xidian, Zhu, Xiangyang
Format Conference Proceeding Journal Article
LanguageEnglish
Published United States IEEE 01.01.2010
Subjects
Accuracy
Algorithms
Biometry - methods
Electromyography
Electromyography - methods
Forearm - physiology
Handwriting
Handwriting recognition
Humans
Muscle Contraction - physiology
Muscle, Skeletal - physiology
Muscles
Pattern Recognition, Automated - methods
Task Performance and Analysis
Time series analysis
Training
Writing
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Summary: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.
ISBN:1424441234
9781424441235
ISSN:1094-687X
1557-170X
DOI:10.1109/IEMBS.2010.5627246