title: An EMG-based handwriting recognition through dynamic time warping.
abstract: 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.
authors.affiliation: State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, China, 200240. huanggan1982@gmail.com
authors.forename: Gan
authors.initials: G
authors.lastname: Huang
authors.forename: Dingguo
authors.initials: D
authors.lastname: Zhang
authors.forename: Xidian
authors.initials: X
authors.lastname: Zheng
authors.forename: Xiangyang
authors.initials: X
authors.lastname: Zhu
mesh_terms: D000465:Algorithms; D001699:Biometry / Q000379:methods*; D004576:Electromyography / Q000379:methods*; D005542:Forearm / Q000502:physiology*; D006236:Handwriting; D006801:Humans; D009119:Muscle Contraction / Q000502:physiology*; D018482:Muscle, Skeletal / Q000502:physiology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D013647:Task Performance and Analysis