Exploration on the feasibility of building muscle-computer interfaces using neck and shoulder motions.
This paper investigates the feasibility of building muscle-computer interfaces starting from surface Electromyography (SEMG) -based neck and shoulder motion recognition. In order to reach the research goal, a real-time SEMG sensing, processing and classification system was developed firstly. Then two types of SEMG recognition experiments, namely user-specific and user-independent classification, were designed and conducted on seven kinds of neck and shoulder motions to explore the feasibility of using these motions as input commands of muscle-computer interfaces. In all 9 subjects took part in these experiments, 97.8% and 84.6% overall average recognition accuracies were obtained in user-specific and user-independent experiments respectively. The experimental results demonstrate that it is possible to build muscle-computer interfaces with neck and shoulder motions. In addition, the results of cross-time experiments designed to explore the relationship between training and accuracy in user-specific recognition indicate that users can interact accurately with computers using the defined motions only after four times training in different days.
Xu
Zhang
Z
Biomedical Engineering Institute, Department of Electronics Science and Technology, University of Science and Technology of China, Hefei 230027, China. zhx90@mail.ustc.edu.cn
Xiang
Chen
C
Lantz
Vuokko
V
Ji-Hai
Yang
Y
Kong-Qiao
Wang
W
D000328:Adult; D001698:Biomedical Engineering; D004576:Electromyography / Q000706:statistics & numerical data; D006801:Humans; D007223:Infant; D008297:Male; D008328:Man-Machine Systems; D009068:Movement / Q000502:physiology; D018482:Muscle, Skeletal / Q000502:physiology*; D009334:Neck Muscles / Q000502:physiology; D012782:Shoulder; D012815:Signal Processing, Computer-Assisted; D014584:User-Computer Interface; D055815:Young Adult