title: The designs and applications of a scanning interface with electrical signal detection on the scalp for the severely disabled.
abstract: This study discussed a computer-aided program development that meets the requirements of people with physical disabilities. A number of control modes, such as electrode signal recorded on the scalp and blink control, were combined with the scanning human-machine interface to improve the external input/output device. Moreover, a novel and precise algorithm, which filters noise and reduces misrecognition of the system, was proposed. A convenient assistive device can assist people with physical disabilities to meet their requirements for independent living and communication with the outside. The traditional scanning keyboard is changed, and only the phonetic notations are typed instead of characters, thus the time of tone and function selection could be saved, and the typing time could be also reduced. Barrier-free computer assistive devices and interface for people with physical disabilities in typing or speech could allow them to use a scanning keyboard to select phonetic symbols instead of Chinese characters to express their thoughts. The human-machine interface controls can obtain more reliable results as 99.8% connection success rate and 95% typing success rate.
authors.affiliation: Department of Automatic Control Engineering, Feng Chia University, Taichung, Taiwan. Electronic address: lincs@fcu.edu.tw.
authors.forename: Chern-Sheng
authors.initials: CS
authors.lastname: Lin
authors.affiliation: Ph.D. Program in Electrical and Communications Engineering, Feng Chia University, Taichung, Taiwan; Department of Medicine, Chung Shan Medical University, Taichung, Taiwan; Department of Integrated Chinese and Western Medicine, Chung Shan Medical University Hospital, Taichung, Taiwan.
authors.forename: Jung-Chih
authors.initials: JC
authors.lastname: Lin
authors.affiliation: Master's Program of Biomedical Informatics and Biomedical Engineering, Feng Chia University, Taichung, Taiwan.
authors.forename: Yen-Chen
authors.initials: YC
authors.lastname: Huang
authors.affiliation: Master's Program of Biomedical Informatics and Biomedical Engineering, Feng Chia University, Taichung, Taiwan.
authors.forename: Yu-Chen
authors.initials: YC
authors.lastname: Lai
authors.affiliation: Department of Automatic Control Engineering, Feng Chia University, Taichung, Taiwan.
authors.forename: Hsing-Cheng
authors.initials: HC
authors.lastname: Chang
mesh_terms: D000465:Algorithms; D062207:Brain-Computer Interfaces; D003143:Communication Devices for People with Disabilities; D004569:Electroencephalography / Q000295:instrumentation* / Q000379:methods*; D004585:Electrooculography / Q000295:instrumentation* / Q000379:methods; D004867:Equipment Design; D019544:Equipment Failure Analysis; D005133:Eye Movements / Q000502:physiology; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: Assistive device; Blink control; Scanning human–machine interface