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Development of an EMG-Based Car Interface Using Artificial Neural Networks for the Physically Handicapped  

Kwak, Jae-Kyung (고려대학교 대학원 전산학과)
Jeon, Tae-Woong (고려대학교 대학원 전산학과)
Park, Hum-Yong (고려대학교 제어계측공학과)
Kim, Sung-Jin (한국과학기술 산업공학과)
An, Kwang-Dek (충북대학교 전기공학과)
Publication Information
Journal of Information Technology Services / v.7, no.2, 2008 , pp. 149-164 More about this Journal
Abstract
As the computing landscape is shifting to ubiquitous computing environments, there is increasingly growing the demand for a variety of device controls that react to user's implicit activities without excessively drawing user attentions. We developed an EMG-based car interface that enables the physically handicapped to drive a car using their functioning peripheral nerves. Our method extracts electromyogram signals caused by wrist movements from four places in the user's forearm and then infers the user's intent from the signals using multi-layered neural nets. By doing so, it makes it possible for the user to control the operation of car equipments and thus to drive the car. It also allows the user to enter inputs into the embedded computer through a user interface like an instrument LCD panel. We validated the effectiveness of our method through experimental use in a car built with the EMG-based interface.
Keywords
Electromyogram (EMG); Human-computer Interface; Artificial Neural Network EMG; Pattern Recognition; Nonlinear Feature Projection; Wavelet Packet Transform; PCA; SOFM;
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