| Summary: | 碩士 === 國立交通大學 === 電機與控制工程系所 === 95 === Electromyographic (EMG) signal, generated due to muscle contraction, is often used for rehabilitation devices. As an indicator for human motion intention, it is quiet intuitive to use the EMG as the command for robot or prosthesis control. However, EMG signals are inconsistent, nonlinear, time varying and uncertain. To duel with these properties, we propose using the neural-network to find out the relationship between EMG and the joint angle of the elbow. As the forearm movement is tackled, we measure EMG from biceps muscle and mean absolute values (MAV) as the feature. An EMG-based robot regulation control system is developed with a user-friendly interface.
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