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This paper aims at building a portable robotic hand for physically disabled people to perform basic hand movements. Surface Electromyography(EMG) signal is collected from muscles of human forearm to extract the subject's intentions of action, where six kinds of gestures are selected for discussion. An Artificial Neural Network(ANN) is trained and utilized to distinguish the desired movement according...
To classify the five individual finger motions from an electromyogram (EMG) signal, a classification system that hybridizes EMG signals in both the transient and converged states of a motion is proposed. The classifications of finger motions are executed individually in each state by a well-established artificial neural network (ANN). Then, the outputs of the two classifiers are combined. The efficacy...
With the aim to control a multiple degrees of freedom electromechanical devices, e.g., assistive robots, powered wheelchair, etc., this paper proposes a real-time multichannel surface electromyography classification scheme based on the coordination or synergies between a functional group of muscles: biceps brachii, triceps brachii, pronator teres, and brachioradialis. The muscular synergy is evaluated...
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