A Novel Pattern Classification Method for Multivariate EMG Signals Using Neural Network

• Published in: Advances in Natural Computation pp. 165 - 174
• Main Authors: Bu, Nan, Arita, Jun, Tsuji, Toshio
• Format: Book Chapter Conference Proceeding
• Language: English; Japanese
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2005; Springer
• Series: Lecture Notes in Computer Science
• Subjects: Applied sciences; Artificial intelligence; Cervical Muscle; Computer science; control theory; systems; Exact sciences and technology; Feature Extraction Technique; Gaussian Mixture Model; Principal Component Analysis; Probabilistic Neural Network; Mixed distribution; Dimensionality; Probabilistic approach; Extraction process; Pattern recognition; Neural network; Modeling; Pattern classification; Phonetics; Feature extraction; Electromyography; Feasibility; Phoneme; Pattern extraction; Principal component analysis

Feature extraction is an important issue in electromyography (EMG) pattern classification, where feature sets of high dimensionality are always used. This paper proposes a novel classification method to deal with high-dimensional EMG patterns, using a probabilistic neural network, a reduced-dimensio...