Classification of EMG Signals: Using DWT Features and ANN Classifier

• Published in: IAENG international journal of computer science Vol. 51; no. 1; p. 23
• Main Authors: Aljebory, Karim M, Jwmah, Yashar M, Mohammed, Thabit S
• Format: Journal Article
• Language: English
• Published: Hong Kong International Association of Engineers 01.01.2024
• Subjects: Algorithms; Artificial neural networks; Classification; Classifiers; Datasets; Discrete Wavelet Transform; Discriminant analysis; Electromyography; Empirical analysis; Feature extraction; Hand (anatomy); Machine learning; Myoelectricity; Neural networks; Performance evaluation; Prostheses; Signal classification; Signal processing; Wavelet transforms; Wheelchairs

This study offers a concise overview of classifying hand movements based on their kinetic and myoelectric characteristics. In this work, we propose utilizing Electromyography (EMG) signals to distinguish these movements, especially for applications like wheelchair guidance and prosthetic control. Un...