Pattern recognition of electromyography signals based on novel time domain features for amputees' limb motion classification

• Published in: Computers & electrical engineering Vol. 67; pp. 646 - 655
• Main Authors: Samuel, Oluwarotimi Williams, Zhou, Hui, Li, Xiangxin, Wang, Hui, Zhang, Haoshi, Sangaiah, Arun Kumar, Li, Guanglin
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Ltd 01.04.2018; Elsevier BV
• Subjects: Amputation; Electrocardiography; Electromyography; Feature extraction; Myoelectric prostheses; Pattern recognition; Performance enhancement; Prostheses; Rehabilitation robotics; Signal classification; Time domain analysis; Time domain features; Upper-limb amputees; Rehabilitation robotics; Myoelectric prostheses; Upper-limb amputees; Electromyography; Pattern recognition; Time domain features

•This study proposed three new time domain (TD) features for EMG Pattern recognition (EMG-PR).•The performances of these features were examined using four performance metrics.•The results showed that the newly proposed features outperform the previously used TD features.•These features might improve...