The classification of movement intention through machine learning models: the identification of significant time-domain EMG features

• Main Authors: Ismail, Mohd Khairuddin, Shahrul Naim, Sidek, Anwar, P. P. Abdul Majeed, Mohd Azraai, Mohd Razman, Asmarani, Ahmad Puzi, Hazlina, Md Yusof
• Format: Article
• Language: English
• Published: Peerj Inc. 2021
• Subjects: TA Engineering (General). Civil engineering (General); TJ Mechanical engineering and machinery
• Online Access: http://umpir.ump.edu.my/id/eprint/32419/1/The%20classification%20of%20movement%20intention%20through%20machine%20learning%20models.pdf; http://umpir.ump.edu.my/id/eprint/32419/; https://doi.org/10.7717/peerj-cs.379; https://doi.org/10.7717/peerj-cs.379
• Institution: Universiti Malaysia Pahang

Electromyography (EMG) signal is one of the extensively utilised biological signals for predicting human motor intention, which is an essential element in human-robot collaboration platforms. Studies on motion intention prediction from EMG signals have often been concentrated on either classificatio...