@inproceedings{96a3078b2f204b98a5d21aa64a9f37e1,
title = "Robust sEMG electrodes configuration for pattern recognition based prosthesis control",
abstract = "Electromyographic (EMG) signal is the electrical manifestation of a muscle contraction. Surface EMG signal can be obtained by electrodes on the skin to control prosthetic hand. However, surface EMG is sensitive to environmental interference, which leads to a low motion recognition rate of prosthesis control when encountering unexpected interferences, like electrodes shift. Electrodes shift occurs particularly in the day-to-day use of wearing electrodes. As a result, a long-term training procedure is necessary. To solve this problem, this paper proposes a new sEMG electrodes configuration to reduce the interference caused by electrodes shift. Experiments are designed to verify the improvements through evaluating the classification accuracy of discriminating eleven hand motions by pattern recognition approach. The comparison results show that the proposed electrodes configuration increases the pattern recognition rate by 4% and 8% when applied kNN and LDA classifier, respectively. This paper suggests that optimising electrodes configuration is able to improve the EMG pattern discrimination and the proposed electrodes configuration has reference value.",
author = "Yinfeng Fang and Honghai Liu",
year = "2014",
month = oct,
doi = "10.1109/SMC.2014.6974252",
language = "English",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2210--2215",
booktitle = "Proceedings of the 2014 IEEE International Conference on Systems, Man and Cybernetics (SMC)",
address = "United States",
note = "International Conference on Systems, Man and Cybernetics, SMC 2014 ; Conference date: 05-10-2014 Through 08-10-2014",
}