
Slide

Centre Interdisciplinaire
de Recherche et d’Innovation
en Cybersécurité et Société
de Recherche et d’Innovation
en Cybersécurité et Société
1.
Bouchard, Stephane; Rancourt, Denis; Clancy, Edward A.
EMG-to-torque dynamic relationship for elbow constant angle contractions Article d'actes
Dans: Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, p. 573, IEEE, Piscataway, NJ, United States, Atlanta, GA, USA, 1999, ISBN: 05891019 (ISSN); 0780356756 (ISBN), (Journal Abbreviation: Annu Int Conf IEEE Eng Med Biol Proc).
Résumé | Liens | BibTeX | Étiquettes: Electromyography, Joints (anatomy), Mathematical models, Signal whitening, Torque
@inproceedings{bouchard_emg–torque_1999,
title = {EMG-to-torque dynamic relationship for elbow constant angle contractions},
author = {Stephane Bouchard and Denis Rancourt and Edward A. Clancy},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-0033353983&partnerID=40&md5=cf7a2b4c35a58c2409dda2d3f1af124d},
isbn = {05891019 (ISSN); 0780356756 (ISBN)},
year = {1999},
date = {1999-01-01},
booktitle = {Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings},
volume = {1},
pages = {573},
publisher = {IEEE, Piscataway, NJ, United States},
address = {Atlanta, GA, USA},
abstract = {The purpose of this work was to determine the optimal EMG-torque relationship using four different EMG processors in conjunction with different system identification (ID) techniques for dynamically torque varying elbow constant angle contractions. Comparing predicted torque with actual elbow torque, it was found that either multiple EMG channels or EMG signal whitening lead to the best relationship. The choice of the system ID model had limited effect on performance.},
note = {Journal Abbreviation: Annu Int Conf IEEE Eng Med Biol Proc},
keywords = {Electromyography, Joints (anatomy), Mathematical models, Signal whitening, Torque},
pubstate = {published},
tppubtype = {inproceedings}
}
The purpose of this work was to determine the optimal EMG-torque relationship using four different EMG processors in conjunction with different system identification (ID) techniques for dynamically torque varying elbow constant angle contractions. Comparing predicted torque with actual elbow torque, it was found that either multiple EMG channels or EMG signal whitening lead to the best relationship. The choice of the system ID model had limited effect on performance.