NDLI: Optimization of input parameters of an EMG-force model in constant and sinusoidal force contractions

Content Provider	IEEE Xplore Digital Library
Author	Hua Cao Boudaoud, S. Marin, F. Marque, C.
Copyright Year	2009
Description	Author affiliation: Université de Technologie de Compiègne, CNRS UMR 6600, Biomécanique et Bioingénierie, 60205, Compiègne, France (Hua Cao; Boudaoud, S.; Marin, F.; Marque, C.)
Abstract	In an electromyographic and muscle force (EMG-Force) model, the variability and uncertainty of the input muscle parameters increase the difficulty of assessing this type of model. In this study, a Monte Carlo method is used to evaluate the robustness and the sensitivity of an EMG-Force model, recently developed by our team, for two groups of simulations (constant and sinusoidal force contractions). Two existing criteria (EMG/force and force/force-variability relations) and a new criterion derived from this model (Root Mean Square error, ErrorRMS, between the force command and the generated force) are used to extract relevant simulations and obtain the optimized parameter ranges in constant force contractions, while only the new criterion could be valuable in sinusoidal force contractions. The comparison of obtained results from the two groups of simulations has shown that the new criterion can replace the two existing criteria in constant and sinusoidal force contractions to give rise to stable optimized input parameter ranges for the studied EMG-Force model.
Starting Page	4962
Ending Page	4965
File Size	701900
Page Count	4
File Format	PDF
ISBN	9781424432967
ISSN	1557170X
DOI	10.1109/IEMBS.2009.5334099
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-03
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Muscles Electromyography Solid modeling Recruitment Uncertainty Predictive models Force measurement Robustness Root mean square USA Councils constant and sinusoidal force contractions EMG-Force model Monte Carlo methods Force/force-variability relation
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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