D
Didier Staudenmann
Researcher at University of Fribourg
Publications - 19
Citations - 1035
Didier Staudenmann is an academic researcher from University of Fribourg. The author has contributed to research in topics: Isometric exercise & Electromyography. The author has an hindex of 12, co-authored 19 publications receiving 940 citations. Previous affiliations of Didier Staudenmann include University of Amsterdam & VU University Amsterdam.
Papers
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Methodological aspects of SEMG recordings for force estimation--a tutorial and review.
TL;DR: The problems associated with surface EMG in muscle force estimation are discussed and the solutions that novel methodological developments provide to this problem are discussed.
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Improving EMG-based muscle force estimation by using a high-density EMG grid and principal component analysis
TL;DR: PCA contributes to the accuracy of EMG-based estimation of muscle force when using a high-density EMG grid by reducing the root mean square difference (RMSD) between predicted and measured force.
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Towards optimal multi-channel EMG electrode configurations in muscle force estimation: a high density EMG study.
TL;DR: Among the sensor configurations, the collection surface alone appeared to be responsible for the major part of the EMG based force estimation quality by improving it with 25%.
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Heterogeneity of muscle activation in relation to force direction: a multi-channel surface electromyography study on the triceps surae muscle
Didier Staudenmann,Idsart Kingma,Andreas Daffertshofer,Dick F. Stegeman,Dick F. Stegeman,J.H. van Dieen +5 more
TL;DR: The correlations between cluster time series and forces at the foot in specific directions differed substantially between clusters, showing that the differentially activated parts of the TS had specific biomechanical functions.
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Effects of EMG processing on biomechanical models of muscle joint systems: sensitivity of trunk muscle moments, spinal forces, and stability.
TL;DR: It is hypothesized that improvements in muscle force estimation can be achieved through adequate EMG processing, specifically whitening and high-pass (HP) filtering of the signals, and that the processing leads to an increase in pick-up area.