Literature DB >> 15642649

Towards optimal multi-channel EMG electrode configurations in muscle force estimation: a high density EMG study.

Didier Staudenmann1, Idsart Kingma, Dick F Stegeman, Jaap H van Dieën.   

Abstract

Surface EMG is an important tool in biomechanics, kinesiology and neurophysiology. In neurophysiology the concept of high-density EMG (HD-EMG), using two dimensional electrode grids, was developed for the measurement of spatiotemporal activation patterns of the underlying muscle and its motor units (MU). The aim of this paper was to determine, with the aid of a HD-EMG grid, the relative importance of a number of electrode sensor configurations for optimizing muscle force estimation. Sensor configurations are distinguished in two categories. The first category concerns dimensions: the size of a single electrode and the inter electrode distance (IED). The second category concerns the sensor's spatial distribution: the total area from which signals are obtained (collection surface) and the number of electrodes per cm(2) (collection density). Eleven subjects performed isometric arm extensions at three elbow angles and three contraction levels. Surface-EMG from the triceps brachii muscle and the external force at the wrist were measured. Compared to a single conventional bipolar electrode pair, the force estimation quality improved by about 30% when using HD-EMG. 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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Year:  2004        PMID: 15642649     DOI: 10.1016/j.jelekin.2004.06.008

Source DB:  PubMed          Journal:  J Electromyogr Kinesiol        ISSN: 1050-6411            Impact factor:   2.368


  12 in total

1.  Time to task failure in shoulder elevation is associated to increase in amplitude and to spatial heterogeneity of upper trapezius mechanomyographic signals.

Authors:  Pascal Madeleine; Dario Farina
Journal:  Eur J Appl Physiol       Date:  2007-10-18       Impact factor: 3.078

2.  Muscle fiber conduction velocity and EMG amplitude of the upper trapezius muscle in healthy subjects after low-level laser irradiation: a randomized, double-blind, placebo-controlled, crossover study.

Authors:  Fabiana Sarilho de Mendonça; Paulo de Tarso Camillo de Carvalho; Daniela Aparecida Biasotto-Gonzalez; Simone Aparecida Penimpedo Calamita; Cid André Fidelis de Paula Gomes; César Ferreira Amorim; Marco Antônio Fumagalli; Fabiano Politti
Journal:  Lasers Med Sci       Date:  2017-12-05       Impact factor: 3.161

3.  Altered neuromuscular control mechanisms of the trapezius muscle in fibromyalgia.

Authors:  Björn Gerdle; Christer Grönlund; Stefan J Karlsson; Andreas Holtermann; Karin Roeleveld
Journal:  BMC Musculoskelet Disord       Date:  2010-03-05       Impact factor: 2.362

4.  Low-back electromyography (EMG) data-driven load classification for dynamic lifting tasks.

Authors:  Deema Totah; Lauro Ojeda; Daniel D Johnson; Deanna Gates; Emily Mower Provost; Kira Barton
Journal:  PLoS One       Date:  2018-02-15       Impact factor: 3.240

5.  Predicting 3D lip shapes using facial surface EMG.

Authors:  Merijn Eskes; Maarten J A van Alphen; Alfons J M Balm; Ludi E Smeele; Dieta Brandsma; Ferdinand van der Heijden
Journal:  PLoS One       Date:  2017-04-13       Impact factor: 3.240

6.  Relationship between Isometric Muscle Force and Fractal Dimension of Surface Electromyogram.

Authors:  Matteo Beretta-Piccoli; Gennaro Boccia; Tessa Ponti; Ron Clijsen; Marco Barbero; Corrado Cescon
Journal:  Biomed Res Int       Date:  2018-03-15       Impact factor: 3.411

7.  Upper Limb End-Effector Force Estimation During Multi-Muscle Isometric Contraction Tasks Using HD-sEMG and Deep Belief Network.

Authors:  Ruochen Hu; Xiang Chen; Shuai Cao; Xu Zhang; Xun Chen
Journal:  Front Neurosci       Date:  2020-05-07       Impact factor: 4.677

8.  Exhausting repetitive piano tasks lead to local forearm manifestation of muscle fatigue and negatively affect musical parameters.

Authors:  Etienne Goubault; Felipe Verdugo; Justine Pelletier; Caroline Traube; Mickaël Begon; Fabien Dal Maso
Journal:  Sci Rep       Date:  2021-04-14       Impact factor: 4.379

9.  A SEMG-Force Estimation Framework Based on a Fast Orthogonal Search Method Coupled with Factorization Algorithms.

Authors:  Xiang Chen; Yuan Yuan; Shuai Cao; Xu Zhang; Xun Chen
Journal:  Sensors (Basel)       Date:  2018-07-11       Impact factor: 3.576

10.  Automated Channel Selection in High-Density sEMG for Improved Force Estimation.

Authors:  Gelareh Hajian; Ali Etemad; Evelyn Morin
Journal:  Sensors (Basel)       Date:  2020-08-27       Impact factor: 3.576

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