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Braz J Med Biol Res. 2012 Oct;45(10):977-81. Epub 2012 May 31.

A simple test of muscle coactivation estimation using electromyography.

Author information

1
Laboratório de Biodinâmica do Movimento Humano, Escola de Educação Física, Universidade São Judas Tadeu, São Paulo, SP, Brasil.

Abstract

In numerous motor tasks, muscles around a joint act coactively to generate opposite torques. A variety of indexes based on electromyography signals have been presented in the literature to quantify muscle coactivation. However, it is not known how to estimate it reliably using such indexes. The goal of this study was to test the reliability of the estimation of muscle coactivation using electromyography. Isometric coactivation was obtained at various muscle activation levels. For this task, any coactivation measurement/index should present the maximal score (100% of coactivation). Two coactivation indexes were applied. In the first, the antagonistic muscle activity (the lower electromyographic signal between two muscles that generate opposite joint torques) is divided by the mean between the agonistic and antagonistic muscle activations. In the second, the ratio between antagonistic and agonistic muscle activation is calculated. Moreover, we computed these indexes considering different electromyographic amplitude normalization procedures. It was found that the first algorithm, with all signals normalized by their respective maximal voluntary coactivation, generates the index closest to the true value (100%), reaching 92 ± 6%. In contrast, the coactivation index value was 82 ± 12% when the second algorithm was applied and the electromyographic signal was not normalized (P < 0.04). The new finding of the present study is that muscle coactivation is more reliably estimated if the EMG signals are normalized by their respective maximal voluntary contraction obtained during maximal coactivation prior to dividing the antagonistic muscle activity by the mean between the agonistic and antagonistic muscle activations.

PMID:
22641413
PMCID:
PMC3854180
[Indexed for MEDLINE]
Free PMC Article

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