To identify the smallest combinations of maximum voluntary isometric contraction (MVIC) tests that produce near-maximum voluntary activation (MVA) for a large proportion of participants for the shoulder girdle muscles.
Healthy participants (N=38).
Main Outcome Measures
The electromyography of 12 shoulder muscles was recorded while participants performed 15 MVIC tests. The smallest combinations of MVIC tests that met our acceptance criterion (ie, produce 90% of MVA for 90% of participants) were identified. Optimal combinations were identified for each of the 12 muscles individually and for the 12 muscles simultaneously. Electromyographic activation levels of the 95th highest percentile obtained with our optimal combinations and with the Four Normalization Tests previously recommended were compared using paired t tests.
Between 2 and 6 MVIC tests were required for each of the 12 muscles, and 12 MVIC tests were required for the 12 muscles to meet the acceptance criterion. These optimal combinations produced electromyographic activation levels of the 95th highest percentile comprised between 97% and 100% of MVA. These electromyographic activation levels were significantly higher than the electromyographic activation levels obtained with the Four Normalization Tests.
Although the number of MVIC tests to normalize 12 shoulder muscles was increased compared with previous recommendations, the proposed method ensures that near-MVA (>90%) was obtained for a large proportion of participants (>90%). Moreover, because electromyographic activation levels of the 95th highest percentile were at least 97% of MVA, the identified combinations could reduce the interparticipant variability. The proposed combinations could help to improve electromyographic normalization and therefore reduce the misinterpretations regarding shoulder muscle activation levels.
List of abbreviations:MVA (maximum voluntary activation), MVIC (maximum voluntary isometric contraction)
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Published online: January 19, 2016
Supported by the Natural Sciences and Engineering Research Council of Canada, Médicus, and the Research Group in Biomedical Sciences and Technologies.
© 2016 by the American Congress of Rehabilitation Medicine