Purpose: To test the accuracy, validity, reliability and sensitivity of an alternative method for the measure of TMS-assessed voluntary activation (VATMS) in the knee extensors. Methods: Ten healthy males (24 ± 5 years) completed a neuromuscular assessment protocol before and after a fatiguing isometric exercise: two sets of five contractions (50%, 62.5%, 75%, 87.5%, 100% Maximal Voluntary Contraction; MVC) with superimposed TMS-evoked twitches for calculation of VATMS using either the first 5 stimulations (1x5C) or all 10 (2x5C). This was performed on two separate occasions (between-day reliability). Accuracy and validity were compared with a routinely used protocol [i.e. 50%, 75%, and 100% of MVC (1x3C) performed three times (3x3C)]. Results: 95% confidence interval for estimated resting twitch, a key determinant of VATMS, was similar between 1x5C, 2x5C, and 3x3C but improved by six-fold when compared to 1x3C (P<0.05). In a fresh state, potentiated twitch force was unchanged following 1x5C but decreased following 2x5C (P<0.05). A recovery was found post-exercise but was smaller for 1x5C compared to 2x5C (P<0.05), with no difference between the latter two (P>0.05). Absolute reliability was strong enough for both 1x5C and 2x5C to depict a true detectable change in the sample’s VATMS following the fatiguing exercise (TEM < 3% at rest, <9% post-exercise) but 2x5C was marginally more sensitive to individual’s changes from baseline. Conclusion: Both 1x5C and 2x5C provide reliable measures of VATMS. However, 1x5C may hold stronger internal validity. Both protocols allow detection of ‘true’ changes in sample’s means but not individual scores following a fatiguing isometric exercise
|Number of pages||17|
|Publication status||Published - 6 Jun 2019|
Bibliographical note© 2019 Dekerle et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- Functional electrical stimulation
- Linear regression analysis
- Muscle contraction
- Statistical data