Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10431741 | Journal of Biomechanics | 2015 | 4 Pages |
Abstract
The aim of this study was to establish how well a three-parameter sigmoid exponential function, DIFACT, follows experimentally obtained voluntary neural activation-angular velocity profiles and how robust it is to perturbed levels of maximal activation. Six male volunteers (age 26.3±2.73 years) were tested before and after an 8-session, 3-week training protocol. Torque-angular velocity (T-Ï) and experimental voluntary neural drive-angular velocity (%VA-Ï) datasets, obtained via the interpolated twitch technique, were determined from pre- and post-training testing sessions. Non-linear regression fits of the product of DIFACT and a Hill type tetanic torque function and of the DIFACT function only were performed on the pre- and post-training T-Ï and %VA-Ï datasets for three different values of the DIFACT upper bound, αmax, 100%, 95% & 90%. The determination coefficients, R2, and the RMS of the fits were compared using a two way mixed ANOVA and results showed that there was no significant difference (p<0.05) due to changing αmax values indicating the DIFACT remains robust to changes in maximal activation. Mean R2 values of 0.95 and 0.96 for pre- and post-training sessions show that the maximal voluntary torque function successfully reproduces the T-Ï raw dataset.
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Biomedical Engineering
Authors
Dimitrios Voukelatos, Matthew TG Pain,