The relationships between skinfold, fatigue and the traditional and log-transformed electromyographic and mechanomyographic signal in the vastus lateralis and recuts femoris
Issue Date
2013-05-31Author
Cooper, Michael A.
Publisher
University of Kansas
Format
68 pages
Type
Thesis
Degree Level
M.S.Ed.
Discipline
Health, Sport and Exercise Sciences
Rights
This item is protected by copyright and unless otherwise specified the copyright of this thesis/dissertation is held by the author.
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Show full item recordAbstract
INTRODUCTION: The purpose of the present study was to examine possible correlations between skinfold thicknesses and the a terms from the EMGRMS- and MMGRMS-force relationships for the vastus lateralis (VL) and rectus femoris (RF) and EMG M-Wave (EMG M-wave) and MMG gross lateral movement (MMG GLM) of the VL and RF from a non-voluntary single evoked potential. In addition, correlations were calculated between the b terms form the EMGRMS- and MMGRMS-force relationships and the fatigue index from the Thorstensson protocol. METHODS: Forty healthy subjects (age = 21 ± 2 yrs., weight = 73.5 ± 13.2 kg, height = 1.7 ± 0.09 m) performed a 6-second isometric ramp contraction followed by transcutaneous electrical stimuli at rest and a 50-repetition fatigue protocol. EMG and MMG sensors were placed on the VL and RF on the center of the muscle belly with skinfold thickness assessed at the site of the electrodes. Transcutaneous stimuli were delivered to the femoral nerve via a bipolar surface electrode that was placed over the inguinal space to assess EMG M-wave and MMG GLM. Simple linear regression models were fit to the natural log-transformed EMGRMS and MMGRMS-force relationships. The b term and a term were calculated for each relationship. The fatigue index was calculated from the equation: ([Initial Peak Force - Final Peak Force]/Initial Peak Force) x 100. Pearson's product correlation coefficients were calculated comparing VL and RF skinfold thicknesses with the a terms from the EMGRMS-and MMGRMS-force relationships, EMG M-wave, and MMG GLM. In addition correlations were calculated comparing the b terms from the EMGRMS- and MMGRMS-force relationships terms for the VL and RF with the fatigue index. RESULTS: There were no significant correlations found between the a terms and the skinfold thicknesses for the RF (p = 0.614, r = -0.082) and VL (p = 0.507, r = 0.108) from the EMGRMS-force relationships and the RF (p = 0.508, r = 0.108) and VL (p = 0.546, r = 0.098) from the MMGRMS-force relationships. In contrast, there were significant correlations between skinfold thicknesses and the EMG M-waves for the RF (p = 0.002, r = -0.521) and VL (p = 0.005, r = -0.479) and for the MMG GLM for the RF (p = 0.031, r = -0.376) and VL (p = 0.004, r = -0.484). Finally, significant correlations were found between the b terms from the MMGRMS-force relationships for the VL (p = 0.007, r = 0.417) and RF (p = 0.014, r = 0.386) with the fatigue index. In addition, the b terms from the EMGRMS-force relationships for the RF (p = 0.017, r = 0.375) were correlated with the fatigue index, however, the b terms for the VL (p = 0.733, r = 0.056) were not correlated with the fatigue index. DISCUSSION: The correlations between the b terms and fatigue index suggested that the log-transformed MMGRMS-force relationship model may reflect muscle fiber type composition. Regarding the EMGRMS-force relationships, it is unclear why the b terms from the RF and not the VL were correlated with the fatigue index. The a terms from the log-transformed EMGRMS- and MMGRMS-force relationships were not correlated with skinfold thicknesses, whereas, the EMG M-wave and MMG GLM produced from non-voluntary evoked twitches were correlated with skinfold thicknesses.
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