| A noninvasive, log-transform method for fiber type discrimination using mechanomyography. | |
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MedLine Citation:
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PMID: 20172740 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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This study examined the log-transformed mechanomyographic (MMG(RMS)) and electromyographic (EMG(RMS)) amplitude vs. force relationships for aerobically-trained (AT), resistance-trained (RT), and sedentary (SED) individuals. Subjects performed isometric ramp contractions from 5% to 90% maximal voluntary contraction. Muscle biopsies were collected and thigh skinfolds, MMG and EMG were recorded from the vastus lateralis muscle. Linear regression models were fit to the log-transformed EMG(RMS) and MMG(RMS) vs. force relationships. The slope (b coefficient) and the antilog of the y-intercept (a coefficient) were calculated. The AT group had the highest percentage of type I fiber area, the RT group had the highest percentage of type IIa fiber area, and the SED group had the highest percentage of type IIx fiber area. The a coefficients were higher for the AT group than the RT and SED groups in both the MMG(RMS) and EMG(RMS) vs. force relationships, whereas the b coefficients were lower for the AT group than the RT and SED groups only in the MMG(RMS) vs. force relationship. The group differences among the a coefficients may have reflected subcutaneous fat acting as a filter thereby reducing EMG(RMS) and MMG(RMS). The lower b coefficients for the AT group in the MMG(RMS) patterns may have reflected fiber area-related differences in motor unit activation strategies. |
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Authors:
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Trent J Herda; Terry J Housh; Andrew C Fry; Joseph P Weir; Brian K Schilling; Eric D Ryan; Joel T Cramer |
Publication Detail:
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Type: Journal Article Date: 2010-02-21 |
Journal Detail:
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Title: Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology Volume: 20 ISSN: 1873-5711 ISO Abbreviation: J Electromyogr Kinesiol Publication Date: 2010 Oct |
Date Detail:
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Created Date: 2010-08-02 Completed Date: 2011-01-04 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9109125 Medline TA: J Electromyogr Kinesiol Country: England |
Other Details:
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Languages: eng Pagination: 787-94 Citation Subset: IM |
Copyright Information:
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Published by Elsevier Ltd. |
Affiliation:
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Department of Health and Exercise Science, Biophysics Laboratory, University of Oklahoma, Norman, Oklahoma, USA. |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Algorithms* Humans Isometric Contraction / physiology* Male Muscle Fibers, Skeletal / classification*, physiology* Muscle, Skeletal / cytology*, physiology* Myography / methods* Young Adult |
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