Visualizing muscular fatigue during running exercises with electromyography-derived variables.

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dc.contributor.advisorJean, B. Randall.
dc.contributor.advisorRylander, Jonathan.
dc.creatorLewis, Adam David, 1992-
dc.date.accessioned2020-09-09T13:35:17Z
dc.date.available2020-09-09T13:35:17Z
dc.date.created2020-05
dc.date.issued2020-04-20
dc.date.submittedMay 2020
dc.date.updated2020-09-09T13:35:18Z
dc.description.abstractRunners commonly face injuries due to fatigue and overuse. However, it is difficult to know when the body is too fatigued to continue a task without damage. This study attempted to observe if fatigue occurred in the leg muscles, specifically both gastrocnemius muscles and the vastus lateralis, during a running trial using electromyography to record the muscle activation signals. Post-processing methods calculated four parameters to detect fatigue: mean frequency, root mean square amplitude, 2nd order Dimitrov spectral index, and fractal dimension. A validation trial with calf raises proved the reliability of these parameters. Results of the running trials showed that both gastrocnemius muscles had their mean frequency and fractal dimension increase, while the root mean square and the spectral index decreased. The vastus lateralis only differed in the spectral index parameter from the gastrocnemius results. These results indicate that muscle recruitment differs in low workload, endurance tasks than strength-based exercises, but also requires future work to corroborate these results.
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/2104/11045
dc.language.isoen
dc.rights.accessrightsWorldwide access
dc.subjectElectromyography. Muscle fatigue. SEMG. Running. Mean frequency. Fractal dimension.
dc.titleVisualizing muscular fatigue during running exercises with electromyography-derived variables.
dc.typeThesis
dc.type.materialtext
thesis.degree.departmentBaylor University. Dept. of Electrical & Computer Engineering.
thesis.degree.grantorBaylor University
thesis.degree.levelMasters
thesis.degree.nameM.S.E.C.E.

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