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Prediction of Muscle Performance During Dynamic Repetitive ExerciseA method for predicting human muscle performance was developed. Eight test subjects performed a repetitive dynamic exercise to failure using a Lordex spinal machine. Electromyography (EMG) data was collected from the erector spinae. Evaluation of the EMG data using a 5th order Autoregressive (AR) model and statistical regression analysis revealed that an AR parameter, the mean average magnitude of AR poles, can predict performance to failure as early as the second repetition of the exercise. Potential applications to the space program include evaluating on-orbit countermeasure effectiveness, maximizing post-flight recovery, and future real-time monitoring capability during Extravehicular Activity.
Document ID
20110006928
Acquisition Source
Johnson Space Center
Document Type
Preprint (Draft being sent to journal)
Authors
Byerly, D. L.
(NASA Johnson Space Center Houston, TX, United States)
Byerly, K. A.
Sognier, M. A.
(Universities Space Research Association Houston, TX, United States)
Squires, W. G.
(Texas Lutheran Coll. Seguin, TX, United States)
Date Acquired
August 25, 2013
Publication Date
January 1, 2002
Subject Category
Aerospace Medicine
Report/Patent Number
JSC-CN-7472
Report Number: JSC-CN-7472
Distribution Limits
Public
Copyright
Public Use Permitted.
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