Sample entropy can sensitively identify changes in biological signal regularity. The aim of this study was to investigate whether sample entropy could detect such change in human movement which may be attributable to fatigue or other factors. The regularity of kettlebell trajectories from simulated kettlebell sport competition performed by five experienced lifters was assessed using a novel moving window technique. Resultant entropy estimate trajectories indicate sensitivity to changes in regularity. Decrements in grip strength indicate this may be attributable to fatigue though other possibilities exist. The ability to easily model the resultant entropy trajectories is also demonstrated. The technique holds potential for use by practitioners though more work is required before implementation.
Taylor, Paul G.; Ross, James A.; and Keogh, Justin W. L .
"INVESTIGATING THE USE OF SAMPLE ENTROPY TO DETECT FATIGUE,"
ISBS Proceedings Archive: Vol. 35:
1, Article 124.
Available at: https://commons.nmu.edu/isbs/vol35/iss1/124