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The purpose of the current study was to examine the influence of lower limb muscle fatigue on the mechanics of the knee joint during an athletic cutting task. A biomechanical methodology was utilized to examine 12 recreationally active females, who cycled through a fatigue-inducing protocol, using a slideboard, followed by the performance of five maximal cuts, until fatigue resulted in trial termination. 3D motion capture was utilized to capture full body movements and changing joint angles of the hip, knee and ankle during the weight acceptance of the cutting maneuver. A force plate was used to record the ground reaction forces of the participants during weight acceptance of the athletic cut. Lastly, surface electromyography monitored the muscle activity of nine muscles on the dominant leg of the participants. Repeated measures ANOVA (p<0.05), with Tukey’s significant post hoc test, was used to determine significance of the main effect of time on the measured variables. Analysis of the kinematic data revealed that, as fatigue progressed, hip and knee flexion angle significantly decreased during weight acceptance. Kinetic data revealed that peak anterior-posterior shear force significantly increased, and medial-lateral impulse of force significantly decreased, as participants progressed through the fatiguing protocol. Finally, surface electromyography data showed an overall significant decrease in muscle activation from the beginning to the end of trial, however, further investigation of pairwise comparisons indicated that, from 60-100% of the trial, muscle activation significantly increased. This work contributes to the body of work concerning exercise induced muscle fatigue and provides further insight into the underlying mechanism of acute injury during heightened fatigued states. The knowledge gained from this study can be used to advise and improve training prescription and monitoring strategies.
Santos, Sara Olivia, "Examining the influence of muscle fatigue on knee joint mechanics during an athletic cutting task" (2019). Electronic Theses and Dissertations. 7734.