In human movement research, discrete measures; such as peak knee flexion angle, are often used to quantify differences between healthy and injured populations. These discrete time points provide the joint motion behavior at one instant in time and do not capture the overall dynamics of the joint motion. To better capture the change joint dynamics we aim to use both the Fast Fourier Transform and Hilbert Transform analyses to analyze the spectral and phasic components of the waveforms.
In the proposed study, we will compute the frequency and phase angle components of healthy and anterior cruciate ligament (ACL) reconstructed individuals' knee biomechanics during running. We will then use bootstrapping analysis to compare and identify differences between the distribution of the frequency and phase angle metrics between the healthy and ACL reconstructed populations. These differences in frequency and phase angle metrics among the two populations will be used to identify individuals at-risk for ACL injury and help determine how to develop more effective rehabilitation programs that are important objectives in the athletic arena.
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