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Surface electromyograms (sEMG) of major leg muscles, recorded during treadmill walking, were analyzed to quantify the improvement in functional ambulation facilitated by epidural spinal cord stimulation (ESCS) compared with partial weight-bearing therapy (PWBT) alone. Due to the nonstationary and stochastic properties of the signal, advanced algorithms were developed to analyze sEMG recorded during this quasi-cyclic dynamic movement. Principal component analysis (PCA) and Cohen class time-frequency spectral analysis distinguished changes in the pattern of sEMG due to ESCS. Moreover, the results from both analysis techniques demonstrate ESCS improved muscle activation patterns during treadmill walking beyond that afforded by PWBT alone, providing an improved temporal match to normal EMG patterns.