PD, bipolar
EVENTS, CONTRACTION, RECRUITMENT, REGRESSIONS
Following data acquisition, the four separate filtered surface EMG signals from the VL were decomposed into their constituent motor unit action potential trains using the Precision Decomposition III (PD III) algorithm described by De Luca et al. (The output from the PD III algorithm consisted of firing times and four unique waveforms corresponding to four bipolar channels from the four electrode pairings for each motor unit. Using the PD III derived firing times of the identified motor units at the >90% accuracy threshold, the spike trigger averaging (STA) procedure was performed on each surface EMG signal, resulting in four representative STA motor unit action potential waveforms for each motor unit. The coefficient of variations of the peak‐to‐peak amplitudes from the STA motor unit action potential waveforms were calculated over time. The window length was 4 s and shifted over the surface of EMG signal using a step size of 1 s. The maximum correlation coefficients between STA and PD III derived waveforms were also calculated. For the STA motor unit action potential waveforms, the composite waveform created from the firing events was compared to the waveforms generated by the PD III algorithm (Hu et al., For each motor unit, two parameters (recruitment threshold [%MVC] and mean firing rate [pps]) were extracted at the targeted contraction level. Each motor unit's recruitment threshold was quantified as the percentage of the MVC corresponding to its first firing during the ascending portion of the trapezoidal contraction. Each motor unit's time‐varying mean firing rate was computed by passing each train of firings though a 1 s Hanning window. Linear regressions were applied on a participant‐by‐participant basis to calculate the slopes (pps/%MVC) and 