Closed-loop identification of the dynamic relation between surface EMG and torque at the human ankle

This work studies the dynamic relationship between the electrical activity produced in skeletal muscles and recorded using electromyogram(EMG), and torque at the healthy human ankle during isometric contractions. Subjects were instructed to voluntarily modulate their ankle torque by tracking a pseudo-random visual command signal. Impulse response functions (IRF) estimated between the EMG and torque records had an unphysiological anticipatory component suggesting that the estimated IRF was biased because the data were recorded in closed-loop. Applying a closed-loop identification algorithm that modeled the EMG-torque relation as a nonparametric impulse response function, and the noise as an autoregressive-moving-average process gave unbiased results. The EMG-torque IRF had second-order, low-pass, dynamics, whose properties varied with the mean torque.