Modeling the impulse response between pairs of EMG signals to estimate conduction delay distribution

Mean electromyogram (EMG) conduction delay is often estimated as the average time delay between two surface EMG recordings arranged along the conduction path. It has previously been shown that the complete distribution of conduction delays can be estimated from the impulse response relating the “upstream” EMG recording to the “downstream” recording. In this work, we examined regularized least squares methods for estimating the impulse response, namely the pseudo-inverse with small singular values discarded and post hoc lowpass filtering. Performance was evaluated by training the model to one recording, then testing on others. Correlation between model-predicted EMG and measured EMG was assessed for 36 subjects, using EMG recordings with 5 mm inter-electrode spacing. The best correlation was 0.86, on average, for both regularization methods. We additionally compared the mean conduction delay computed from the “gold standard” cross-correlation method to the peak time of the impulse response. The best models differed by 0.01 ms, on average, for both regularization methods. Nonetheless, the impulse responses exhibited excessive energy near zero time, causing delay distribution estimates to exhibit high probabilities at unphysiological short time delays. Inter-electrode spacing larger than 5 mm may be required to alleviate this limitation.