Estimating motor unit discharge patterns from high-density surface electromyogram

Abstract

Objective: We systematically tested the capability of the Convolution Kernel Compensation (CKC) method to identify motor unit (MU) discharge patterns from the simulated and experimental surface electromyogram (sEMG) during low-force contractions.

Methods: sEMG was detected with a grid of 13 x 5 electrodes. In simulated signals with 20 dB signal-to-noise ratio, 11+/-3 out of 63 concurrently active MUs were identified with sensitivity >95% in the estimation of their discharge times. In experimental signals recorded at 0-10% of the maximal force, the discharge patterns of (range) 11-19 MUs (abductor pollicis; n=8 subjects), 9-17 MUs (biceps brachii; n=2), 7-11 MUs (upper trapezius; n=2), and 6-10 MUs (vastus lateralis; n=2) were identified. In the abductor digiti minimi muscle of one subject, the decomposition results from concurrently recorded sEMG and intramuscular EMG (iEMG) were compared; the two approaches agreed on 98+/-1% of MU discharges.

Conclusion: It is possible to identify the discharge patterns of several MUs during low-force contractions from high-density sEMG.

Significance: sEMG can be used for the analysis of individual MUs when the application of needles is not desirable or in combination with iEMG to increase the number of sampled MUs.