Estimating motor unit discharge patterns from high-density surface electromyogram

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 partterns 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 call 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 or sampled MUs. (C) 2009 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.