Motor Units Discriminated From High-density, Surface Electromyography Require Careful Scrutiny.

Abstract

High-density, surface electromyography (EMG) allows concurrent recording of motor unit (MU) activity by increasing the recording area and the number of recording sites. The recorded signal comprises overlapping MU action potentials, some of which can be identified with a decomposition algorithm. However, such analyses often produce results that contradict the classical findings on motor unit discharge characteristics. PURPOSE: To evaluate the quality of the interspike intervals (ISIs) extracted from a high-density surface EMG recording by a decomposition algorithm. METHODS: Muscle activity was recorded using high-density, surface EMG (4x8 grid with a 10 mm interelectrode distance) in 10 persons with multiple sclerosis during steady, isometric dorsiflexor contractions on their less-affected limb. The target force was 10% of maximum. Custom Matlab software was used to perform a convolution kernel compensation model and a blind-source separation algorithm to discriminate individual MUs from EMG recordings. The discharge times (DT) from the discriminated MUs were used to calculate the ISIs (ISI = DTn-DTn-1). For each MU, the average ISI, average coefficient of variation for ISI (ISICV), kurtosis for the distribution of ISIs, and skewness for the distribution of ISIs was calculated. ISIs outside of the range of 25 ms - 400 ms were deemed inaccurate and removed from the data and the same analyses were repeated. Data are reported as mean [95% CI]. RESULTS: The ISIs (n = 33,980; 303 [285-321] per MU) of 113 MUs were examined. Before removing ISIs that did not meet the inclusion criteria (25 - 400 ms), the average ISI was 136 ms [123 - 151 ms], the average ISICV was 72% [50 - 95%], the average kurtosis was 53.5 [39.1 - 67.8], and the average skewness was 4.4 [3.5 - 4.3]. On average, 3.34% (range 0 - 31%) of the ISIs per MU were outside the acceptable range. After ISI removal, the average ISI was 120 ms [114 - 125 ms], the average ISICV was 28% [26 - 31%], the average kurtosis was 11.0 [8.9 - 13.2], and the average skewness was 1.95 [1.70 - 2.20]. Most removed ISIs were <25 ms. CONCLUSION: The findings quantify the extent to which MU discharge times extracted from high-density, surface EMG recordings with an automatic decomposition algorithm can be confounded by discrimination errors.