Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/11918
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Type: Journal article
Title: A comparison of cross-correlation and surface EMG techniques used to quantify motor unit synchronization in humans
Author: Semmler, J.
Nordstrom, M.
Citation: Journal of Neuroscience Methods, 1999; 90(1):47-55
Publisher: ELSEVIER SCIENCE BV
Issue Date: 1999
ISSN: 0165-0270
1872-678X
Abstract: Two methods used to estimate the strength of motor unit (MU) synchronization in a muscle are the direct cross-correlation of MU discharge times, and averaging of the surface electromyogram (SEMG) with respect to discharge of a reference MU. Although indirect, the latter approach has the advantage that a global estimate of MU synchrony can be obtained quickly and easily. The two methods are generally regarded as providing equivalent information on the extent of MU synchronization in a muscle, but this proposition has not previously been tested quantitatively. In the present study, we used both the SEMG technique (189 MUs) and cross-correlation of MU discharge (498 MU pairs) to estimate MU synchrony in 28 first dorsal interosseus (FDI) muscles from 16 subjects. Despite considerable overlap in the identity of MUs used to quantify synchrony with each method, linear regression revealed no significant correlation between the estimates of MU synchronization in FDI muscles obtained with the two techniques (r2= 0.04, n = 28). This discrepancy was not due to insufficient sampling of the MU population with the cross-correlation method, although we found evidence for a non-uniform tendency for synchronous discharge in two of 13 motor units providing sufficient data for the analysis. The most likely explanation for the discrepancy between the estimates of MU synchrony is that methodological problems with the SEMG technique limit its accuracy. These problems are difficult to avoid under normal experimental conditions, and we conclude that the SEMG method is not reliable for quantitative comparisons of MU synchrony between muscles and subjects.
Keywords: Motor Neurons
Humans
Electromyography
Linear Models
Surface Properties
Time Factors
Adolescent
Adult
Middle Aged
DOI: 10.1016/S0165-0270(99)00069-2
Published version: http://dx.doi.org/10.1016/s0165-0270(99)00069-2
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