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Motor unit number estimation: sample size considerations
M Slawnych1, C Laszlo, C Hershler
1Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada.
Abstract:
A computer model of the motor unit number estimation procedure was developed to evaluate the sampling error associated with estimates of the number of motor units in muscles. Two different distributions were used to model the motor unit amplitude distribution and were chosen in such a manner that they qualitatively matched the distributions observed under both normal and neurogenic conditions. As expected, the results indicated that estimation error decreases as a function of sample size. However, the relationship between these two variables was nonlinear in the sense that successive increases in sample size lead to progressively smaller decreases in estimation error. The results also indicated that the shape of the motor unit amplitude distribution plays an important role. Specifically, estimates obtained using the distribution modeling normal muscle were generally higher than the actual number of motor units in the muscle, which was not the case for the distribution modeling neurogenic muscle. In addition, the neurogenic distribution was associated with much smaller estimation error, suggesting that motor unit number estimation is well suited to the analysis of neurogenic disease processes.