Statistical motor unit number estimation assuming a binomial distribution

The statistical method of motor unit number estimation (MUNE) uses the natural stochastic variation in a muscle's compound response to electrical stimulation to obtain an estimate of the number of recruitable motor units. The current method assumes that this variation follows a Poisson distribution. We present an alternative that instead assumes a binomial distribution. Results of computer simulations and of a pilot study on 19 healthy subjects showed that the binomial MUNE values are considerably higher than those of the Poisson method, and in better agreement with the results of other MUNE techniques. In addition, simulation results predict that the performance in patients with severe motor unit loss will be better for the binomial than Poisson method. The adapted method remains closer to physiology, because it can accommodate the increase in activation probability that results from rising stimulus intensity. It does not need recording windows as used with the Poisson method, and is therefore less user-dependent and more objective and quicker in its operation. For these reasons, we believe that the proposed modifications may lead to significant improvements in the statistical MUNE technique.