Supplements to Clinical neurophysiology最新文献

This study assessed the accuracy of three automatic motor unit analysis algorithms--multi-motor unit analysis, decomposition quantitative EMG, and EMGtools--on a set of real EMG signals whose true composition was determined by manual decomposition. All three algorithms correctly identified all the MUs in signals with up to 5 active MUs, and most of the MUs in signals with up to 10 active MUs. The algorithms accurately estimated MUAP amplitudes and firing rates, but they estimated duration less accurately because of baseline noise. These findings support the validity and utility of these algorithms.

Poliomyelitis is a monophasic illness affecting lower motor neurons and individuals may describe new problems years after the initial weakness. We have studied 38 people with the post-polio syndrome over a 15-year period assessing a number of neuromuscular measures, including motor unit number estimation (MUNE). Twenty-five individuals reported progressive weakness but there was no objective change in MUNE and other measures. There was an association with reported weakness and initial deficits. There was a slow decline in MUNE values over time in both groups.

Quantitative EMG (QEMG) is a useful technique to diagnose subtle neuromuscular disorders. Automated QEMG techniques rely upon computer algorithms to extract motor unit action potentials (MUAPs). A number of different algorithms are available and we have compared the performance of three of them. We have also assessed a number of variables related to the operations performed by the algorithms, including marking of MUAP metrics, data acquisitions time, and effects of raising the high-pass filter. We have also assessed whether there are differences in MUAP metrics depending upon where the needle is placed in the muscle.

Although statistical MUNE has many positive attributes, it is inappropriate for use in multicenter ALS clinical trials. No other commonly used technique for MUNE possesses all the attributes necessary to be a valid and useful outcome measure in ALS trials. However, MUNE as a theoretical outcome measure remains extremely attractive and new techniques must be sought so that it can reach its full potential as a valid and reproducible outcome measure in ALS clinical trials.

Motor unit number estimation (MUNE) techniques--whether they reflect a true motor unit count or some related index--should not be confounded by changes in the neuromuscular system other than a decline in the number of functional motor units. In neurodegenerative conditions such as amyotrophic lateral sclerosis (ALS), there is evidence of changes in the excitability of motor axons. If changes in axon excitability confound a particular MUNE technique, this would influence the use of that technique in ALS patients. We hypothesized on the basis of computational models that changes in axon membrane excitability would change the outcome of a statistical MUNE test, even though the true number of motor units remained unchanged. To test the validity of the model predictions we induced changes in axon excitability of healthy control subjects by applying a polarizing current while simultaneously carrying out a statistical MUNE test. In a group of 7 subjects we found a significant difference in MUNE as a result of the change in axon excitability produced by the polarizing current (paired t-test, P < 0.05). We conclude that the statistical MUNE method is confounded by changes in axon excitability. Since increasing evidence shows that axon excitability is altered as part of the pathophysiological process underlying ALS, clinical researchers should be cautious when using statistical MUNE with this patient population.