Volume 36, Issue 1 pp. 62-70
Main Article

Motor unit number estimates and quantitative motor unit analysis in healthy subjects and patients with amyotrophic lateral sclerosis

Shaun G. Boe PhD

Corresponding Author

Shaun G. Boe PhD

School of Kinesiology, University of Western Ontario, London, Ontario, Canada

School of Kinesiology, University of Western Ontario, London, Ontario, CanadaSearch for more papers by this author
Daniel W. Stashuk PhD

Daniel W. Stashuk PhD

Department of Systems Design Engineering, University of Waterloo, Waterloo, Ontario, Canada

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Timothy J. Doherty MD, PhD

Timothy J. Doherty MD, PhD

School of Kinesiology, University of Western Ontario, London, Ontario, Canada

Departments of Clinical Neurological Sciences and Rehabilitation Medicine, University of Western Ontario, University Hospital, London Health Sciences Centre, 339 Windermere Road, London, Ontario N6A 5A5, Canada

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First published: 23 April 2007
Citations: 32

Abstract

Limitations associated with global measures of function in patients with amyotrophic lateral sclerosis (ALS) and the qualitative nature of needle electromyography have stimulated the development of alternate means of monitoring disease severity and progression in ALS. Thus, the objective of this study was to examine the ability of one these techniques, decomposition-based quantitative electromyography (DQEMG), to obtain electrophysiological data, including motor unit number estimates (MUNEs), from a group of patients with ALS. The first dorsal interosseous and biceps brachii muscles were studied in 10 healthy subjects and 9 patients with ALS. Following the acquisition of a maximum M wave, needle- and surface-detected EMGs were collected simultaneously during 30-second contractions performed at 10% of the maximum voluntary contraction force to obtain motor unit potential (MUP) trains. DQEMG was then used to extract the surface-detected MUP associated with each MUP train, the mean size of which was divided into the maximum M wave to obtain a MUNE. The results suggest that quantitative electrophysiological data obtained using DQEMG are representative of the pathophysiological changes in the lower motor system in ALS patients, supporting its use in studies documenting the natural history and progression of the disease. Muscle Nerve, 2007

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