DocumentCode
746381
Title
A technique to track individual motor unit action potentials in surface EMG by monitoring their conduction velocities and amplitudes
Author
Beck, Rebecca B J ; Houtman, Caroline J. ; Malley, Mark J O ; Lowery, Madeleine M. ; Stegeman, Dick F.
Author_Institution
Dept. of Clinical Neurophysiol., Univ. Med. Centre Nijmegen, Netherlands
Volume
52
Issue
4
fYear
2005
fDate
4/1/2005 12:00:00 AM
Firstpage
622
Lastpage
629
Abstract
The speed of propagation of an action potential along a muscle fiber, its conduction velocity (CV), can be used as an indication of the physiological or pathological state of the muscle fiber membrane. The motor unit action potential (MUAP), the waveform resulting from the spatial and temporal summation of the individual muscle fiber action potentials of that motor unit (MU), propagates with a speed referred to as the motor unit conduction velocity (MUCV). This paper introduces a new algorithm, the MU tracking algorithm, which estimates MUCVs and MUAP amplitudes for individual MUs in a localized MU population using SEMG signals. By tracking these values across time, the electrical activity of the localized MU pool can be monitored. An assessment of the performance of the algorithm has been achieved using simulated SEMG signals. It is concluded that this analysis technique enhances the suitability of SEMG for clinical applications and points toward a future of noninvasive diagnosis and assessment of neuromuscular disorders.
Keywords
biomembranes; electromyography; medical signal processing; patient diagnosis; electrical activity; individual motor unit action potentials; motor unit conduction velocity; motor unit tracking algorithm; muscle fiber membrane; neuromuscular disorders; noninvasive diagnosis; surface EMG; Amplitude estimation; Biomedical monitoring; Biomembranes; Electromyography; Fatigue; Medical diagnostic imaging; Muscles; Noninvasive treatment; Pathology; Signal analysis; Motor unit conduction velocity; peak velocity; surface electromyography; Action Potentials; Algorithms; Diagnosis, Computer-Assisted; Electromyography; Motor Neurons; Muscle Fibers; Muscle, Skeletal; Neural Conduction;
fLanguage
English
Journal_Title
Biomedical Engineering, IEEE Transactions on
Publisher
ieee
ISSN
0018-9294
Type
jour
DOI
10.1109/TBME.2005.844027
Filename
1408119
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