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Critical Reviews™ in Biomedical Engineering
SJR: 0.26 SNIP: 0.375 CiteScore™: 1.4

ISSN Druckformat: 0278-940X
ISSN Online: 1943-619X

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Critical Reviews™ in Biomedical Engineering

DOI: 10.1615/CritRevBiomedEng.v38.i5.30
pages 467-485

A Review of Clinical Quantitative Electromyography

Charles Farkas
Department of Systems Design Engineering, University of Waterloo, Canada
Andrew Hamilton-Wright
Department of Mathematics and Computer Science, Mount Allison University, New Brunswick, Canada
Hossein Parsaei
Department of Systems Design Engineering, University of Waterloo, Canada
Daniel W. Stashuk
Department of Systems Design Engineering, University of Waterloo, Canada

ABSTRAKT

Information regarding the morphology of motor unit potentials (MUPs) and motor unit firing patterns can be used to help diagnose, treat, and manage neuromuscular disorders. In a conventional electromyographic (EMG) examination, a clinician manually assesses the characteristics of needle-detected EMG signals across a number of distinct needle positions and forms an overall impression of the condition of the muscle. Such a subjective assessment is highly dependent on the skills and level of experience of the clinician, and is prone to a high error rate and operator bias. Quantitative methods have been developed to characterize MUP waveforms using statistical and probabilistic techniques that allow for greater objectivity and reproducibility in supporting the diagnostic process. In this review, quantitative EMG (QEMG) techniques ranging from simple reporting of numeric MUP values to interpreted muscle characterizations are presented and reviewed in terms of their clinical potential to improve status quo methods. QEMG techniques are also evaluated in terms of their suitability for use in a clinical decision support system based on previously established criteria. Aspects of prototype clinical decision support systems are then presented to illustrate some of the concepts of QEMG-based decision making.


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