Literature DB >> 21175409

A review of clinical quantitative electromyography.

Charles Farkas1, Andrew Hamilton-Wright, Hossein Parsaei, Daniel W Stashuk.   

Abstract

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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Year:  2010        PMID: 21175409     DOI: 10.1615/critrevbiomedeng.v38.i5.30

Source DB:  PubMed          Journal:  Crit Rev Biomed Eng        ISSN: 0278-940X


  5 in total

Review 1.  Clinical Measures of Disease Progression in Amyotrophic Lateral Sclerosis.

Authors:  Seward B Rutkove
Journal:  Neurotherapeutics       Date:  2015-04       Impact factor: 7.620

2.  Recording characteristics of electrical impedance-electromyography needle electrodes.

Authors:  H Kwon; J F Di Cristina; S B Rutkove; B Sanchez
Journal:  Physiol Meas       Date:  2018-05-22       Impact factor: 2.833

Review 3.  A systematic recurrent theme analysis of the reported limitations of facial electromyography.

Authors:  L Geoghegan; R M Kwasnicki; S Kanabar; D Pethers; C Nduka
Journal:  Ann Med Surg (Lond)       Date:  2018-07-11

4.  An Android Application for Estimating Muscle Onset Latency using Surface EMG Signal.

Authors:  M Karimpour; H Parsaei; Z Rojhani-Shirazi; R Sharifian; F Yazdani
Journal:  J Biomed Phys Eng       Date:  2019-04-01

5.  Can Wavelet Denoising Improve Motor Unit Potential Template Estimation?

Authors:  Hasanzadeh S H; Parsaei H; Movahedi M M
Journal:  J Biomed Phys Eng       Date:  2020-04-01
  5 in total

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