Literature DB >> 15876628

Can standard surface EMG processing parameters be used to estimate motor unit global firing rate?

Ping Zhou1, William Zev Rymer.   

Abstract

The relations between motor unit global firing rates and established quantitative measures for processing the surface electromyogram (EMG) signals were explored using a simulation approach. Surface EMG signals were simulated using the reported properties of the first dorsal interosseous muscle in man, and the models were varied systematically, using several hypothetical relations between motor unit electrical and force output, and also using different motor unit firing rate strategies. The utility of using different EMG processing parameters to help estimate global motor unit firing rate was evaluated based on their relations to the number of motor unit action potentials (MUAPs) in the simulated surface EMG signals. Our results indicate that the relation between motor unit electrical and mechanical properties, and the motor unit firing rate scheme are all important factors determining the form of the relation between surface EMG amplitude and motor unit global firing rate. Conversely, these factors have less impact on the relations between turn or zero-crossing point counts and the number of MUAPs in surface EMG. We observed that the number of turn or zero-crossing points tends to saturate with the increase in the MUAP number in surface EMG, limiting the utility of these measures as estimates of MUAP number. The simulation results also indicate that the mean or median frequency of the surface EMG power spectrum is a poor indicator of the global motor unit firing rate.

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Year:  2004        PMID: 15876628     DOI: 10.1088/1741-2560/1/2/005

Source DB:  PubMed          Journal:  J Neural Eng        ISSN: 1741-2552            Impact factor:   5.379


  4 in total

1.  Accuracy assessment of CKC high-density surface EMG decomposition in biceps femoris muscle.

Authors:  H R Marateb; K C McGill; A Holobar; Z C Lateva; M Mansourian; R Merletti
Journal:  J Neural Eng       Date:  2011-10-06       Impact factor: 5.379

2.  A simulation-based analysis of motor unit number index (MUNIX) technique using motoneuron pool and surface electromyogram models.

Authors:  Xiaoyan Li; William Zev Rymer; Ping Zhou
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2012-04-13       Impact factor: 3.802

3.  Multichannel Surface EMG Decomposition Based on Measurement Correlation and LMMSE.

Authors:  Yong Ning; Yuming Zhao; Akbarjon Juraboev; Ping Tan; Jin Ding; Jinbao He
Journal:  J Healthc Eng       Date:  2018-06-28       Impact factor: 2.682

4.  Characteristic Variation of Electromechanical Delay After the Botulinum Toxin Injection in Spastic Biceps Brachii Muscles.

Authors:  Sourav Chandra; Babak Afsharipour; William Z Rymer; Nina L Suresh
Journal:  Front Neurol       Date:  2022-02-10       Impact factor: 4.003

  4 in total

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