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Updated: Aug 20, 2025

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Determining The Electromyographic Fatigue Threshold Following a Single Visit Exercise Test
Published on: July 27, 2015
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Variability of Time- and Frequency-Domain Surface Electromyographic Measures in Non-Fatigued Shoulder Muscles
Hamad Nasser Alasim1, Ashish D Nimbarte2
1Mechanical and Industrial Engineering Department, College of Engineering, Majmaah University, Majmaah, Saudi Arabia.
IISE Transactions on Occupational Ergonomics and Human Factors
|November 22, 2022
Summary
Surface electromyography (sEMG) measures are used to assess localized muscle fatigue (LMF). However, work-related factors can affect baseline sEMG readings, impacting fatigue assessment accuracy.
Area of Science:
- Ergonomics
- Biomedical Engineering
- Occupational Health
Background:
- Localized Muscle Fatigue (LMF) assessment often relies on surface electromyography (sEMG) measures.
- Quantifying LMF typically involves comparing fatigued states to a "fresh" or no-fatigue baseline.
- The validity of this baseline is crucial for accurate LMF prediction and monitoring.
Purpose of the Study:
- To investigate the influence of work-related factors on baseline sEMG measures.
- To provide guidance on the variability of sEMG measures in non-fatigued states.
- To enhance the accuracy of LMF assessment in occupational settings.
Main Methods:
- Analysis of time- and frequency-domain sEMG measures.
- Evaluation of sEMG data collected under various occupational conditions.
- Statistical assessment of variability in baseline sEMG signals.
Main Results:
- Baseline sEMG measures are significantly affected by work-related factors.
- Commonly used time- and frequency-domain sEMG measures exhibit considerable variability in the absence of fatigue.
- These findings challenge the assumption of a stable "fresh" sEMG reference.
Conclusions:
- The "fresh" condition reference for sEMG-based LMF assessment is not always reliable.
- Ergonomists must account for work-related variability in baseline sEMG for accurate LMF assessment.
- Improved understanding of sEMG variability can lead to more precise occupational fatigue monitoring.

