ArticleSensors (Basel, Switzerland)2022
A Simulation Study to Assess the Factors of Influence on Mean and Median Frequency of sEMG Signals during Muscle Fatigue.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed.
- Sport specific differences in upper limb median frequency responses during isometric push and pull tasks in volleyball and fitness athletes.BMC sports science, medicine & rehabilitation · 2026Article
- Acute Physiological Responses to Prolonged Sedentary Behavior: Impact on Cardiovascular Function and Muscle Activity in Young Adults.Journal of functional morphology and kinesiology · 2026Article
- Continuous wavelet transform-based analysis of shoulder muscle fatigue during dynamic abduction: a surface electromyography study.Frontiers in bioengineering and biotechnology · 2026Article
- A practical assessment of hamstring muscle endurance and fatigue using the maximum-speed single-leg bridge test.BMC sports science, medicine & rehabilitation · 2025Article
- Impact of mental fatigue on lower limb biomechanics and non-contact anterior cruciate ligament injury risk in basketball players during the stop-jump task: a self-controlled trial.Journal of orthopaedic surgery and research · 2025Article
- Electromyography Signal Acquisition, Filtering, and Data Analysis for Exoskeleton Development.Sensors (Basel, Switzerland) · 2025Review
- Altered Muscle-Brain Connectivity During Left and Right Biceps Brachii Isometric Contraction Following Sleep Deprivation: Insights from PLV and PDC.Sensors (Basel, Switzerland) · 2025Article
- Quantitative musculoskeletal monitoring and analysis in aquatic rehabilitation.Frontiers in electronics · 2025Article
- Biomechanical mechanisms of multidirectional dynamic compensatory muscle fatigue induced by abnormal cervical curvature: a cross-sectional case-control study based on surface electromyography and Cobb angle.Frontiers in sports and active living · 2025Article
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Abstract
Mean and Median frequency are typically used for detecting and monitoring muscle fatigue. These parameters are extracted from power spectral density whose estimate can be obtained by several techniques, each one characterized by advantages and disadvantages. Previous works studied how the implementation settings can influence the performance of these techniques; nevertheless, the estimation results have never been fully evaluated when the power density spectrum is in a low-frequency zone, as happens to the surface electromyography (sEMG) spectrum during muscle fatigue. The latter is therefore the objective of this study that has compared the Welch and the autoregressive parametric approaches on synthetic sEMG signals simulating severe muscle fatigue. Moreover, the sensitivity of both the approaches to the observation duration and to the level of noise has been analyzed. Results showed that the mean frequency greatly depends on the noise level, and that for Signal to Noise Ratio (SNR) less than 10dB the errors make the estimate unacceptable. On the other hand, the error in calculating the median frequency is always in the range 2-10 Hz, so this parameter should be preferred in the tracking of muscle fatigue. Results show that the autoregressive model always outperforms the Welch technique, and that the 3rd order continuously produced accurate and precise estimates; consequently, the latter should be used when analyzing severe fatiguing contraction.
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