Correction: Adeel et al. Oxygen Consumption (VO<sub>2</sub>) and Surface Electromyography (sEMG) during Moderate-Strength Training Exercises. <i>Int. J. Environ. Res. Public Health</i> 2022, <i>19</i>, 2233. [PDF]
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Legendre Polynomial Fitting-Based Permutation Entropy Offers New Insights into the Influence of Fatigue on Surface Electromyography (sEMG) Signal Complexity. [PDF]
Jabloun M, Buttelli O, Ravier P.
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Quantitative assessment of muscle fatigue during rowing ergometer exercise using wavelet analysis of surface electromyography (sEMG). [PDF]
Daniel N +3 more
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Real-time continuous assessment of fatigue from surface electromyography with deep learning for training load regulation in elite cyclists. [PDF]
Zhai R +5 more
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Muscle Fatigue Investigation Using sEMG Signals and a DAQ Card Data Acquisition System in LabVIEW. [PDF]
Krawiecki Z, Kuwałek P.
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Association Between Interlimb Asymmetry in Normalized Vastus Medialis sEMG Amplitude and Functional Mobility in Patients with Post-Traumatic Knee Contracture: A Cross-Sectional Study. [PDF]
Kan XL +9 more
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An exploratory, in-field, multimodal assessment of cervical function in adults following to high-altitude trekking with light backpack. [PDF]
Perpetuini D +5 more
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Electrophysiological Signatures of Sarcopenia: A Systematic Review of sEMG Features, Fatigue Indices and AI-Based Classifiers. [PDF]
Villanueva-De-Luna KV +6 more
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Surface Electromyography-Based Evaluation of Neuromuscular Recruitment Under Different Resistance Conditions During Water-Resistance Rowing. [PDF]
Sha L, Chiu WH.
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Feature-Level Fusion of Surface Electromyography and Mechanomyography Signals for MVC-Normalized Shoulder Abduction Force-Level Classification in Healthy Adults. [PDF]
Zhou C +7 more
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