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Updated: Sep 10, 2026
Determining The Electromyographic Fatigue Threshold Following a Single Visit Exercise Test
Published on: July 27, 2015
Wavelet-Based Electromyographic and Mechanomyographic Intensity Responses to Fatiguing Tasks Anchored to a Rating of
Dolores G Ortega1,2, Robert W Smith3, Jocelyn E Arnett2
1Department of Kinesiology, California State University, Fullerton, Fullerton, California.
Abstract:
Ortega, DG, Smith, RW, Arnett, JE, Neltner, TJ, Roberts, TD, Pioske, JS, Schmidt, RJ, and Housh, TJ. Wavelet-based electromyographic and mechanomyographic intensity responses to fatiguing tasks anchored to a rating of perceived exertion versus torque. J Strength Cond Res XX(X): 000-000, 2026-This study used wavelet analyses to examine the effects of anchor scheme on electromyographic (EMG) and mechanomyographic (MMG) intensity. Twelve men (age = 20.9 ± 2.2 years) performed maximal voluntary isometric contractions (MVICs) before and after sustained, isometric forearm flexion tasks anchored to a rating of perceived exertion (RPE) of 4 (RPE4FT) and the torque (TRQ4FT) that corresponded to an RPE of 4. Wavelet analyses were used to decompose the EMG and MMG signals recorded from the biceps brachii during the MVICs onto sets of 11 nonlinearly scaled Cauchy wavelets. Repeated measures analyses of variance were used to analyze the EMG and MMG intensity data, with significance set at p ≤ 0.05. After the RPE4FT, EMG intensity decreased (p = 0.004 to 0.047) at wavelet bands 5 and 8-11. After the TRQ4FT, EMG intensity increased (p = 0.009) at wavelet band 1 and decreased (p < 0.001 to p = 0.047) at wavelet bands 5-11. The MMG intensity distribution across the 11 wavelet bands did not differ (p > 0.05) between the sustained tasks and remained unchanged from pretest to post-test MVIC. Taken together, the EMG and MMG intensity responses suggested that, despite the presence of peripheral fatigue, which affected the TRQ4FT to a greater extent than the RPE4FT, motor units were maximally recruited with no change in their firing rates from pretest to post-test MVIC. Thus, the application of wavelet-based spectral analyses offers a sensitive approach for detecting subtle changes in muscle function, which has important implications for advancing diagnostic precision and developing targeted interventions in sports performance, rehabilitation, and clinical assessments of neuromuscular health.
