SECTION III - SPORTS TRAINING / RESEARCH PAPER
Identification of Peripheral Fatigue through Exercise-Induced Changes in Muscle Contractility
1
Department of Sports and Computers Sciences, Physical Performance & Sports Research Center, Universidad Pablo de Olavide, Sevilla, Spain.
2
Department of Physical Education, University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain.
3
Department of Sports and Computers Sciences, Faculty of Sport Sciences, Universidad Pablo de Olavide, Sevilla, Spain.
4
Sport Performance, Physical Condition and Wellness Lab. Faculty of Education and Sport Sciences, Universidad de Vigo,
Submission date: 2023-11-05
Final revision date: 2023-12-15
Acceptance date: 2024-02-23
Online publication date: 2024-05-17
Corresponding author
Oscar García-García
Physical Education and Sport, Universidad de Vigo, Facultad de Ciencias de la Educación y del Deporte, 36005, Pontevedra, Spain
Physical Education and Sport, Universidad de Vigo, Facultad de Ciencias de la Educación y del Deporte, 36005, Pontevedra, Spain
KEYWORDS
tensiomyographyresistance trainingmaximal isometric forcecountermovement jumpmuscle contractile properties
TOPICS
ABSTRACT
The aim of this study was to assess whether tensiomyography is a tool sensitive enough to detect peripheral fatigue. Twenty-six strength-trained men were split into two groups: 1) a fatigued group (FG), who performed a full-squat (SQ) standardized warm-up plus 3 x 8 SQs with 75% 1RM with a 5-min rest interval, and 2) a non-fatigued group (NFG), who only did the SQ standardized warm-up. The countermovement jump (CMJ), maximal isometric force (MIF) in the SQ at 90º knee flexion, and TMG in vastus medialis (VM) and vastus lateralis (VL) muscles were assessed pre- and post-protocols. Data were analyzed through mixed ANOVA, logistic regression analysis, and receiver-operating curves. There were significant group x time interactions (p < 0.01) for CMJ height, MIF, maximal radial displacement (Dm), and radial displacement velocity (Vrd90) since the FG acutely decreased in these variables, while no significant changes were observed for the NFG. The logistic regression showed a significant model for detecting fatigue, whether it used the CMJ or MIF, with only the relative change in VL-Vrd90 as a fatigue predictor. The determination of the area under the curve showed that Dm and Vrd90 had good to excellent discriminative ability. Dm and Vrd90 are sensitive to detect fatigue in VL and VM muscles in resistance training contexts.
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