Integrating biomechanical indicators in training load monitoring based on TRIMP model among elite basketball players
DOI:
https://doi.org/10.47197/retos.v78.116527Keywords:
Training Load, TRIMP, Biomechanics, EMG, NeuromuscularAbstract
Introduction: this study addressed the limitations of the traditional training impulse model in representing training load in elite basketball, a sport characterized by high mechanical stress and neuromuscular demands. the conventional model primarily reflected cardiovascular load and underestimated biomechanical contributions associated with explosive movements.
Objective: the objective of the study was to evaluate a hybrid training load model integrating biomechanical indicators with the traditional training impulse approach in elite basketball players.
Methodology: a quasi-experimental design was applied to a sample of 26 elite basketball players. training load data were collected using heart rate monitoring systems, force platforms, surface electromyographic recordings, and high-speed motion analysis. biomechanical indicators included ground reaction force, ground contact time, muscle electrical activity, and knee joint angle. statistical analyses involved paired sample tests, correlation analysis, and multiple regression procedures.
Results: the results demonstrated statistically significant differences between the traditional model and the hybrid biomechanical model in estimating training load. ground reaction force showed the strongest association with the hybrid model, followed by muscle electrical activity and ground contact time. regression analysis indicated that biomechanical indicators jointly explained a substantial proportion of training load variability, with knee joint angle identified as the most influential predictor.
Discussion: the findings were consistent with previous research emphasizing the importance of mechanical load and neuromuscular stress in high-impact sports. the hybrid model provided greater sensitivity in capturing external and internal load components compared with traditional cardiovascular-based approaches.
Conclusions: the integration of biomechanical indicators enhanced training load monitoring in elite basketball and supports a more comprehensive and individualized assessment approach.
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