Computational Analysis of Neuromuscular Adaptations to Strength and Plyometric Training: An Integrated Modeling Study.

ABSTRACT: Understanding neuromuscular adaptations resulting from specific training modalities is crucial for optimizing athletic performance and injury prevention. This in silico proof-of-concept study aimed to computationally model and predict neuromuscular adaptations induced by strength and plyometric training, integrating musculoskeletal simulations and machine learning techniques. A validated musculoskeletal model (OpenSim 4.4; 23 DOF, 92 musculotendon actuators) was scaled to a representative athlete (180 cm, 75 kg). Plyometric (vertical jumps, horizontal broad jumps, drop jumps) and strength exercises (back squat, deadlift, leg press) were simulated to evaluate biomechanical responses, including ground reaction forces, muscle activations, joint kinetics, and rate of force development (RFD). P

SUBMITTER: Manescu DC 

PROVIDER: S-EPMC12473730 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature