Benjamin Jon Fregly

This study compares generic and personalized foot-ground contact models in walking simulations, finding that personalized models improve accuracy in estimating ground reactions and joint loads.

This paper provides detailed tutorials for creating personalized neuromusculoskeletal models and designing treatments for walking impairments in two clinical cases using the NMSM Pipeline.

This study develops a synergy-based feedforward plus feedback control model for post-stroke walking, finding that 100% feedforward control best reproduces experimental data.

This paper develops a personalized shoulder modeling framework that improves kinematic accuracy for multiple motions using closed-chain models with 5 DOFs.

MATLAB toolsets add joint, muscle, synergy, and foot-contact personalization and optimal-control treatment design to OpenSim; one post-stroke case predicted 60% faster walking at equal metabolic cost.

This paper compares SynX and SO methods for estimating missing EMG signals and muscle forces during walking, finding SynX provides more accurate results.

This study assesses changes in walking function and neural control after pelvic cancer surgery with reconstruction using movement data and neuromusculoskeletal modeling.

This study evaluates if incorporating muscle synergies into static optimization improves muscle activation predictions during gait, finding no improvement but noting potential benefits for control applications.