Aaron J. Young

The paper introduces AMP, an automated motion capture pipeline that reduces manual effort by 73.5% while maintaining spatial accuracy within 10 mm of manual ground truth.

This paper introduces an autoencoder-based method for computing motor modules from EMG data, showing improved stability and biomechanical interpretability compared to non-negative matrix factorization.

This study develops a personalized exoskeleton control method that reduces metabolic cost by optimizing mappings from biological joint moments to torque, showing greater benefits than non-personalized approaches.

The paper critiques a study claiming experiment-free exoskeleton control via simulation, highlighting unverified claims and physiological inconsistencies.