Arnault Hubert Caillet

This paper develops and validates a multiscale Hill-type neuromuscular actuator against experimental benchmarks of motor unit and muscle force measurements, showing improved accuracy in force reproduction.

This paper reviews Hill-type muscle models, finding most lack innovation, proper validation, parameter identification, and reusability.

The paper analyzes motor unit firing rates during isometric contractions to show diverse rate coding patterns across motor unit pools.

NeuroMotion generates synthetic EMG signals during voluntary movements by integrating musculoskeletal models, neural networks, and motor unit models, enabling analysis of neuromechanical interactions.

The paper describes new electrophysiological and computational methods to accurately estimate neural drive to muscles in humans in vivo by improving MU sampling and using data augmentation.

This paper shows that larger and denser EMG electrode grids improve the identification of more representative motor unit samples through computational and experimental analysis.

The paper proposes a method combining EMG signal decomposition and realistic motoneuron modeling to estimate the firing behavior of entire motoneuron pools in humans.

The paper derives mathematical relationships between electrophysiological and anatomical properties of spinal alpha-motoneurons across species, validating existing theories and providing a tool for modeling and experimental analysis.