Arthur D. Kuo

This paper shows that short gait tests underestimate steady walking speed and proposes a method to correct for this bias using multiple distance measurements.

This paper introduces an Energy-Time trade-off model to explain the smoothness, speed, and individuality of human reaching movements, showing it outperforms previous models.

This paper quantifies the energy cost of walking on uneven terrain, showing it increases quadratically with amplitude and cubically with speed.

This paper describes modifications to a split-belt instrumented treadmill to enable use on uneven terrain, demonstrating accurate ground reaction force measurements.

The paper develops a new muscle model that integrates force development dynamics, finding that conventional processes cannot explain force production speed, and proposes 'force facilitation dynamics' as a key rate-limiting factor.

This study quantifies how biomechanical inverse dynamics analysis is highly sensitive to temporal mis-synchronization in data, showing significant errors in joint moments and powers with even small delays.

The paper estimates the energetic cost of human running and finds that active muscle work accounts for most of the cost, even when considering passive elastic contributions.

This study shows that smooth human arm movements are energetically optimal, as jerkier motions require more metabolic energy due to increased muscle force production rates.

The paper proposes an optimality principle for combining central pattern generators and reflex circuits in locomotion, showing how uncertainty-driven feedback optimizes gait stability and energy efficiency.