Brokoslaw Laschowski

Abstract Accurate neural decoding of brain dynamics remains a significant and open challenge in brain-machine interfaces. While various signal processing, feature extraction, and classification algorithms have been proposed, a systematic comparison of these is lacking. Accordingly, here we conducted one of the largest comparative studies evaluating different combinations of state-of-the-art algorithms for motor neural decoding to find the optimal combination.

Abstract Control of robotic leg prostheses and exoskeletons is an open challenge. Computer modeling and simulation can be used to study the dynamics and control of human walking and extract principles that can be programmed into robotic legs to behave similar to biological legs.

Abstract Robotic prosthetic legs and exoskeletons require real-time and accurate estimation of the walking environment for smooth transitions between different locomotion mode controllers. However, previous studies have mainly been limited to static image classification, therein ignoring the temporal dynamics of human-robot locomotion.