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Toward personalized human-in-the-loop training: Real-time estimation of individual motor learning dynamics using the dual-rate model

Published in Computers in Biology and Medicine, 2025

This study presents a real-time estimation framework for modelling individual motor learning dynamics using system identification methods: Moving Horizon Estimation (MHE) and Extended Kalman Filter (EKF). The results show how these methods can enable adaptive and personalized robotic training, bridging control theory, neuroscience, and rehabilitation robotics.

Recommended citation: A. Salemi, A. Afkhami Ardekani, A. H. Vette, M. Nazarahari. (2025). Toward personalized human-in-the-loop training: Real-time estimation of individual motor learning dynamics using the dual-rate model. Computers in Biology and Medicine, 198, 111198. https://doi.org/10.1016/j.compbiomed.2025.111198
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Published: March 01, 2012

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