Motor Learning

Motor learning research investigates how humans acquire and refine motor skills, aiming to understand the underlying neural mechanisms and develop effective training strategies. Current research focuses on leveraging technology, such as wearable sensors and robotic devices, to provide personalized feedback and haptic guidance, exploring the influence of individual traits and employing diverse model architectures including neural networks, deep reinforcement learning (particularly model-based approaches), and XGBoost for real-time performance analysis. These advancements hold significant implications for rehabilitation, athletic training, and human-robot interaction, offering the potential to improve motor skill acquisition and recovery from injury.