Topic: Robotic-assisted rehabilitation

Robotic-assisted rehabilitation therapies play a crucial role in improving motor recovery by providing precise, repeatable, and intensive therapeutic interventions that traditional methods often lack [1,2,3]. Nonetheless, their adaptability is restricted due to a lack of comprehensive data on patients' biophysical signals and behavior [4,5,6]. Developing intelligent control mechanisms for rehabilitation devices is an essential step to enable personalized and responsive training for patients. This research project introduces the development of an innovative multimodal decoder for hybrid Brain-