Enhancing Motor Learning Performance by Incorporating Brain-to-brain Coupling with Affective Interaction.

The widespread clinical application of rehabilitation robots is an inevitable trend. Nonetheless, the absence of affective interactions in robot-based training could significantly limit rehabilitation robots' clinical effects. While a favorable patient-clinician relationship during rehabilitation training may promote positive affectivity and result in improved clinical outcomes, the mechanisms underlying this phenomenon remain unclear. In this study, a motor learning experiment was designed to prospectively investigate the impact of interpersonal interactions on training outcomes. Ten pairs of friends engaged in a left-hand drawing task across two training sessions: one led by a close partner and the other by a robot. Pairs of participants' EEG was recorded during training sessions via hyperscaning and task performance was evaluated before and after the training. Results revealed significant motor learning progress and enhanced brain activation in the central, parieto-occipital, and frontal cortex, along with strengthened interbrain coupling in partner-led training compared with robot-based training. These findings suggest that partner-assisted training fosters stronger motivation, attention, and positive emotions, contributing to superior outcomes. This study may provide theoretical and technical support for the design of human-machine affective interaction in rehabilitation robots.