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

Area of Science:

• Neuroscience
• Rehabilitation Robotics
• Human-Computer Interaction

Background:

• Rehabilitation robots are increasingly used in clinical settings.
• Lack of affective interaction in robot-based training may limit clinical effectiveness.
• Positive patient-clinician relationships enhance rehabilitation outcomes, but underlying mechanisms are unclear.

Purpose of the Study:

• To investigate the impact of interpersonal interactions on motor learning outcomes.
• To compare the effects of partner-led versus robot-led training sessions.
• To explore the neural mechanisms, including brain activation and interbrain coupling, associated with different training modalities.

Main Methods:

• A motor learning experiment involving a left-hand drawing task.
• Ten pairs of friends participated in two training sessions: one partner-led, one robot-led.
• Electroencephalography (EEG) hyperscanning recorded brain activity; task performance was assessed pre- and post-training.

Main Results:

• Partner-led training resulted in significant motor learning progress compared to robot-led training.
• Enhanced brain activation was observed in the central, parieto-occipital, and frontal cortex during partner-led sessions.
• Strengthened interbrain coupling was evident in partner-led training compared to robot-based training.

Conclusions:

• Partner-assisted training enhances motivation, attention, and positive emotions, leading to superior rehabilitation outcomes.
• Affective human-machine interaction is crucial for optimizing rehabilitation robot efficacy.
• Findings support the development of human-machine affective interaction strategies for rehabilitation robots.