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EEG-Based Analysis of Brain Responses in Multi-Modal Human-Robot Interaction: Modulating Engagement by Oliver, Suzanne; Kitago, Tomoko; Buchwald, Adam; Atashzar, S. Farokh is a scholarly article available to read on EtoBox.

What is EEG-Based Analysis of Brain Responses in Multi-Modal Human-Robot Interaction: Modulating Engagement about?

User engagement, cognitive participation, and motivation during task execution in physical human-robot interaction are crucial for motor learning. These factors are especially important in contexts like robotic rehabilitation, where neuroplasticity is targeted. However, traditional robotic rehabilitation systems often face challenges in maintaining user engagement, leading to unpredictable therapeutic outcomes. To address this issue, various techniques, such as assist-as-needed controllers, have been developed to prevent user slacking and encourage active participation. In this paper, we introduce a new direction through a novel multi-modal robotic interaction designed to enhance user engagement by synergistically integrating visual, motor, cognitive, and auditory (speech recognition) tasks into a single, comprehensive activity. To assess engagement quantitatively, we compared multiple electroencephalography (EEG) biomarkers between this multi-modal protocol and a traditional motor-only protocol. Fifteen healthy adult participants completed 100 trials of each task type. Our findings revealed that EEG biomarkers, particularly relative alpha power, showed statistically significant im

Author

Oliver, Suzanne; Kitago, Tomoko; Buchwald, Adam; Atashzar, S. Farokh

Published

2024

Language

EN