Abstract:
This study explored the feasibility of incorpo-rating a passive Brain-Computer Interface (BCI) into the individualization process of wearable assistive devices, with a sp...Show MoreMetadata
Abstract:
This study explored the feasibility of incorpo-rating a passive Brain-Computer Interface (BCI) into the individualization process of wearable assistive devices, with a specific focus on lower-limb exoskeletons. These devices can greatly improve mobility and quality of life for those with lower limb impairments. However, their optimal performance relies on personalized adjustments. This study offered a unique approach to user feedback without intentional control. A one-degree-of-freedom knee exoskeleton was utilized, introducing different levels of impedance to create distinct assistance levels. The analysis identified specific brain clusters, notably the right premotor and supplementary motor cortex, exhibiting significant differences in activity between the easiest and the most challenging conditions. This critical proof-of-concept step demonstrated that through decoding the user's brain activity, passive BCI could support the individualization of assistive technology. This approach indicated the potential to enhance the performance and user experience of wearable assistive devices.
Published in: 2024 10th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob)
Date of Conference: 01-04 September 2024
Date Added to IEEE Xplore: 23 October 2024
ISBN Information: