Impact of Generative AI Models on Neurocybernetics for Enhancing Brain-Computer Interface Adaptability in Motor Disabilities
Poly Rani Ghosh 1*, Shakher Halder 1, Halima Mowla 1
Journal of Primeasia 4(1) 1-7 https://doi.org/10.25163/primeasia.4140047
Submitted: 10 April 2023 Revised: 17 June 2023 Published: 19 July 2023
Abstract
Motor disabilities can arise from conditions such as stroke, spinal cord injuries, or neurodegenerative diseases, severely limiting an individual's movement and communication abilities. Brain-computer interfaces (BCIs) represent a promising technology aimed at establishing a direct connection between the brain and external devices, allowing individuals with motor impairments to control assistive technologies using their brain signals. However, conventional BCIs often rely on fixed signal patterns or require extensive user training, presenting challenges for some users and constraining system flexibility. Variability in brain signals and the inability to adapt further impede widespread BCI adoption among this population. This study explores the integration of generative AI models to enhance BCI adaptability for people with motor disabilities. By leveraging generative AI, our framework generates realistic brain signals tailored to each user's specific characteristics. Through rigorous experimentation and case studies, we demonstrate the efficacy of our approach in improving BCI performance and usability. Our findings underscore the transformative potential of generative artificial intelligence in neurocybernetics, illustrating its capacity to advance BCI accessibility and effectiveness in rehabilitating motor disabilities. The limitations of traditional BCIs through innovative AI-driven solutions, this research contributes to the evolving field of assistive technologies. It highlights the pivotal role of generative AI in fostering greater autonomy and quality of life for individuals with motor impairments, paving the way for more inclusive and responsive neurotechnology in the future.
Keywords: Brain-computer interfaces, Motor disabilities, Generative AI, Neurocybernetics, Assistive technologies.
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