Enhancing Accessibility through Brain-Computer Interfaces (BCIs) in Assistive Technology

Abstract

Brain-Computer Interfaces (BCIs) have revolutionized assistive technology, offering transformative solutions to enhance accessibility for individuals with physical and neurological disabilities. By enabling direct communication between the brain and external devices, BCIs bypass traditional pathways, empowering users to control assistive tools through neural activity. This research explores the integration of BCIs into assistive technology, focusing on their potential to improve mobility, communication, and independence. It examines cutting-edge applications such as neural-controlled prosthetics, speech-generating devices, and smart home systems tailored for accessibility. The study also addresses challenges including signal processing accuracy, user adaptability, and ethical considerations surrounding data privacy and inclusivity. By analyzing advancements in machine learning algorithms and neurofeedback systems, the research provides insights into optimizing BCI functionality for practical deployment. Ultimately, this study highlights the role of BCIs in creating a more inclusive society by redefining the capabilities of assistive technologies.