Investigating the Efficacy of Brain-Computer Interfaces in Enhancing Cognitive Abilities for Direct Brain-to-Machine Communication

Abstract

Brain-Computer Interfaces (BCIs) are assistive technologies used to facilitate direct communication between the brain and external devices. This paper explores the potential of BCIs to enhance artificial cognitive abilities in systems and enable direct brain-to-machine communication. The integration of Artificial Intelligence (AI) with BCIs is explored to identify the improvements in accuracy, personalization, user experience and integration of cognition into BCI systems. The study emphasizes the potential uses of BCIs in robotics, humancomputer interfaces, healthcare, and rehabilitation. Based on the systematic literature review done in this paper, it is noted that BCIs can be effectively used to improve cognitive functions like memory, attention, and creativity. BCIs also assist with motor rehabilitation for individuals with disabilities, create more natural and intuitive human-robot interaction, and develop personalized therapy approaches for various conditions like ADHD. However, it is necessary to address current low accuracy problems, user interface challenges and limited cognitive abilities in BCIs. While addressing technological improvements through rigorous research, it is necessary to ensure responsible and ethical evolution of BCI technology for integrating cognitive abilities in computer systems.