Bridging minds and machines: the recent advances of brain-computer interfaces in neurological and neurosurgical applications

Awuah, Wireko Andrew, Ahluwalia, Arjun, Darko, Kwadwo, Sanker, Vivek, Tan, Joecelyn Kirani, Pearl, Tenkorang Ohenewaa, Ben-Jaafar, Adam, Ranganathan, Sruthi, Aderinto, Nicholas, Mehta, Aashna, Shah, Muhammad Hamza, Lee Boon Chun, Kevin, Abdul-Rahman, Toufik and Atallah, Oday 2024. Bridging minds and machines: the recent advances of brain-computer interfaces in neurological and neurosurgical applications. World Neurosurgery 189 , pp. 138-153. 10.1016/j.wneu.2024.05.104

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Abstract

Brain-Computer Interfaces (BCIs), a remarkable technological advancement in neurology and neurosurgery, mark a significant leap since the inception of electroencephalography (EEG) in 1924. These interfaces effectively convert central nervous system signals into commands for external devices, offering revolutionary benefits to patients with severe communication and motor impairments due to a myriad of neurological conditions like stroke, spinal cord injuries, and neurodegenerative disorders. BCIs enable these individuals to communicate and interact with their environment, using their brain signals to operate interfaces for communication and environmental control. This technology is especially crucial for those completely locked in, providing a communication lifeline where other methods fall short. The advantages of BCIs are profound, offering autonomy and an improved quality of life for patients with severe disabilities. They allow for direct interaction with various devices and prostheses, bypassing damaged or non-functional neural pathways. However, challenges persist, including the complexity of accurately interpreting brain signals, the need for individual calibration, and ensuring reliable, long-term use. Additionally, ethical considerations arise regarding autonomy, consent, and the potential for dependence on technology. Despite these challenges, BCIs represent a transformative development in neurotechnology, promising enhanced patient outcomes and a deeper understanding of brain-machine interfaces.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Medicine
Additional Information:	License information from Publisher: LICENSE 1: URL: http://creativecommons.org/licenses/by/4.0/, Start Date: 2024-05-24
Publisher:	Elsevier
ISSN:	1878-8750
Date of First Compliant Deposit:	28 May 2024
Date of Acceptance:	17 May 2024
Last Modified:	06 Aug 2024 13:59
URI:	https://orca.cardiff.ac.uk/id/eprint/169233

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