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The combination of brain-computer interfaces and artificial intelligence: applications and challenges
Brain-computer interfaces (BCIs) have shown great prospects as real-time bidirectional links between living brains and actuators. Artificial intelligence (AI), which can advance the analysis and decoding of neural activity, has turbocharged the field of BCIs. Over the past decade, a wide range of BC...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7327323/ https://www.ncbi.nlm.nih.gov/pubmed/32617332 http://dx.doi.org/10.21037/atm.2019.11.109 |
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author | Zhang, Xiayin Ma, Ziyue Zheng, Huaijin Li, Tongkeng Chen, Kexin Wang, Xun Liu, Chenting Xu, Linxi Wu, Xiaohang Lin, Duoru Lin, Haotian |
author_facet | Zhang, Xiayin Ma, Ziyue Zheng, Huaijin Li, Tongkeng Chen, Kexin Wang, Xun Liu, Chenting Xu, Linxi Wu, Xiaohang Lin, Duoru Lin, Haotian |
author_sort | Zhang, Xiayin |
collection | PubMed |
description | Brain-computer interfaces (BCIs) have shown great prospects as real-time bidirectional links between living brains and actuators. Artificial intelligence (AI), which can advance the analysis and decoding of neural activity, has turbocharged the field of BCIs. Over the past decade, a wide range of BCI applications with AI assistance have emerged. These “smart” BCIs including motor and sensory BCIs have shown notable clinical success, improved the quality of paralyzed patients’ lives, expanded the athletic ability of common people and accelerated the evolution of robots and neurophysiological discoveries. However, despite technological improvements, challenges remain with regard to the long training periods, real-time feedback, and monitoring of BCIs. In this article, the authors review the current state of AI as applied to BCIs and describe advances in BCI applications, their challenges and where they could be headed in the future. |
format | Online Article Text |
id | pubmed-7327323 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-73273232020-07-01 The combination of brain-computer interfaces and artificial intelligence: applications and challenges Zhang, Xiayin Ma, Ziyue Zheng, Huaijin Li, Tongkeng Chen, Kexin Wang, Xun Liu, Chenting Xu, Linxi Wu, Xiaohang Lin, Duoru Lin, Haotian Ann Transl Med Review Article on Medical Artificial Intelligent Research Brain-computer interfaces (BCIs) have shown great prospects as real-time bidirectional links between living brains and actuators. Artificial intelligence (AI), which can advance the analysis and decoding of neural activity, has turbocharged the field of BCIs. Over the past decade, a wide range of BCI applications with AI assistance have emerged. These “smart” BCIs including motor and sensory BCIs have shown notable clinical success, improved the quality of paralyzed patients’ lives, expanded the athletic ability of common people and accelerated the evolution of robots and neurophysiological discoveries. However, despite technological improvements, challenges remain with regard to the long training periods, real-time feedback, and monitoring of BCIs. In this article, the authors review the current state of AI as applied to BCIs and describe advances in BCI applications, their challenges and where they could be headed in the future. AME Publishing Company 2020-06 /pmc/articles/PMC7327323/ /pubmed/32617332 http://dx.doi.org/10.21037/atm.2019.11.109 Text en 2020 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Review Article on Medical Artificial Intelligent Research Zhang, Xiayin Ma, Ziyue Zheng, Huaijin Li, Tongkeng Chen, Kexin Wang, Xun Liu, Chenting Xu, Linxi Wu, Xiaohang Lin, Duoru Lin, Haotian The combination of brain-computer interfaces and artificial intelligence: applications and challenges |
title | The combination of brain-computer interfaces and artificial intelligence: applications and challenges |
title_full | The combination of brain-computer interfaces and artificial intelligence: applications and challenges |
title_fullStr | The combination of brain-computer interfaces and artificial intelligence: applications and challenges |
title_full_unstemmed | The combination of brain-computer interfaces and artificial intelligence: applications and challenges |
title_short | The combination of brain-computer interfaces and artificial intelligence: applications and challenges |
title_sort | combination of brain-computer interfaces and artificial intelligence: applications and challenges |
topic | Review Article on Medical Artificial Intelligent Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7327323/ https://www.ncbi.nlm.nih.gov/pubmed/32617332 http://dx.doi.org/10.21037/atm.2019.11.109 |
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