A Systematic Review of Bimanual Motor Coordination in Brain-Computer Interface
Advancements in neuroscience and artificial intelligence are propelling rapid progress in brain-computer interfaces (BCIs). These developments hold significant potential for decoding motion intentions from brain signals, enabling direct control commands without reliance on conventional neural pathwa...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
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| Online Access: | https://ieeexplore.ieee.org/document/10816155/ |
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| author | Poraneepan Tantawanich Chatrin Phunruangsakao Shin-Ichi Izumi Mitsuhiro Hayashibe |
| author_facet | Poraneepan Tantawanich Chatrin Phunruangsakao Shin-Ichi Izumi Mitsuhiro Hayashibe |
| author_sort | Poraneepan Tantawanich |
| collection | DOAJ |
| description | Advancements in neuroscience and artificial intelligence are propelling rapid progress in brain-computer interfaces (BCIs). These developments hold significant potential for decoding motion intentions from brain signals, enabling direct control commands without reliance on conventional neural pathways. Growing interest exists in decoding bimanual motor tasks, crucial for activities of daily living. This stems from the need to restore motor function, especially in individuals with deficits. This review aims to summarize neurological advancements in bimanual BCIs, encompassing neuroimaging techniques, experimental paradigms, and analysis algorithms. Thirty-six articles were reviewed, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The literature search result revealed diverse experimental paradigms, protocols, and research directions, including enhancing the decoding accuracy, advancing versatile prosthesis robots, and enabling real-time applications. Notably, within BCI studies on bimanual movement coordination, a shared objective is to achieve naturalistic movement and practical applications with neurorehabilitation potential. |
| format | Article |
| id | doaj-art-8d68d0b0968a462ca20472a29d0c5add |
| institution | Kabale University |
| issn | 1534-4320 1558-0210 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
| spelling | doaj-art-8d68d0b0968a462ca20472a29d0c5add2025-01-09T00:00:10ZengIEEEIEEE Transactions on Neural Systems and Rehabilitation Engineering1534-43201558-02102025-01-013326628510.1109/TNSRE.2024.352216810816155A Systematic Review of Bimanual Motor Coordination in Brain-Computer InterfacePoraneepan Tantawanich0https://orcid.org/0009-0000-1948-8120Chatrin Phunruangsakao1https://orcid.org/0000-0002-2448-8464Shin-Ichi Izumi2Mitsuhiro Hayashibe3https://orcid.org/0000-0001-6179-5706Department of Robotics, Graduate School of Engineering, Tohoku University, Sendai, JapanNeuro-Robotics Laboratory, Graduate School of Biomedical Engineering, Tohoku University, Sendai, JapanTsurumaki Onsen Hospital, Hadano, JapanDepartment of Robotics, the Graduate School of Engineering, the Neuro-Robotics Laboratory, and the Graduate School of Biomedical Engineering, Tohoku University, Sendai, JapanAdvancements in neuroscience and artificial intelligence are propelling rapid progress in brain-computer interfaces (BCIs). These developments hold significant potential for decoding motion intentions from brain signals, enabling direct control commands without reliance on conventional neural pathways. Growing interest exists in decoding bimanual motor tasks, crucial for activities of daily living. This stems from the need to restore motor function, especially in individuals with deficits. This review aims to summarize neurological advancements in bimanual BCIs, encompassing neuroimaging techniques, experimental paradigms, and analysis algorithms. Thirty-six articles were reviewed, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The literature search result revealed diverse experimental paradigms, protocols, and research directions, including enhancing the decoding accuracy, advancing versatile prosthesis robots, and enabling real-time applications. Notably, within BCI studies on bimanual movement coordination, a shared objective is to achieve naturalistic movement and practical applications with neurorehabilitation potential.https://ieeexplore.ieee.org/document/10816155/Brain-computer interfacebimanual coordinationneurosciencemachine learning |
| spellingShingle | Poraneepan Tantawanich Chatrin Phunruangsakao Shin-Ichi Izumi Mitsuhiro Hayashibe A Systematic Review of Bimanual Motor Coordination in Brain-Computer Interface IEEE Transactions on Neural Systems and Rehabilitation Engineering Brain-computer interface bimanual coordination neuroscience machine learning |
| title | A Systematic Review of Bimanual Motor Coordination in Brain-Computer Interface |
| title_full | A Systematic Review of Bimanual Motor Coordination in Brain-Computer Interface |
| title_fullStr | A Systematic Review of Bimanual Motor Coordination in Brain-Computer Interface |
| title_full_unstemmed | A Systematic Review of Bimanual Motor Coordination in Brain-Computer Interface |
| title_short | A Systematic Review of Bimanual Motor Coordination in Brain-Computer Interface |
| title_sort | systematic review of bimanual motor coordination in brain computer interface |
| topic | Brain-computer interface bimanual coordination neuroscience machine learning |
| url | https://ieeexplore.ieee.org/document/10816155/ |
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