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Rezvani S, Hosseini-Zahraei SH, Tootchi A, Guger C, Chaibakhsh Y, Saberi A, Chaibakhsh A. A review on the performance of brain-computer interface systems used for patients with locked-in and completely locked-in syndrome. Cogn Neurodyn 2024; 18:1419-1443. [PMID: 39104673 PMCID: PMC11297882 DOI: 10.1007/s11571-023-09995-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 06/28/2023] [Accepted: 07/30/2023] [Indexed: 08/07/2024] Open
Abstract
Patients with locked-in syndrome (LIS) and complete locked-in syndrome (CLIS) own a fully functional brain restricted within a non-functional body. In order to help LIS patients stay connected with their surroundings, brain-computer interfaces (BCIs) and related technologies have emerged. BCIs translate brain activity into actions that can be performed by external devices enabling LIS patients to communicate, leading to an increase in their quality of life. The past decade has seen the rapid development of BCIs that have the potential to be used for patients with locked-in syndrome, from which a great deal is tested only on healthy subjects and not on actual patients. This study aims to (1) provide the readers with a comprehensive study that contributes to this growing area of research by exploring the performance of BCIs tested specifically on LIS and CLIS patients, (2) give an overview of different modalities and paradigms used in different stages of the locked-in syndrome, and (3) discuss the contributions and limitations of BCIs introduced for the LIS and CLIS patients in the state-of-the-art and lay a groundwork for researchers interested in this field.
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Affiliation(s)
- Sanaz Rezvani
- Department of Mechanical Engineering, University, University of Guilan, Campus 2, Rasht, 41447-84475 Guilan Iran
- Intelligent Systems and Advanced Control Lab, University of Guilan, Rasht, 41938-13776 Guilan Iran
| | | | - Amirreza Tootchi
- Department of Mechanical & Energy Engineering, Indiana University - Purdue University Indianapolis (IUPUI), 723 W Michigan Street, Indianapolis, IN 46202 USA
| | | | - Yasmin Chaibakhsh
- Department of Cardiac Anesthesia, Rajaie Cardiovascular Medical and Research Centre, Iran University of Medical Sciences, Tehran, 19956-14331 Iran
| | - Alia Saberi
- Department of Neurology, Poursina Hospital, School of Medicine, Guilan University of Medical Sciences, Rasht, 41937-13194 Guilan Iran
| | - Ali Chaibakhsh
- Intelligent Systems and Advanced Control Lab, University of Guilan, Rasht, 41938-13776 Guilan Iran
- Faculty of Mechanical Engineering, University of Guilan, Rasht, 41996-13776 Guilan Iran
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Lin S, Jiang J, Huang K, Li L, He X, Du P, Wu Y, Liu J, Li X, Huang Z, Zhou Z, Yu Y, Gao J, Lei M, Wu H. Advanced Electrode Technologies for Noninvasive Brain-Computer Interfaces. ACS NANO 2023; 17:24487-24513. [PMID: 38064282 DOI: 10.1021/acsnano.3c06781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/27/2023]
Abstract
Brain-computer interfaces (BCIs) have garnered significant attention in recent years due to their potential applications in medical, assistive, and communication technologies. Building on this, noninvasive BCIs stand out as they provide a safe and user-friendly method for interacting with the human brain. In this work, we provide a comprehensive overview of the latest developments and advancements in material, design, and application of noninvasive BCIs electrode technology. We also explore the challenges and limitations currently faced by noninvasive BCI electrode technology and sketch out the technological roadmap from three dimensions: Materials and Design; Performances; Mode and Function. We aim to unite research efforts within the field of noninvasive BCI electrode technology, focusing on the consolidation of shared goals and fostering integrated development strategies among a diverse array of multidisciplinary researchers.
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Affiliation(s)
- Sen Lin
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
| | - Jingjing Jiang
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
| | - Kai Huang
- State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
- State Key Laboratory of Information Photonics and Optical Communications and School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Lei Li
- National Engineering Research Center of Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
| | - Xian He
- State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
| | - Peng Du
- State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
| | - Yufeng Wu
- State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
| | - Junchen Liu
- State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
- State Key Laboratory of Information Photonics and Optical Communications and School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Xilin Li
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
- Advanced Institute for Brain and Intelligence, Guangxi University, Nanning 530004, China
| | - Zhibao Huang
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
| | - Zenan Zhou
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
| | - Yuanhang Yu
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
| | - Jiaxin Gao
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
| | - Ming Lei
- State Key Laboratory of Information Photonics and Optical Communications and School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Hui Wu
- State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
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Khan MA, Saibene M, Das R, Brunner IC, Puthusserypady S. Emergence of flexible technology in developing advanced systems for post-stroke rehabilitation: a comprehensive review. J Neural Eng 2021; 18. [PMID: 34736239 DOI: 10.1088/1741-2552/ac36aa] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2021] [Accepted: 11/04/2021] [Indexed: 11/12/2022]
Abstract
OBJECTIVE Stroke is one of the most common neural disorders, which causes physical disabilities and motor impairments among its survivors. Several technologies have been developed for providing stroke rehabilitation and to assist the survivors in performing their daily life activities. Currently, the use of flexible technology (FT) for stroke rehabilitation systems is on a rise that allows the development of more compact and lightweight wearable systems, which stroke survivors can easily use for long-term activities. APPROACH For stroke applications, FT mainly includes the "flexible/stretchable electronics", "e-textile (electronic textile)" and "soft robotics". Thus, a thorough literature review has been performed to report the practical implementation of FT for post-stroke application. MAIN RESULTS In this review, the highlights of the advancement of FT in stroke rehabilitation systems are dealt with. Such systems mainly involve the "biosignal acquisition unit", "rehabilitation devices" and "assistive systems". In terms of biosignals acquisition, electroencephalography (EEG) and electromyography (EMG) are comprehensively described. For rehabilitation/assistive systems, the application of functional electrical stimulation (FES) and robotics units (exoskeleton, orthosis, etc.) have been explained. SIGNIFICANCE This is the first review article that compiles the different studies regarding flexible technology based post-stroke systems. Furthermore, the technological advantages, limitations, and possible future implications are also discussed to help improve and advance the flexible systems for the betterment of the stroke community.
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Affiliation(s)
- Muhammad Ahmed Khan
- Technical University of Denmark, Ørsteds Plads Building 345C, Room 215, Lyngby, 2800, DENMARK
| | - Matteo Saibene
- Technical University of Denmark, Ørsteds Plads, Building 345C, Lyngby, 2800, DENMARK
| | - Rig Das
- Technical University of Denmark, Ørsteds Plads Building 345C, Room 214, Lyngby, 2800, DENMARK
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Antonietti A, Balachandran P, Hossaini A, Hu Y, Valeriani D. The BCI Glossary: a first proposal for a community review. BRAIN-COMPUTER INTERFACES 2021. [DOI: 10.1080/2326263x.2021.1969789] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Alberto Antonietti
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milano, Italy
| | | | - Ali Hossaini
- Department of Engineering, King’s College London, London, UK
| | - Yaoping Hu
- Department of Electrical and Software Engineering,University of Calgary, Calgary, AB, Canada
| | - Davide Valeriani
- Department of Otolaryngology Head and Neck Surgery, Massachusetts Eye and Ear, Boston, MA, USA
- Department of Otolaryngology Head and Neck Surgery, Harvard Medical School, Boston, MA, USA
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A comprehensive assessment of Brain Computer Interfaces: Recent trends and challenges. J Neurosci Methods 2020; 346:108918. [PMID: 32853592 DOI: 10.1016/j.jneumeth.2020.108918] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 07/15/2020] [Accepted: 08/19/2020] [Indexed: 12/23/2022]
Abstract
BACKGROUND An uninterrupted channel of communication and control between the human brain and electronic processing units has led to an increased use of Brain Computer Interfaces (BCIs). This article attempts to present an all-encompassing review on BCI and the scientific advancements associated with it. The ultimate goal of this review is to provide a general overview of the BCI technology and to shed light on different aspects of BCIs. This review also underscores the applications, practical challenges and opportunities associated with BCI technology, which can be used to accelerate future developments in this field. METHODS This review is based on a systematic literature search for tracking down the relevant research annals and proceedings. Using a methodical search strategy, the search was carried out across major technical databases. The retrieved records were screened for their relevance and a total of 369 research chronicles were engulfed in this review based on the inclusion criteria. RESULTS This review describes the present scenario and recent advancements in BCI technology. It also identifies several application areas of BCI technology. This comprehensive review provides evidence that, while we are getting ever closer, significant challenges still exist for the development of BCIs that can seamlessly integrate with the user's biological system. CONCLUSION The findings of this review confirm the importance of BCI technology in various applications. It is concluded that BCI technology, still in its sprouting phase, requires significant explorations for further development.
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Comprehensive review on brain-controlled mobile robots and robotic arms based on electroencephalography signals. INTEL SERV ROBOT 2020. [DOI: 10.1007/s11370-020-00328-5] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Pattnaik PK, Sarraf J. Brain Computer Interface issues on hand movement. JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES 2018. [DOI: 10.1016/j.jksuci.2016.09.006] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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