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Murtaugh B, Fager S, Sorenson T. Emergence from Disorders of Consciousness: Optimizing Self-Agency Through Communication. Phys Med Rehabil Clin N Am 2024; 35:175-191. [PMID: 37993188 PMCID: PMC11216683 DOI: 10.1016/j.pmr.2023.07.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2023]
Abstract
Language and communication deficits are intrinsic to disorders of consciousness. This article will provide an overview of language and communication deficits that can significantly confound the accuracy of diagnostic assessment in these patients. Authors will also discuss interventions to promote early communication using assistive technology and augmentative communication rehabilitation strategies. Finally, this article will discuss the importance of family education as well as ethical considerations connected to the recovery of communication and adaptive strategies to support patient autonomy and enhance self-agency.
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Affiliation(s)
- Brooke Murtaugh
- Department of Rehabilitation Programs, Madonna Rehabilitation Hospitals, 5401 South Street, Lincoln, NE 68506, USA.
| | - Susan Fager
- Research Institute, Madonna Rehabilitation Hospitals, 5401 South Street, Lincoln, NE 68506, USA
| | - Tabatha Sorenson
- Department of Occupational Therapy, Madonna Rehabilitation Hospitals, 5401 South Street, Lincoln, NE 68506, USA
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2
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Oh E, Shin S, Kim SP. Brain-computer interface in critical care and rehabilitation. Acute Crit Care 2024; 39:24-33. [PMID: 38224957 PMCID: PMC11002623 DOI: 10.4266/acc.2023.01382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 11/08/2023] [Indexed: 01/17/2024] Open
Abstract
This comprehensive review explores the broad landscape of brain-computer interface (BCI) technology and its potential use in intensive care units (ICUs), particularly for patients with motor impairments such as quadriplegia or severe brain injury. By employing brain signals from various sensing techniques, BCIs offer enhanced communication and motor rehabilitation strategies for patients. This review underscores the concept and efficacy of noninvasive, electroencephalogram-based BCIs in facilitating both communicative interactions and motor function recovery. Additionally, it highlights the current research gap in intuitive "stop" mechanisms within motor rehabilitation protocols, emphasizing the need for advancements that prioritize patient safety and individualized responsiveness. Furthermore, it advocates for more focused research that considers the unique requirements of ICU environments to address the challenges arising from patient variability, fatigue, and limited applicability of current BCI systems outside of experimental settings.
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Affiliation(s)
- Eunseo Oh
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Korea
| | - Seyoung Shin
- Department of Mechanical Engineering, Sungkyunkwan University, Suwon, Korea
| | - Sung-Phil Kim
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, Korea
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Zhang J, Xu B, Lou X, Wu Y, Shen X. MI-based BCI with accurate real-time three-class classification processing and light control application. Proc Inst Mech Eng H 2023; 237:1017-1028. [PMID: 37550947 DOI: 10.1177/09544119231187287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/09/2023]
Abstract
The use of brain-computer interfaces (BCIs) to control intelligent devices is a current and future research direction. However, the challenges of low accuracy of real-time recognition and the need for multiple electroencephalographic channels are yet to be overcome. While a number of research teams have proposed many ways to improve offline classification accuracy, the potential problems in real-time experiments are often overlooked. In this study, we proposed a label-based channel diversion preprocessing to solve the problem of low real-time classification accuracy. The Tikhonov regularised common spatial-pattern algorithm (TRCSP) and one vs rest support vector machine (OVR-SVM) were used for feature extraction and pattern classification. High accuracy was achieved in real-time three-class classification using only three channels (average real-time accuracy of 87.46%, with a maximum of 90.33%). In addition, the stability and reliability of the system were verified through lighting control experiments in a real environment. Using the autonomy of MI and real-time feedback of light brightness, we have built a fully autonomous interactive system. The improvement in the real-time classification accuracy in this study is of great significance to the industrialisation of BCI.
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Affiliation(s)
- Jiakai Zhang
- School of Information Science and Technology, Nantong University, Nantong, China
| | - Boyang Xu
- School of Information Science and Technology, Nantong University, Nantong, China
| | - Xiongjie Lou
- School of Information Science and Technology, Nantong University, Nantong, China
| | - Yan Wu
- School of Information Science and Technology, Nantong University, Nantong, China
| | - Xiaoyan Shen
- School of Information Science and Technology, Nantong University, Nantong, China
- Nantong Research Institute for Advanced Communication Technologies, Nantong University, Nantong, China
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Fager SK, Sorenson T, Jakobs E, Koester H, Jakobs T, Beukelman DR. Multi-modal access method (eye-tracking + switch-scanning) for individuals with severe motor impairment: A preliminary investigation. Assist Technol 2023; 35:321-329. [PMID: 35298355 PMCID: PMC9576815 DOI: 10.1080/10400435.2022.2053895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/01/2022] [Indexed: 10/18/2022] Open
Abstract
Individuals with severe motor impairments often require alternative means to access computers and communication technology. A range of alternative access devices exist; however, most rely on use of a single access modality. While this approach works for some individuals, it can be limiting for others. This study explored the use of a multi-modal prototype (eye-tracking + switch-scanning) on typing performance with a range of individuals with motor impairments. The multi-modal prototype was compared to eye-tracking alone for this study. Results indicated that the multi-modal prototype had significantly slower typing rate but significantly lower total errors compared to eye-tracking alone. Analysis of individual data revealed four subgroups of clinical relevance including individuals that 1) benefit from multi-modal, 2) benefit from eye-tracking, 3) demonstrate learning and 4) demonstrate fluctuating performance.
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Affiliation(s)
- S. K. Fager
- Institute for Rehabilitation Science and Engineering, Madonna Rehabilitation Hospitals, Lincoln, Nebraska, USA
| | - T. Sorenson
- Institute for Rehabilitation Science and Engineering, Madonna Rehabilitation Hospitals, Lincoln, Nebraska, USA
| | - E. Jakobs
- Invotek, Inc., Alma, Arkansas, USA
- Department of Communication Sciences and Disorders, Pennsylvania State University, University Park, Pennsylvania, USA
| | - H. Koester
- Koester Performance Research, Asheville, North Carolina, USA
| | | | - D. R. Beukelman
- Institute for Rehabilitation Science and Engineering, Madonna Rehabilitation Hospitals, Lincoln, Nebraska, USA
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Sowers DJ, Wilkinson KM. Demands Associated With an Augmentative and Alternative Communication System in Relation to Alternative Forms of Access for Individuals With Motor Impairments. AMERICAN JOURNAL OF SPEECH-LANGUAGE PATHOLOGY 2023; 32:37-54. [PMID: 36599109 DOI: 10.1044/2022_ajslp-22-00006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
PURPOSE Successful adoption and use of aided augmentative and alternative communication (AAC) must address how to promote fluid, efficient, and organized execution of the motor behavior needed to access the AAC system. A substantial number of people who use AAC have significant motor impairments and require "alternative" access options, such as eye gaze or switch use. Such individuals may be particularly vulnerable to interference from a poorly designed system. However, the inherent demands of alternative access methods have received little direct study. The goal of this tutorial is to offer a clinically and theoretically guided framework for considerations concerning AAC access, with the hope of spurring further discussion and empirical research. METHOD A framework that draws upon dynamic systems theory was used to illustrate the interactions between the various elements of importance to AAC access. Information and research from the fields of motor learning, developmental dynamic systems theory, AAC, and assistive technology was integrated into this tutorial to examine their applications for alternative AAC access methods. RESULTS The framework illustrated that AAC access involves a complex coordination between individual skills, the demands of the communication environment, the activity being undertaken, and the supports and demands inherent in the AAC system itself. CONCLUSIONS Awareness of the many demands that alternative forms of access place on the person who uses them can guide clinicians during assessment and intervention decision making regarding access options for individuals with significant motor impairments. Specific directions for future research are considered.
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Affiliation(s)
- Dawn J Sowers
- Department of Communication Sciences and Disorders, The Pennsylvania State University, University Park
| | - Krista M Wilkinson
- Department of Communication Sciences and Disorders, The Pennsylvania State University, University Park
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Chuang CC, Lee CC, So EC, Yeng CH, Chen YJ. Multi-Task Learning-Based Deep Neural Network for Steady-State Visual Evoked Potential-Based Brain-Computer Interfaces. SENSORS (BASEL, SWITZERLAND) 2022; 22:8303. [PMID: 36366001 PMCID: PMC9656443 DOI: 10.3390/s22218303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 10/23/2022] [Accepted: 10/24/2022] [Indexed: 06/16/2023]
Abstract
Amyotrophic lateral sclerosis (ALS) causes people to have difficulty communicating with others or devices. In this paper, multi-task learning with denoising and classification tasks is used to develop a robust steady-state visual evoked potential-based brain-computer interface (SSVEP-based BCI), which can help people communicate with others. To ease the operation of the input interface, a single channel-based SSVEP-based BCI is selected. To increase the practicality of SSVEP-based BCI, multi-task learning is adopted to develop the neural network-based intelligent system, which can suppress the noise components and obtain a high level of accuracy of classification. Thus, denoising and classification tasks are selected in multi-task learning. The experimental results show that the proposed multi-task learning can effectively integrate the advantages of denoising and discriminative characteristics and outperform other approaches. Therefore, multi-task learning with denoising and classification tasks is very suitable for developing an SSVEP-based BCI for practical applications. In the future, an augmentative and alternative communication interface can be implemented and examined for helping people with ALS communicate with others in their daily lives.
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Affiliation(s)
- Chia-Chun Chuang
- Department of Anesthesia, An Nan Hospital, China Medical University, Tainan 70965, Taiwan
- Department of Medical Sciences Industry, Chang Jung Christian University, Tainan 71101, Taiwan
| | - Chien-Ching Lee
- Department of Anesthesia, An Nan Hospital, China Medical University, Tainan 70965, Taiwan
- Department of Medical Sciences Industry, Chang Jung Christian University, Tainan 71101, Taiwan
| | - Edmund-Cheung So
- Department of Anesthesia, An Nan Hospital, China Medical University, Tainan 70965, Taiwan
| | - Chia-Hong Yeng
- Department of Electrical Engineering, Southern Taiwan University of Science and Technology, Tainan 71005, Taiwan
| | - Yeou-Jiunn Chen
- Department of Electrical Engineering, Southern Taiwan University of Science and Technology, Tainan 71005, Taiwan
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Peters B, Eddy B, Galvin-McLaughlin D, Betz G, Oken B, Fried-Oken M. A systematic review of research on augmentative and alternative communication brain-computer interface systems for individuals with disabilities. Front Hum Neurosci 2022; 16:952380. [PMID: 35966988 PMCID: PMC9374067 DOI: 10.3389/fnhum.2022.952380] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 07/04/2022] [Indexed: 11/13/2022] Open
Abstract
Augmentative and alternative communication brain-computer interface (AAC-BCI) systems are intended to offer communication access to people with severe speech and physical impairment (SSPI) without requiring volitional movement. As the field moves toward clinical implementation of AAC-BCI systems, research involving participants with SSPI is essential. Research has demonstrated variability in AAC-BCI system performance across users, and mixed results for comparisons of performance for users with and without disabilities. The aims of this systematic review were to (1) describe study, system, and participant characteristics reported in BCI research, (2) summarize the communication task performance of participants with disabilities using AAC-BCI systems, and (3) explore any differences in performance for participants with and without disabilities. Electronic databases were searched in May, 2018, and March, 2021, identifying 6065 records, of which 73 met inclusion criteria. Non-experimental study designs were common and sample sizes were typically small, with approximately half of studies involving five or fewer participants with disabilities. There was considerable variability in participant characteristics, and in how those characteristics were reported. Over 60% of studies reported an average selection accuracy ≤70% for participants with disabilities in at least one tested condition. However, some studies excluded participants who did not reach a specific system performance criterion, and others did not state whether any participants were excluded based on performance. Twenty-nine studies included participants both with and without disabilities, but few reported statistical analyses comparing performance between the two groups. Results suggest that AAC-BCI systems show promise for supporting communication for people with SSPI, but they remain ineffective for some individuals. The lack of standards in reporting outcome measures makes it difficult to synthesize data across studies. Further research is needed to demonstrate efficacy of AAC-BCI systems for people who experience SSPI of varying etiologies and severity levels, and these individuals should be included in system design and testing. Consensus in terminology and consistent participant, protocol, and performance description will facilitate the exploration of user and system characteristics that positively or negatively affect AAC-BCI use, and support innovations that will make this technology more useful to a broader group of people. Clinical trial registration https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42018095345, PROSPERO: CRD42018095345.
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Affiliation(s)
- Betts Peters
- Consortium for Accessible Multimodal Brain-Body Interfaces, United States
- REKNEW Projects, Institute on Development and Disability, Department of Pediatrics, Oregon Health and Science University, Portland, OR, United States
| | - Brandon Eddy
- Consortium for Accessible Multimodal Brain-Body Interfaces, United States
- REKNEW Projects, Institute on Development and Disability, Department of Pediatrics, Oregon Health and Science University, Portland, OR, United States
- Speech and Hearing Sciences Department, Portland State University, Portland, OR, United States
| | - Deirdre Galvin-McLaughlin
- Consortium for Accessible Multimodal Brain-Body Interfaces, United States
- REKNEW Projects, Institute on Development and Disability, Department of Pediatrics, Oregon Health and Science University, Portland, OR, United States
| | - Gail Betz
- Health Sciences and Human Services Library, University of Maryland, Baltimore, MD, United States
| | - Barry Oken
- Consortium for Accessible Multimodal Brain-Body Interfaces, United States
- Department of Neurology, Oregon Health & Science University, Portland, OR, United States
| | - Melanie Fried-Oken
- Consortium for Accessible Multimodal Brain-Body Interfaces, United States
- REKNEW Projects, Institute on Development and Disability, Department of Pediatrics, Oregon Health and Science University, Portland, OR, United States
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Rojas M, Ponce P, Molina A. Development of a Sensing Platform Based on Hands-Free Interfaces for Controlling Electronic Devices. Front Hum Neurosci 2022; 16:867377. [PMID: 35754778 PMCID: PMC9231433 DOI: 10.3389/fnhum.2022.867377] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 05/04/2022] [Indexed: 11/13/2022] Open
Abstract
Hands-free interfaces are essential to people with limited mobility for interacting with biomedical or electronic devices. However, there are not enough sensing platforms that quickly tailor the interface to these users with disabilities. Thus, this article proposes to create a sensing platform that could be used by patients with mobility impairments to manipulate electronic devices, thereby their independence will be increased. Hence, a new sensing scheme is developed by using three hands-free signals as inputs: voice commands, head movements, and eye gestures. These signals are obtained by using non-invasive sensors: a microphone for the speech commands, an accelerometer to detect inertial head movements, and an infrared oculography to register eye gestures. These signals are processed and received as the user's commands by an output unit, which provides several communication ports for sending control signals to other devices. The interaction methods are intuitive and could extend boundaries for people with disabilities to manipulate local or remote digital systems. As a study case, two volunteers with severe disabilities used the sensing platform to steer a power wheelchair. Participants performed 15 common skills for wheelchair users and their capacities were evaluated according to a standard test. By using the head control they obtained 93.3 and 86.6%, respectively for volunteers A and B; meanwhile, by using the voice control they obtained 63.3 and 66.6%, respectively. These results show that the end-users achieved high performance by developing most of the skills by using the head movements interface. On the contrary, the users were not able to develop most of the skills by using voice control. These results showed valuable information for tailoring the sensing platform according to the end-user needs.
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Affiliation(s)
- Mario Rojas
- Tecnologico de Monterrey, School of Engineering and Sciences, Mexico City, Mexico
| | - Pedro Ponce
- Tecnologico de Monterrey, School of Engineering and Sciences, Mexico City, Mexico
| | - Arturo Molina
- Tecnologico de Monterrey, School of Engineering and Sciences, Mexico City, Mexico
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Pitt KM, McKelvey M, Weissling K. The perspectives of augmentative and alternative communication experts on the clinical integration of non-invasive brain-computer interfaces. BRAIN-COMPUTER INTERFACES 2022. [DOI: 10.1080/2326263x.2022.2057758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- Kevin M. Pitt
- Department of Special Education and Communication Disorders, University of Nebraska–Lincoln, Lincoln, NE, USA
| | - Miechelle McKelvey
- Department of Communication Disorders, University of Nebraska Kearney Kearney, NE, USA
| | - Kristy Weissling
- Department of Special Education and Communication Disorders, University of Nebraska–Lincoln, Lincoln, NE, USA
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Martínez-Cagigal V, Thielen J, Santamaría-Vázquez E, Pérez-Velasco S, Desain P, Hornero R. Brain-computer interfaces based on code-modulated visual evoked potentials (c-VEP): a literature review. J Neural Eng 2021; 18. [PMID: 34763331 DOI: 10.1088/1741-2552/ac38cf] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Accepted: 11/11/2021] [Indexed: 11/11/2022]
Abstract
Objective.Code-modulated visual evoked potentials (c-VEP) have been consolidated in recent years as robust control signals capable of providing non-invasive brain-computer interfaces (BCIs) for reliable, high-speed communication. Their usefulness for communication and control purposes has been reflected in an exponential increase of related articles in the last decade. The aim of this review is to provide a comprehensive overview of the literature to gain understanding of the existing research on c-VEP-based BCIs, since its inception (1984) until today (2021), as well as to identify promising future research lines.Approach.The literature review was conducted according to the Preferred Reporting Items for Systematic reviews and Meta-Analysis guidelines. After assessing the eligibility of journal manuscripts, conferences, book chapters and non-indexed documents, a total of 70 studies were included. A comprehensive analysis of the main characteristics and design choices of c-VEP-based BCIs was discussed, including stimulation paradigms, signal processing, modeling responses, applications, etc.Main results.The literature review showed that state-of-the-art c-VEP-based BCIs are able to provide an accurate control of the system with a large number of commands, high selection speeds and even without calibration. In general, a lack of validation in real setups was observed, especially regarding the validation with disabled populations. Future work should be focused toward developing self-paced c-VEP-based portable BCIs applied in real-world environments that could exploit the unique benefits of c-VEP paradigms. Some aspects such as asynchrony, unsupervised training, or code optimization still require further research and development.Significance.Despite the growing popularity of c-VEP-based BCIs, to the best of our knowledge, this is the first literature review on the topic. In addition to providing a joint discussion of the advances in the field, some future lines of research are suggested to contribute to the development of reliable plug-and-play c-VEP-based BCIs.
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Affiliation(s)
- Víctor Martínez-Cagigal
- Biomedical Engineering Group, E.T.S. Ingenieros de Telecomunicación, Paseo de Belén, 15, University of Valladolid, Valladolid, Spain.,Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain
| | - Jordy Thielen
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Eduardo Santamaría-Vázquez
- Biomedical Engineering Group, E.T.S. Ingenieros de Telecomunicación, Paseo de Belén, 15, University of Valladolid, Valladolid, Spain.,Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain
| | - Sergio Pérez-Velasco
- Biomedical Engineering Group, E.T.S. Ingenieros de Telecomunicación, Paseo de Belén, 15, University of Valladolid, Valladolid, Spain
| | - Peter Desain
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - Roberto Hornero
- Biomedical Engineering Group, E.T.S. Ingenieros de Telecomunicación, Paseo de Belén, 15, University of Valladolid, Valladolid, Spain.,Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain
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Kawala-Sterniuk A, Browarska N, Al-Bakri A, Pelc M, Zygarlicki J, Sidikova M, Martinek R, Gorzelanczyk EJ. Summary of over Fifty Years with Brain-Computer Interfaces-A Review. Brain Sci 2021; 11:43. [PMID: 33401571 PMCID: PMC7824107 DOI: 10.3390/brainsci11010043] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 12/25/2020] [Accepted: 12/27/2020] [Indexed: 11/16/2022] Open
Abstract
Over the last few decades, the Brain-Computer Interfaces have been gradually making their way to the epicenter of scientific interest. Many scientists from all around the world have contributed to the state of the art in this scientific domain by developing numerous tools and methods for brain signal acquisition and processing. Such a spectacular progress would not be achievable without accompanying technological development to equip the researchers with the proper devices providing what is absolutely necessary for any kind of discovery as the core of every analysis: the data reflecting the brain activity. The common effort has resulted in pushing the whole domain to the point where the communication between a human being and the external world through BCI interfaces is no longer science fiction but nowadays reality. In this work we present the most relevant aspects of the BCIs and all the milestones that have been made over nearly 50-year history of this research domain. We mention people who were pioneers in this area as well as we highlight all the technological and methodological advances that have transformed something available and understandable by a very few into something that has a potential to be a breathtaking change for so many. Aiming to fully understand how the human brain works is a very ambitious goal and it will surely take time to succeed. However, even that fraction of what has already been determined is sufficient e.g., to allow impaired people to regain control on their lives and significantly improve its quality. The more is discovered in this domain, the more benefit for all of us this can potentially bring.
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Affiliation(s)
- Aleksandra Kawala-Sterniuk
- Faculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, 45-758 Opole, Poland; (N.B.); (M.P.); (J.Z.)
| | - Natalia Browarska
- Faculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, 45-758 Opole, Poland; (N.B.); (M.P.); (J.Z.)
| | - Amir Al-Bakri
- Department of Biomedical Engineering, College of Engineering, University of Babylon, 51001 Babylon, Iraq;
| | - Mariusz Pelc
- Faculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, 45-758 Opole, Poland; (N.B.); (M.P.); (J.Z.)
- Department of Computing and Information Systems, University of Greenwich, London SE10 9LS, UK
| | - Jaroslaw Zygarlicki
- Faculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, 45-758 Opole, Poland; (N.B.); (M.P.); (J.Z.)
| | - Michaela Sidikova
- Department of Cybernetics and Biomedical Engineering, VSB-Technical University Ostrava—FEECS, 708 00 Ostrava-Poruba, Czech Republic; (M.S.); (R.M.)
| | - Radek Martinek
- Department of Cybernetics and Biomedical Engineering, VSB-Technical University Ostrava—FEECS, 708 00 Ostrava-Poruba, Czech Republic; (M.S.); (R.M.)
| | - Edward Jacek Gorzelanczyk
- Department of Theoretical Basis of BioMedical Sciences and Medical Informatics, Nicolaus Copernicus University, Collegium Medicum, 85-067 Bydgoszcz, Poland;
- Institute of Philosophy, Kazimierz Wielki University, 85-092 Bydgoszcz, Poland
- Babinski Specialist Psychiatric Healthcare Center, Outpatient Addiction Treatment, 91-229 Lodz, Poland
- The Society for the Substitution Treatment of Addiction “Medically Assisted Recovery”, 85-791 Bydgoszcz, Poland
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