1
|
Chen Y, Wang F, Li T, Zhao L, Gong A, Nan W, Ding P, Fu Y. Considerations and discussions on the clear definition and definite scope of brain-computer interfaces. Front Neurosci 2024; 18:1449208. [PMID: 39161655 PMCID: PMC11330831 DOI: 10.3389/fnins.2024.1449208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2024] [Accepted: 07/22/2024] [Indexed: 08/21/2024] Open
Abstract
Brain-computer interface (BCI) is a revolutionizing human-computer interaction with potential applications in both medical and non-medical fields, emerging as a cutting-edge and trending research direction. Increasing numbers of groups are engaging in BCI research and development. However, in recent years, there has been some confusion regarding BCI, including misleading and hyped propaganda about BCI, and even non-BCI technologies being labeled as BCI. Therefore, a clear definition and a definite scope for BCI are thoroughly considered and discussed in the paper, based on the existing definitions of BCI, including the six key or essential components of BCI. In the review, different from previous definitions of BCI, BCI paradigms and neural coding are explicitly included in the clear definition of BCI provided, and the BCI user (the brain) is clearly identified as a key component of the BCI system. Different people may have different viewpoints on the definition and scope of BCI, as well as some related issues, which are discussed in the article. This review argues that a clear definition and definite scope of BCI will benefit future research and commercial applications. It is hoped that this review will reduce some of the confusion surrounding BCI and promote sustainable development in this field.
Collapse
Affiliation(s)
- Yanxiao Chen
- Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China
- Brain Cognition and Brain-Computer Intelligence Integration Group, Kunming University of Science and Technology, Kunming, China
| | - Fan Wang
- Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China
- Brain Cognition and Brain-Computer Intelligence Integration Group, Kunming University of Science and Technology, Kunming, China
| | - Tianwen Li
- Brain Cognition and Brain-Computer Intelligence Integration Group, Kunming University of Science and Technology, Kunming, China
- Faculty of Science, Kunming University of Science and Technology, Kunming, China
| | - Lei Zhao
- Brain Cognition and Brain-Computer Intelligence Integration Group, Kunming University of Science and Technology, Kunming, China
- Faculty of Science, Kunming University of Science and Technology, Kunming, China
| | - Anmin Gong
- School of Information Engineering, Chinese People’s Armed Police Force Engineering University, Xi’an, China
| | - Wenya Nan
- School of Psychology, Shanghai Normal University, Shanghai, China
| | - Peng Ding
- Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China
- Brain Cognition and Brain-Computer Intelligence Integration Group, Kunming University of Science and Technology, Kunming, China
| | - Yunfa Fu
- Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China
- Brain Cognition and Brain-Computer Intelligence Integration Group, Kunming University of Science and Technology, Kunming, China
| |
Collapse
|
2
|
Zanona ADF, Piscitelli D, Seixas VM, Scipioni KRDDS, Bastos MSC, de Sá LCK, Monte-Silva K, Bolivar M, Solnik S, De Souza RF. Brain-computer interface combined with mental practice and occupational therapy enhances upper limb motor recovery, activities of daily living, and participation in subacute stroke. Front Neurol 2023; 13:1041978. [PMID: 36698872 PMCID: PMC9869053 DOI: 10.3389/fneur.2022.1041978] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 11/28/2022] [Indexed: 01/11/2023] Open
Abstract
Background We investigated the effects of brain-computer interface (BCI) combined with mental practice (MP) and occupational therapy (OT) on performance in activities of daily living (ADL) in stroke survivors. Methods Participants were randomized into two groups: experimental (n = 23, BCI controlling a hand exoskeleton combined with MP and OT) and control (n = 21, OT). Subjects were assessed with the functional independence measure (FIM), motor activity log (MAL), amount of use (MAL-AOM), and quality of movement (MAL-QOM). The box and blocks test (BBT) and the Jebsen hand functional test (JHFT) were used for the primary outcome of performance in ADL, while the Fugl-Meyer Assessment was used for the secondary outcome. Exoskeleton activation and the degree of motor imagery (measured as event-related desynchronization) were assessed in the experimental group. For the BCI, the EEG electrodes were placed on the regions of FC3, C3, CP3, FC4, C4, and CP4, according to the international 10-20 EEG system. The exoskeleton was placed on the affected hand. MP was based on functional tasks. OT consisted of ADL training, muscle mobilization, reaching tasks, manipulation and prehension, mirror therapy, and high-frequency therapeutic vibration. The protocol lasted 1 h, five times a week, for 2 weeks. Results There was a difference between baseline and post-intervention analysis for the experimental group in all evaluations: FIM (p = 0.001, d = 0.56), MAL-AOM (p = 0.001, d = 0.83), MAL-QOM (p = 0.006, d = 0.84), BBT (p = 0.004, d = 0.40), and JHFT (p = 0.001, d = 0.45). Within the experimental group, post-intervention improvements were detected in the degree of motor imagery (p < 0.001) and the amount of exoskeleton activations (p < 0.001). For the control group, differences were detected for MAL-AOM (p = 0.001, d = 0.72), MAL-QOM (p = 0.013, d = 0.50), and BBT (p = 0.005, d = 0.23). Notably, the effect sizes were larger for the experimental group. No differences were detected between groups at post-intervention. Conclusion BCI combined with MP and OT is a promising tool for promoting sensorimotor recovery of the upper limb and functional independence in subacute post-stroke survivors.
Collapse
Affiliation(s)
- Aristela de Freitas Zanona
- Department of Occupational Therapy and Graduate Program in Applied Health Sciences, Federal University of Sergipe, São Cristóvão, Sergipe, Brazil,*Correspondence: Aristela de Freitas Zanona ✉
| | - Daniele Piscitelli
- School of Medicine and Surgery, University of Milano-Bicocca, Milan, Italy,Department of Kinesiology, University of Connecticut, Storrs, CT, United States
| | - Valquiria Martins Seixas
- Department of Occupational Therapy and Graduate Program in Applied Health Sciences, Federal University of Sergipe, São Cristóvão, Sergipe, Brazil
| | | | | | | | - Kátia Monte-Silva
- Department of Physical Therapy, Federal University of Pernambuco, Recife, Pernambuco, Brazil
| | - Miburge Bolivar
- Department of Occupational Therapy and Graduate Program in Applied Health Sciences, Federal University of Sergipe, São Cristóvão, Sergipe, Brazil
| | - Stanislaw Solnik
- Department of Physical Therapy, University of North Georgia, Dahlonega, GA, United States,Department of Physical Education, Wroclaw University of Health and Sport Sciences, Wroclaw, Poland
| | - Raphael Fabricio De Souza
- Department of Occupational Therapy and Graduate Program in Applied Health Sciences, Federal University of Sergipe, São Cristóvão, Sergipe, Brazil
| |
Collapse
|
3
|
Camargo-Vargas D, Callejas-Cuervo M, Mazzoleni S. Brain-Computer Interfaces Systems for Upper and Lower Limb Rehabilitation: A Systematic Review. SENSORS (BASEL, SWITZERLAND) 2021; 21:4312. [PMID: 34202546 PMCID: PMC8271710 DOI: 10.3390/s21134312] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 06/09/2021] [Accepted: 06/18/2021] [Indexed: 12/22/2022]
Abstract
In recent years, various studies have demonstrated the potential of electroencephalographic (EEG) signals for the development of brain-computer interfaces (BCIs) in the rehabilitation of human limbs. This article is a systematic review of the state of the art and opportunities in the development of BCIs for the rehabilitation of upper and lower limbs of the human body. The systematic review was conducted in databases considering using EEG signals, interface proposals to rehabilitate upper/lower limbs using motor intention or movement assistance and utilizing virtual environments in feedback. Studies that did not specify which processing system was used were excluded. Analyses of the design processing or reviews were excluded as well. It was identified that 11 corresponded to applications to rehabilitate upper limbs, six to lower limbs, and one to both. Likewise, six combined visual/auditory feedback, two haptic/visual, and two visual/auditory/haptic. In addition, four had fully immersive virtual reality (VR), three semi-immersive VR, and 11 non-immersive VR. In summary, the studies have demonstrated that using EEG signals, and user feedback offer benefits including cost, effectiveness, better training, user motivation and there is a need to continue developing interfaces that are accessible to users, and that integrate feedback techniques.
Collapse
Affiliation(s)
- Daniela Camargo-Vargas
- Software Research Group, Universidad Pedagógica y Tecnológica de Colombia, Tunja 150002, Colombia;
| | - Mauro Callejas-Cuervo
- School of Computer Science, Universidad Pedagógica y Tecnológica de Colombia, Tunja 150002, Colombia
| | - Stefano Mazzoleni
- Department of Electrical and Information Engineering, Politecnico di Bari, 70126 Bari, Italy;
| |
Collapse
|
4
|
Klein E. Ethics and the emergence of brain-computer interface medicine. HANDBOOK OF CLINICAL NEUROLOGY 2020; 168:329-339. [PMID: 32164863 DOI: 10.1016/b978-0-444-63934-9.00024-x] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Brain-computer interface (BCI) technology will usher in profound changes to the practice of medicine. BCI devices, broadly defined as those capable of reading brain activity and translating this into operation of a device, will offer patients and clinicians new ways to address impairments of communication, movement, sensation, and mental health. These new capabilities will bring new responsibilities and raise a diverse set of ethical challenges. One way to understand and begin to address these challenges is to view them in terms of the goals of medicine. In this chapter, different ways in which BCI technology may subserve the goals of medicine is explored. This is followed by articulation of additional goals particularly relevant to BCI technology: neural diversity, neural privacy, agency, and authenticity. The goals of medicine provide a useful ethical framework for the introduction of BCI devices into medicine.
Collapse
Affiliation(s)
- Eran Klein
- Department of Neurology, Oregon Health and Science University, Portland, OR, United States; Department of Philosophy, University of Washington, Seattle, WA, United States.
| |
Collapse
|