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Starke G, Akmazoglu TB, Colucci A, Vermehren M, van Beinum A, Buthut M, Soekadar SR, Bublitz C, Chandler JA, Ienca M. Qualitative studies involving users of clinical neurotechnology: a scoping review. BMC Med Ethics 2024; 25:89. [PMID: 39138452 PMCID: PMC11323440 DOI: 10.1186/s12910-024-01087-z] [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] [Received: 01/23/2023] [Accepted: 08/02/2024] [Indexed: 08/15/2024] Open
Abstract
BACKGROUND The rise of a new generation of intelligent neuroprostheses, brain-computer interfaces (BCI) and adaptive closed-loop brain stimulation devices hastens the clinical deployment of neurotechnologies to treat neurological and neuropsychiatric disorders. However, it remains unclear how these nascent technologies may impact the subjective experience of their users. To inform this debate, it is crucial to have a solid understanding how more established current technologies already affect their users. In recent years, researchers have used qualitative research methods to explore the subjective experience of individuals who become users of clinical neurotechnology. Yet, a synthesis of these more recent findings focusing on qualitative methods is still lacking. METHODS To address this gap in the literature, we systematically searched five databases for original research articles that investigated subjective experiences of persons using or receiving neuroprosthetics, BCIs or neuromodulation with qualitative interviews and raised normative questions. RESULTS 36 research articles were included and analysed using qualitative content analysis. Our findings synthesise the current scientific literature and reveal a pronounced focus on usability and other technical aspects of user experience. In parallel, they highlight a relative neglect of considerations regarding agency, self-perception, personal identity and subjective experience. CONCLUSIONS Our synthesis of the existing qualitative literature on clinical neurotechnology highlights the need to expand the current methodological focus as to investigate also non-technical aspects of user experience. Given the critical role considerations of agency, self-perception and personal identity play in assessing the ethical and legal significance of these technologies, our findings reveal a critical gap in the existing literature. This review provides a comprehensive synthesis of the current qualitative research landscape on neurotechnology and the limitations thereof. These findings can inform researchers on how to study the subjective experience of neurotechnology users more holistically and build patient-centred neurotechnology.
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Grants
- HYBRIDMIND (SNSF 32NE30_199436; BMBF, 01GP2121A and -B), ERA-NET NEURON
- HYBRIDMIND (SNSF 32NE30_199436; BMBF, 01GP2121A and -B), ERA-NET NEURON
- HYBRIDMIND (SNSF 32NE30_199436; BMBF, 01GP2121A and -B), ERA-NET NEURON
- HYBRIDMIND (SNSF 32NE30_199436; BMBF, 01GP2121A and -B), ERA-NET NEURON
- HYBRIDMIND (SNSF 32NE30_199436; BMBF, 01GP2121A and -B), ERA-NET NEURON
- HYBRIDMIND (SNSF 32NE30_199436; BMBF, 01GP2121A and -B), ERA-NET NEURON
- HYBRIDMIND (SNSF 32NE30_199436; BMBF, 01GP2121A and -B), ERA-NET NEURON
- HYBRIDMIND (SNSF 32NE30_199436; BMBF, 01GP2121A and -B), ERA-NET NEURON
- HYBRIDMIND (SNSF 32NE30_199436; BMBF, 01GP2121A and -B), ERA-NET NEURON
- HYBRIDMIND (SNSF 32NE30_199436; BMBF, 01GP2121A and -B), ERA-NET NEURON
- NGBMI (759370) European Research Council (ERC)
- NGBMI (759370) European Research Council (ERC)
- NGBMI (759370) European Research Council (ERC)
- NGBMI (759370) European Research Council (ERC)
- SSMART (01DR21025A), NEO (13GW0483C), QHMI (03ZU1110DD), QSHIFT (01UX2211) and NeuroQ (13N16486) Federal Ministry of Research and Education (BMBF)
- SSMART (01DR21025A), NEO (13GW0483C), QHMI (03ZU1110DD), QSHIFT (01UX2211) and NeuroQ (13N16486) Federal Ministry of Research and Education (BMBF)
- SSMART (01DR21025A), NEO (13GW0483C), QHMI (03ZU1110DD), QSHIFT (01UX2211) and NeuroQ (13N16486) Federal Ministry of Research and Education (BMBF)
- SSMART (01DR21025A), NEO (13GW0483C), QHMI (03ZU1110DD), QSHIFT (01UX2211) and NeuroQ (13N16486) Federal Ministry of Research and Education (BMBF)
- A-2019-558 Einstein Foundation Berlin
- A-2019-558 Einstein Foundation Berlin
- A-2019-558 Einstein Foundation Berlin
- A-2019-558 Einstein Foundation Berlin
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Affiliation(s)
- Georg Starke
- Faculty of Medicine, Institute for History and Ethics of Medicine, Technical University of Munich, Munich, Germany.
- College of Humanities, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
| | | | - Annalisa Colucci
- Clinical Neurotechnology Laboratory, Department of Psychiatry and Neurosciences at the Charité Campus Mitte, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Mareike Vermehren
- Clinical Neurotechnology Laboratory, Department of Psychiatry and Neurosciences at the Charité Campus Mitte, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Amanda van Beinum
- Centre for Health Law Policy and Ethics, University of Ottawa, Ottawa, ON, Canada
| | - Maria Buthut
- Clinical Neurotechnology Laboratory, Department of Psychiatry and Neurosciences at the Charité Campus Mitte, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Surjo R Soekadar
- Clinical Neurotechnology Laboratory, Department of Psychiatry and Neurosciences at the Charité Campus Mitte, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | | | - Jennifer A Chandler
- Bertram Loeb Research Chair, Faculty of Law, University of Ottawa, Ottawa, ON, Canada
| | - Marcello Ienca
- Faculty of Medicine, Institute for History and Ethics of Medicine, Technical University of Munich, Munich, Germany
- College of Humanities, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
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Urian D, Higgins N, Abreu-Melon JM, Nagam V, González-Márquez C, Oppong A, Nsaanee B. Neglected Stakeholder Perspectives in Qualitative Neural Implant Research. AJOB Neurosci 2024; 15:184-187. [PMID: 39018226 DOI: 10.1080/21507740.2024.2365132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/19/2024]
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Livanis E, Voultsos P, Vadikolias K, Pantazakos P, Tsaroucha A. Understanding the Ethical Issues of Brain-Computer Interfaces (BCIs): A Blessing or the Beginning of a Dystopian Future? Cureus 2024; 16:e58243. [PMID: 38745805 PMCID: PMC11091939 DOI: 10.7759/cureus.58243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/14/2024] [Indexed: 05/16/2024] Open
Abstract
In recent years, scientific discoveries in the field of neuroscience combined with developments in the field of artificial intelligence have led to the development of a range of neurotechnologies. Advances in neuroimaging systems, neurostimulators, and brain-computer interfaces (BCIs) are leading to new ways of enhancing, controlling, and "reading" the brain. In addition, although BCIs were developed and used primarily in the medical field, they are now increasingly applied in other fields (entertainment, marketing, education, defense industry). We conducted a literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to provide background information about ethical issues related to the use of BCIs. Among the ethical issues that emerged from the thematic data analysis of the reviewed studies included questions revolving around human dignity, personhood and autonomy, user safety, stigma and discrimination, privacy and security, responsibility, research ethics, and social justice (including access to this technology). This paper attempts to address the various aspects of these concerns. A variety of distinct ethical issues were identified, which, for the most part, were in line with the findings of prior research. However, we identified two nuances, which are related to the empirical research on ethical issues related to BCIs and the impact of BCIs on international relationships. The paper also highlights the need for the cooperation of all stakeholders to ensure the ethical development and use of this technology and concludes with several recommendations. The principles of bioethics provide an initial guiding framework, which, however, should be revised in the current artificial intelligence landscape so as to be responsive to challenges posed by the development and use of BCIs.
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Affiliation(s)
- Efstratios Livanis
- Department of Accounting and Finance, University of Macedonia, Thessaloniki, GRC
- Postgraduate Program on Bioethics, School of Medicine, Democritus University of Thrace, Alexandroupoli, GRC
| | - Polychronis Voultsos
- Laboratory of Forensic Medicine & Toxicology (Medical Law and Ethics) School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, GRC
- Postgraduate Program on Bioethics, School of Medicine, Democritus University of Thrace, Alexandroupoli, GRC
| | - Konstantinos Vadikolias
- Postgraduate Program on Bioethics, School of Medicine, Democritus University of Thrace, Alexandroupoli, GRC
- Department of Neurology, University Hospital of Alexandroupolis, Alexandroupoli, GRC
| | - Panagiotis Pantazakos
- Department of Philosophy, School of Philosophy, National and Kapodistrian University of Athens, Athens, GRC
- Postgraduate Program on Bioethics, School of Medicine, Democritus University of Thrace, Alexandroupoli, GRC
| | - Alexandra Tsaroucha
- Postgraduate Program on Bioethics, School of Medicine, Democritus University of Thrace, Alexandroupoli, GRC
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Sample M, Sattler S, Boehlen W, Racine E. Brain-computer interfaces, disability, and the stigma of refusal: A factorial vignette study. PUBLIC UNDERSTANDING OF SCIENCE (BRISTOL, ENGLAND) 2023; 32:522-542. [PMID: 36633302 PMCID: PMC10115937 DOI: 10.1177/09636625221141663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
As brain-computer interfaces are promoted as assistive devices, some researchers worry that this promise to "restore" individuals worsens stigma toward disabled people and fosters unrealistic expectations. In three web-based survey experiments with vignettes, we tested how refusing a brain-computer interface in the context of disability affects cognitive (blame), emotional (anger), and behavioral (coercion) stigmatizing attitudes (Experiment 1, N = 222) and whether the effect of a refusal is affected by the level of brain-computer interface functioning (Experiment 2, N = 620) or the risk of malfunctioning (Experiment 3, N = 620). We found that refusing a brain-computer interface increased blame and anger, while brain-computer interface functioning did change the effect of a refusal. Higher risks of device malfunctioning partially reduced stigmatizing attitudes and moderated the effect of refusal. This suggests that information about disabled people who refuse a technology can increase stigma toward them. This finding has serious implications for brain-computer interface regulation, media coverage, and the prevention of ableism.
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Affiliation(s)
- Matthew Sample
- Matthew Sample, Centre for Ethics and Law in the Life Sciences, Leibniz University Hannover, 30167 Hannover, Germany.
| | | | - Wren Boehlen
- Institut de recherches cliniques de Montréal, Canada
| | - Eric Racine
- Institut de recherches cliniques de Montréal, Canada; Université de Montréal, Canada; McGill University, Canada
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Saibene A, Caglioni M, Corchs S, Gasparini F. EEG-Based BCIs on Motor Imagery Paradigm Using Wearable Technologies: A Systematic Review. SENSORS (BASEL, SWITZERLAND) 2023; 23:2798. [PMID: 36905004 PMCID: PMC10007053 DOI: 10.3390/s23052798] [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: 02/01/2023] [Revised: 02/21/2023] [Accepted: 02/28/2023] [Indexed: 06/18/2023]
Abstract
In recent decades, the automatic recognition and interpretation of brain waves acquired by electroencephalographic (EEG) technologies have undergone remarkable growth, leading to a consequent rapid development of brain-computer interfaces (BCIs). EEG-based BCIs are non-invasive systems that allow communication between a human being and an external device interpreting brain activity directly. Thanks to the advances in neurotechnologies, and especially in the field of wearable devices, BCIs are now also employed outside medical and clinical applications. Within this context, this paper proposes a systematic review of EEG-based BCIs, focusing on one of the most promising paradigms based on motor imagery (MI) and limiting the analysis to applications that adopt wearable devices. This review aims to evaluate the maturity levels of these systems, both from the technological and computational points of view. The selection of papers has been performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), leading to 84 publications considered in the last ten years (from 2012 to 2022). Besides technological and computational aspects, this review also aims to systematically list experimental paradigms and available datasets in order to identify benchmarks and guidelines for the development of new applications and computational models.
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Affiliation(s)
- Aurora Saibene
- Department of Informatics, Systems and Communication, University of Milano-Bicocca, Viale Sarca 336, 20126 Milano, Italy
- NeuroMI, Milan Center for Neuroscience, Piazza dell’Ateneo Nuovo 1, 20126 Milano, Italy
| | - Mirko Caglioni
- Department of Informatics, Systems and Communication, University of Milano-Bicocca, Viale Sarca 336, 20126 Milano, Italy
| | - Silvia Corchs
- NeuroMI, Milan Center for Neuroscience, Piazza dell’Ateneo Nuovo 1, 20126 Milano, Italy
- Department of Theoretical and Applied Sciences, University of Insubria, Via J. H. Dunant 3, 21100 Varese, Italy
| | - Francesca Gasparini
- Department of Informatics, Systems and Communication, University of Milano-Bicocca, Viale Sarca 336, 20126 Milano, Italy
- NeuroMI, Milan Center for Neuroscience, Piazza dell’Ateneo Nuovo 1, 20126 Milano, Italy
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Identifying Thematics in a Brain-Computer Interface Research. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2023; 2023:2793211. [PMID: 36643889 PMCID: PMC9833923 DOI: 10.1155/2023/2793211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 12/21/2022] [Accepted: 12/24/2022] [Indexed: 01/05/2023]
Abstract
This umbrella review is motivated to understand the shift in research themes on brain-computer interfacing (BCI) and it determined that a shift away from themes that focus on medical advancement and system development to applications that included education, marketing, gaming, safety, and security has occurred. The background of this review examined aspects of BCI categorisation, neuroimaging methods, brain control signal classification, applications, and ethics. The specific area of BCI software and hardware development was not examined. A search using One Search was undertaken and 92 BCI reviews were selected for inclusion. Publication demographics indicate the average number of authors on review papers considered was 4.2 ± 1.8. The results also indicate a rapid increase in the number of BCI reviews from 2003, with only three reviews before that period, two in 1972, and one in 1996. While BCI authors were predominantly Euro-American in early reviews, this shifted to a more global authorship, which China dominated by 2020-2022. The review revealed six disciplines associated with BCI systems: life sciences and biomedicine (n = 42), neurosciences and neurology (n = 35), and rehabilitation (n = 20); (2) the second domain centred on the theme of functionality: computer science (n = 20), engineering (n = 28) and technology (n = 38). There was a thematic shift from understanding brain function and modes of interfacing BCI systems to more applied research novel areas of research-identified surround artificial intelligence, including machine learning, pre-processing, and deep learning. As BCI systems become more invasive in the lives of "normal" individuals, it is expected that there will be a refocus and thematic shift towards increased research into ethical issues and the need for legal oversight in BCI application.
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Pitt KM, Brumberg JS. Evaluating the perspectives of those with severe physical impairments while learning BCI control of a commercial augmentative and alternative communication paradigm. Assist Technol 2023; 35:74-82. [PMID: 34184974 PMCID: PMC8742840 DOI: 10.1080/10400435.2021.1949405] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/21/2021] [Indexed: 01/11/2023] Open
Abstract
Augmentative and alternative communication (AAC) techniques can provide access to communication for individuals with severe physical impairments. Brain-computer interface (BCI) access techniques may serve alongside existing AAC access methods to provide communication device control. However, there is limited information available about how individual perspectives change with motor-based BCI-AAC learning. Four individuals with ALS completed 12 BCI-AAC training sessions in which they made letter selections during an automatic row-column scanning pattern via a motor-based BCI-AAC. Recurring measures were taken before and after each BCI-AAC training session to evaluate changes associated with BCI-AAC performance, and included measures of fatigue, frustration, mental effort, physical effort, device satisfaction, and overall ease of device control. Levels of pre- to post-fatigue were low for use of the BCI-AAC system. However, participants indicated different perceptions of the term fatigue, with three participants discussing fatigue to be generally synonymous with physical effort, and one mental effort. Satisfaction with the BCI-AAC system was related to BCI-AAC performance for two participants, and levels of frustration for two participants. Considering a range of person-centered measures in future clinical BCI-AAC applications is important for optimizing and standardizing BCI-AAC assessment procedures.
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Affiliation(s)
- Kevin M Pitt
- Department of Special Education and Communication Disorders, University of Nebraska-Lincoln, Lincoln, Nebraska, USA
| | - Jonathan S Brumberg
- Department of Speech-Language-Hearing: Sciences & Disorders, University of Kansas, Lawrence, Kansas, USA
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Public attitudes towards neurotechnology: Findings from two experiments concerning Brain Stimulation Devices (BSDs) and Brain-Computer Interfaces (BCIs). PLoS One 2022; 17:e0275454. [DOI: 10.1371/journal.pone.0275454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 09/17/2022] [Indexed: 11/10/2022] Open
Abstract
This study contributes to the emerging literature on public perceptions of neurotechnological devices (NTDs) in their medical and non-medical applications, depending on their invasiveness, framing effects, and interindividual differences related to personal needs and values. We conducted two web-based between-subject experiments (2×2×2) using a representative, nation-wide sample of the adult population in Germany. Using vignettes describing how two NTDs, brain stimulation devices (BSDs; NExperiment 1 = 1,090) and brain-computer interfaces (BCIs; NExperiment 2 = 1,089), function, we randomly varied the purpose (treatment vs. enhancement) and invasiveness (noninvasive vs. invasive) of the NTD, and assessed framing effects (variable order of assessing moral acceptability first vs. willingness to use first). We found a moderate moral acceptance and willingness to use BSDs and BCIs. Respondents preferred treatment over enhancement purposes and noninvasive over invasive devices. We also found a framing effect and explored the role of personal characteristics as indicators of personal needs and values (e.g., stress, religiosity, and gender). Our results suggest that the future demand for BSDs or BCIs may depend on the purpose, invasiveness, and personal needs and values. These insights can inform technology developers about the public’s needs and concerns, and enrich legal and ethical debates.
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Valeriani D, Santoro F, Ienca M. The present and future of neural interfaces. Front Neurorobot 2022; 16:953968. [PMID: 36304780 PMCID: PMC9592849 DOI: 10.3389/fnbot.2022.953968] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 07/13/2022] [Indexed: 11/18/2022] Open
Abstract
The 2020's decade will likely witness an unprecedented development and deployment of neurotechnologies for human rehabilitation, personalized use, and cognitive or other enhancement. New materials and algorithms are already enabling active brain monitoring and are allowing the development of biohybrid and neuromorphic systems that can adapt to the brain. Novel brain-computer interfaces (BCIs) have been proposed to tackle a variety of enhancement and therapeutic challenges, from improving decision-making to modulating mood disorders. While these BCIs have generally been developed in an open-loop modality to optimize their internal neural decoders, this decade will increasingly witness their validation in closed-loop systems that are able to continuously adapt to the user's mental states. Therefore, a proactive ethical approach is needed to ensure that these new technological developments go hand in hand with the development of a sound ethical framework. In this perspective article, we summarize recent developments in neural interfaces, ranging from neurohybrid synapses to closed-loop BCIs, and thereby identify the most promising macro-trends in BCI research, such as simulating vs. interfacing the brain, brain recording vs. brain stimulation, and hardware vs. software technology. Particular attention is devoted to central nervous system interfaces, especially those with application in healthcare and human enhancement. Finally, we critically assess the possible futures of neural interfacing and analyze the short- and long-term implications of such neurotechnologies.
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Affiliation(s)
| | - Francesca Santoro
- Institute for Biological Information Processing - Bioelectronics, IBI-3, Forschungszentrum Juelich, Juelich, Germany
- Faculty of Electrical Engineering and Information Technology, RWTH Aachen University, Aachen, Germany
| | - Marcello Ienca
- College of Humanities, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland
- *Correspondence: Marcello Ienca
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Moreno J, Gross ML, Becker J, Hereth B, Shortland ND, Evans NG. The ethics of AI-assisted warfighter enhancement research and experimentation: Historical perspectives and ethical challenges. Front Big Data 2022; 5:978734. [PMID: 36156934 PMCID: PMC9500287 DOI: 10.3389/fdata.2022.978734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Accepted: 08/08/2022] [Indexed: 11/13/2022] Open
Abstract
The military applications of AI raise myriad ethical challenges. Critical among them is how AI integrates with human decision making to enhance cognitive performance on the battlefield. AI applications range from augmented reality devices to assist learning and improve training to implantable Brain-Computer Interfaces (BCI) to create bionic "super soldiers." As these technologies mature, AI-wired warfighters face potential affronts to cognitive liberty, psychological and physiological health risks and obstacles to integrating into military and civil society during their service and upon discharge. Before coming online and operational, however, AI-assisted technologies and neural interfaces require extensive research and human experimentation. Each endeavor raises additional ethical concerns that have been historically ignored thereby leaving military and medical scientists without a cogent ethics protocol for sustainable research. In this way, this paper is a "prequel" to the current debate over enhancement which largely considers neuro-technologies once they are already out the door and operational. To lay the ethics foundation for AI-assisted warfighter enhancement research, we present an historical overview of its technological development followed by a presentation of salient ethics research issues (ICRC, 2006). We begin with a historical survey of AI neuro-enhancement research highlighting the ethics lacunae of its development. We demonstrate the unique ethical problems posed by the convergence of several technologies in the military research setting. Then we address these deficiencies by emphasizing how AI-assisted warfighter enhancement research must pay particular attention to military necessity, and the medical and military cost-benefit tradeoffs of emerging technologies, all attending to the unique status of warfighters as experimental subjects. Finally, our focus is the enhancement of friendly or compatriot warfighters and not, as others have focused, enhancements intended to pacify enemy warfighters.
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Affiliation(s)
- Jonathan Moreno
- Department of Bioethics, School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | | | - Jack Becker
- Harvard Law School, Cambridge, MA, United States
| | - Blake Hereth
- Department of Philosophy, University of Massachusetts at Lowell, Lowell, MA, United States
| | - Neil D. Shortland
- School of Criminology and Justice Studies, University of Massachusetts at Lowell, Lowell, MA, United States
| | - Nicholas G. Evans
- Department of Philosophy, University of Massachusetts at Lowell, Lowell, MA, United States
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Williams SC, Horsfall HL, Funnell JP, Hanrahan JG, Schaefer AT, Muirhead W, Marcus HJ. Neurosurgical Team Acceptability of Brain-Computer Interfaces: A Two-Stage International Cross-Sectional Survey. World Neurosurg 2022; 164:e884-e898. [PMID: 35623610 PMCID: PMC10444691 DOI: 10.1016/j.wneu.2022.05.062] [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] [Received: 04/10/2022] [Accepted: 05/15/2022] [Indexed: 11/29/2022]
Abstract
OBJECTIVE Invasive brain-computer interfaces (BCIs) require neurosurgical implantation, which confers a range of risks. Despite this situation, no studies have assessed the acceptability of invasive BCIs among the neurosurgical team. This study aims to establish baseline knowledge of BCIs within the neurosurgical team and identify attitudes toward different applications of invasive BCI. METHODS A 2-stage cross-sectional international survey of the neurosurgical team (neurosurgeons, anesthetists, and operating room nurses) was conducted. Results from the first, qualitative, survey were used to guide the second-stage quantitative survey, which assessed acceptability of invasive BCI applications. Five-part Likert scales were used to collect quantitative data. Surveys were distributed internationally via social media and collaborators. RESULTS A total of 108 qualitative responses were collected. Themes included the promise of BCIs positively affecting disease targets, concerns regarding stability, and an overall positive emotional reaction to BCI technology. The quantitative survey generated 538 responses from 32 countries. Baseline knowledge of BCI technology was poor, with 9% claiming to have a good or expert knowledge of BCIs. Acceptability of invasive BCI for rehabilitative purposes was >80%. Invasive BCI for augmentation in healthy populations divided opinion. CONCLUSIONS The neurosurgical team's view of the acceptability of invasive BCI was divided across a range of indications. Some applications (e.g., stroke rehabilitation) were viewed as more appropriate than other applications (e.g., augmentation for military use). This range in views highlights the need for stakeholder consultation on acceptable use cases along with regulation and guidance to govern initial BCI implantations if patients are to realize the potential benefits.
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Affiliation(s)
- Simon C Williams
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom; Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), London, United Kingdom.
| | - Hugo Layard Horsfall
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom; Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), London, United Kingdom
| | - Jonathan P Funnell
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom; Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), London, United Kingdom
| | - John G Hanrahan
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom; Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), London, United Kingdom
| | - Andreas T Schaefer
- The Francis Crick Institute, Sensory Circuits and Neurotechnology Laboratory, London, United Kingdom; Department of Neuroscience, Physiology & Pharmacology, University College London, London, United Kingdom
| | - William Muirhead
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom; Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), London, United Kingdom
| | - Hani J Marcus
- Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, United Kingdom; Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), London, United Kingdom
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van Velthoven EAM, van Stuijvenberg OC, Haselager DRE, Broekman M, Chen X, Roelfsema P, Bredenoord AL, Jongsma KR. Ethical implications of visual neuroprostheses-a systematic review. J Neural Eng 2022; 19. [PMID: 35475424 DOI: 10.1088/1741-2552/ac65b2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 04/08/2022] [Indexed: 11/12/2022]
Abstract
Objective. The aim of this review was to systematically identify the ethical implications of visual neuroprostheses.Approach. A systematic search was performed in both PubMed and Embase using a search string that combined synonyms for visual neuroprostheses, brain-computer interfaces (BCIs), cochlear implants (CIs), and ethics. We chose to include literature on BCIs and CIs, because of their ethically relavant similarities and functional parallels with visual neuroprostheses.Main results. We included 84 articles in total. Six focused specifically on visual prostheses. The other articles focused more broadly on neurotechnologies, on BCIs or CIs. We identified 169 ethical implications that have been categorized under seven main themes: (a) benefits for health and well-being; (b) harm and risk; (c) autonomy; (d) societal effects; (e) clinical research; (f) regulation and governance; and (g) involvement of experts, patients and the public.Significance. The development and clinical use of visual neuroprostheses is accompanied by ethical issues that should be considered early in the technological development process. Though there is ample literature on the ethical implications of other types of neuroprostheses, such as motor neuroprostheses and CIs, there is a significant gap in the literature regarding the ethical implications of visual neuroprostheses. Our findings can serve as a starting point for further research and normative analysis.
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Affiliation(s)
- E A M van Velthoven
- Department of Medical Humanities, Julius Center, University Medical Center Utrecht, PO Box 85500, Utrecht, 3508 GA, The Netherlands
| | - O C van Stuijvenberg
- Department of Medical Humanities, Julius Center, University Medical Center Utrecht, PO Box 85500, Utrecht, 3508 GA, The Netherlands
| | - D R E Haselager
- Department of Medical Humanities, Julius Center, University Medical Center Utrecht, PO Box 85500, Utrecht, 3508 GA, The Netherlands
| | - M Broekman
- Department of Neurosurgery, Haaglanden Medical Center, The Hague, The Netherlands.,Department of Neurosurgery, Leiden Medical Center, Leiden, The Netherlands
| | - X Chen
- Department of Vision & Cognition, Netherlands Institute for Neuroscience, Meibergdreef 47, 1105 BA Amsterdam, The Netherlands
| | - P Roelfsema
- Department of Vision & Cognition, Netherlands Institute for Neuroscience, Meibergdreef 47, 1105 BA Amsterdam, The Netherlands.,Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, VU University, Amsterdam, The Netherlands.,Department of Psychiatry, Academic Medical Center, Amsterdam, The Netherlands
| | - A L Bredenoord
- Erasmus School of Philosophy, Erasmus University Rotterdam, Rotterdam, The Netherlands
| | - K R Jongsma
- Department of Medical Humanities, Julius Center, University Medical Center Utrecht, PO Box 85500, Utrecht, 3508 GA, The Netherlands
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13
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Chandler JA, Van der Loos KI, Boehnke S, Beaudry JS, Buchman DZ, Illes J. Brain Computer Interfaces and Communication Disabilities: Ethical, Legal, and Social Aspects of Decoding Speech From the Brain. Front Hum Neurosci 2022; 16:841035. [PMID: 35529778 PMCID: PMC9069963 DOI: 10.3389/fnhum.2022.841035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 03/03/2022] [Indexed: 11/28/2022] Open
Abstract
A brain-computer interface technology that can decode the neural signals associated with attempted but unarticulated speech could offer a future efficient means of communication for people with severe motor impairments. Recent demonstrations have validated this approach. Here we assume that it will be possible in future to decode imagined (i.e., attempted but unarticulated) speech in people with severe motor impairments, and we consider the characteristics that could maximize the social utility of a BCI for communication. As a social interaction, communication involves the needs and goals of both speaker and listener, particularly in contexts that have significant potential consequences. We explore three high-consequence legal situations in which neurally-decoded speech could have implications: Testimony, where decoded speech is used as evidence; Consent and Capacity, where it may be used as a means of agency and participation such as consent to medical treatment; and Harm, where such communications may be networked or may cause harm to others. We then illustrate how design choices might impact the social and legal acceptability of these technologies.
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Affiliation(s)
- Jennifer A. Chandler
- Bertram Loeb Research Chair, Faculty of Law, University of Ottawa, Ottawa, ON, Canada
- *Correspondence: Jennifer A. Chandler,
| | | | - Susan Boehnke
- Centre for Neuroscience Studies, Queen’s University, Kingston, ON, Canada
| | - Jonas S. Beaudry
- Institute for Health and Social Policy (IHSP) and Faculty of Law, McGill University, Montreal, QC, Canada
| | - Daniel Z. Buchman
- Centre for Addiction and Mental Health, Dalla Lana School of Public Health, Krembil Research Institute, University of Toronto Joint Centre for Bioethics, Toronto, ON, Canada
| | - Judy Illes
- Division of Neurology, Department of Medicine, University of British Columbia, Vancouver, BC, Canada
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14
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Villamil V, Wolbring G. Influencing discussions and use of neuroadvancements as professionals and citizens: Perspectives of Canadian speech-language pathologists and audiologists. Work 2022; 71:565-584. [DOI: 10.3233/wor-205104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND: Early involvement of stakeholders in neuroethics and neurogovernance discourses of neuroscientific and neurotechnological advancements is seen as essential to curtail negative consequences. Speech-language pathologists (SLPs) and audiologists (AUs) make use of neuroadvancements including cochlear implants, brain-computer interfaces, and deep-brain stimulation. Although they have a stake in neuroethics and neurogovernance discussions, they are rarely mentioned in having a role, whether as professionals or as citizens. OBJECTIVE: The objective of the study was to explore the role of SLPs and AUs as professionals and citizens in neuroethics and neurogovernance discussions and examine the utility of lifelong learning mechanisms to learn about the implications of neuroadvancements to contribute in a meaningful way to these discussions. METHODS: Semi-structured interviews conducted with 7 SLPs and 3 AUs were analyzed using thematic analysis. RESULTS: Participants stated that their roles expected from them as professionals and as citizens indicate the importance to be knowledgeable on ethical, legal, and social implications of neuroadvancements and that lifelong learning is not used to learn about these implications. CONCLUSION: More must be done to facilitate the participation of SLPs and AUs in neuroethics and neurogovernance discussions, which would enrich the neuroethics and neurogovernance discourses benefitting patients, professionals, and the public.
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Affiliation(s)
- Valentina Villamil
- Speech-Language Pathology, Faculty of Rehabilitation Medicine, University of Alberta, Edmonton, AB, Canada
| | - Gregor Wolbring
- Community Rehabilitation and Disability Studies, Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
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15
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Shankhdhar A, Verma PK, Agrawal P, Madaan V, Gupta C. Quality analysis for reliable complex multiclass neuroscience signal classification via electroencephalography. INTERNATIONAL JOURNAL OF QUALITY & RELIABILITY MANAGEMENT 2022. [DOI: 10.1108/ijqrm-07-2021-0237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
PurposeThe aim of this paper is to explore the brain–computer interface (BCI) as a methodology for generating awareness and increasing reliable use cases of the same so that an individual's quality of life can be enhanced via neuroscience and neural networks, and risk evaluation of certain experiments of BCI can be conducted in a proactive manner.Design/methodology/approachThis paper puts forward an efficient approach for an existing BCI device, which can enhance the performance of an electroencephalography (EEG) signal classifier in a composite multiclass problem and investigates the effects of sampling rate on feature extraction and multiple channels on the accuracy of a complex multiclass EEG signal. A one-dimensional convolutional neural network architecture is used to further classify and improve the quality of the EEG signals, and other algorithms are applied to test their variability. The paper further also dwells upon the combination of internet of things multimedia technology to be integrated with a customized design BCI network based on a conventionally used system known as the message query telemetry transport.FindingsAt the end of our implementation stage, 98% accuracy was achieved in a binary classification problem of classifying digit and non-digit stimuli, and 36% accuracy was observed in the classification of signals resulting from stimuli of digits 0 to 9.Originality/valueBCI, also known as the neural-control interface, is a device that helps a user reliably interact with a computer using only his/her brain activity, which is measured usually via EEG. An EEG machine is a quality device used for observing the neural activity and electric signals generated in certain parts of the human brain, which in turn can help us in studying the different core components of the human brain and how it functions to improve the quality of human life in general.
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16
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Le Bars S, Chokron S, Balp R, Douibi K, Waszak F. Theoretical Perspective on an Ideomotor Brain-Computer Interface: Toward a Naturalistic and Non-invasive Brain-Computer Interface Paradigm Based on Action-Effect Representation. Front Hum Neurosci 2021; 15:732764. [PMID: 34776904 PMCID: PMC8581635 DOI: 10.3389/fnhum.2021.732764] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 10/11/2021] [Indexed: 11/13/2022] Open
Abstract
Recent years have been marked by the fulgurant expansion of non-invasive Brain-Computer Interface (BCI) devices and applications in various contexts (medical, industrial etc.). This technology allows agents "to directly act with thoughts," bypassing the peripheral motor system. Interestingly, it is worth noting that typical non-invasive BCI paradigms remain distant from neuroscientific models of human voluntary action. Notably, bidirectional links between action and perception are constantly ignored in BCI experiments. In the current perspective article, we proposed an innovative BCI paradigm that is directly inspired by the ideomotor principle, which postulates that voluntary actions are driven by the anticipated representation of forthcoming perceptual effects. We believe that (1) adapting BCI paradigms could allow simple action-effect bindings and consequently action-effect predictions and (2) using neural underpinnings of those action-effect predictions as features of interest in AI methods, could lead to more accurate and naturalistic BCI-mediated actions.
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Affiliation(s)
- Solène Le Bars
- Altran Lab, Capgemini Engineering, Paris, France.,Université de Paris, INCC UMR 8002, CNRS, Paris, France
| | - Sylvie Chokron
- Université de Paris, INCC UMR 8002, CNRS, Paris, France.,Fondation Ophtalmologique Adolphe de Rothschild, Paris, France
| | - Rodrigo Balp
- Altran Lab, Capgemini Engineering, Paris, France
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17
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Sahonero-Alvarez G, Singh AK, Sayrafian K, Bianchi L, Roman-Gonzalez A. A Functional BCI Model by the P2731 Working Group: Transducer. BRAIN-COMPUTER INTERFACES 2021. [DOI: 10.1080/2326263x.2021.1968633] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
| | | | - Kamran Sayrafian
- Information Technology Laboratory, National Institute of Standards & Technology, Gaithersburg, USA
| | - Luigi Bianchi
- Civil Engineering and Computer Science Engineering Dept. Tor Vergata University of Rome, Rome, Italy
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18
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Douibi K, Le Bars S, Lemontey A, Nag L, Balp R, Breda G. Toward EEG-Based BCI Applications for Industry 4.0: Challenges and Possible Applications. Front Hum Neurosci 2021; 15:705064. [PMID: 34483868 PMCID: PMC8414547 DOI: 10.3389/fnhum.2021.705064] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Accepted: 07/20/2021] [Indexed: 11/13/2022] Open
Abstract
In the last few decades, Brain-Computer Interface (BCI) research has focused predominantly on clinical applications, notably to enable severely disabled people to interact with the environment. However, recent studies rely mostly on the use of non-invasive electroencephalographic (EEG) devices, suggesting that BCI might be ready to be used outside laboratories. In particular, Industry 4.0 is a rapidly evolving sector that aims to restructure traditional methods by deploying digital tools and cyber-physical systems. BCI-based solutions are attracting increasing attention in this field to support industrial performance by optimizing the cognitive load of industrial operators, facilitating human-robot interactions, and make operations in critical conditions more secure. Although these advancements seem promising, numerous aspects must be considered before developing any operational solutions. Indeed, the development of novel applications outside optimal laboratory conditions raises many challenges. In the current study, we carried out a detailed literature review to investigate the main challenges and present criteria relevant to the future deployment of BCI applications for Industry 4.0.
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Affiliation(s)
| | | | - Alice Lemontey
- Capgemini Engineering, Paris, France.,Ecole Strate Design, Sèvres, France
| | - Lipsa Nag
- Capgemini Engineering, Paris, France
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19
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Matarasso AK, Rieke JD, White K, Yusufali MM, Daly JJ. Combined real-time fMRI and real time fNIRS brain computer interface (BCI): Training of volitional wrist extension after stroke, a case series pilot study. PLoS One 2021; 16:e0250431. [PMID: 33956845 PMCID: PMC8101762 DOI: 10.1371/journal.pone.0250431] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Accepted: 04/01/2021] [Indexed: 02/07/2023] Open
Abstract
OBJECTIVE Pilot testing of real time functional magnetic resonance imaging (rt-fMRI) and real time functional near infrared spectroscopy (rt-fNIRS) as brain computer interface (BCI) neural feedback systems combined with motor learning for motor recovery in chronic severely impaired stroke survivors. APPROACH We enrolled a four-case series and administered three sequential rt-fMRI and ten rt-fNIRS neural feedback sessions interleaved with motor learning sessions. Measures were: Arm Motor Assessment Tool, functional domain (AMAT-F; 13 complex functional tasks), Fugl-Meyer arm coordination scale (FM); active wrist extension range of motion (ROM); volume of activation (fMRI); and fNIRS HbO concentration. Performance during neural feedback was assessed, in part, using percent successful brain modulations during rt-fNIRS. MAIN RESULTS Pre-/post-treatment mean clinically significant improvement in AMAT-F (.49 ± 0.22) and FM (10.0 ± 3.3); active wrist ROM improvement ranged from 20° to 50°. Baseline to follow-up change in brain signal was as follows: fMRI volume of activation was reduced in almost all ROIs for three subjects, and for one subject there was an increase or no change; fNIRS HbO was within normal range, except for one subject who increased beyond normal at post-treatment. During rt-fNIRS neural feedback training, there was successful brain signal modulation (42%-78%). SIGNIFICANCE Severely impaired stroke survivors successfully engaged in spatially focused BCI systems, rt-fMRI and rt-fNIRS, to clinically significantly improve motor function. At the least, equivalency in motor recovery was demonstrated with prior long-duration motor learning studies (without neural feedback), indicating that no loss of motor improvement resulted from substituting neural feedback sessions for motor learning sessions. Given that the current neural feedback protocol did not prevent the motor improvements observed in other long duration studies, even in the presence of fewer sessions of motor learning in the current work, the results support further study of neural feedback and its potential for recovery of motor function in stroke survivors. In future work, expanding the sophistication of either or both rt-fMRI and rt-fNIRS could hold the potential for further reducing the number of hours of training needed and/or the degree of recovery. ClinicalTrials.gov ID: NCT02856035.
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Affiliation(s)
- Avi K. Matarasso
- Brain Rehabilitation Research Center, Malcom Randall VA Medical Center, Gainesville, Florida, United States of America
- Department of Chemical Engineering, College of Engineering, University of Florida, Gainesville, Florida, United States of America
| | - Jake D. Rieke
- Brain Rehabilitation Research Center, Malcom Randall VA Medical Center, Gainesville, Florida, United States of America
| | - Keith White
- Brain Rehabilitation Research Center, Malcom Randall VA Medical Center, Gainesville, Florida, United States of America
| | - M. Minhal Yusufali
- Brain Rehabilitation Research Center, Malcom Randall VA Medical Center, Gainesville, Florida, United States of America
- J. Pruitt Family Department of Biomedical Engineering, College of Engineering, University of Florida, Gainesville, Florida, United States of America
| | - Janis J. Daly
- Brain Rehabilitation Research Center, Malcom Randall VA Medical Center, Gainesville, Florida, United States of America
- Department of Neurology, College of Medicine, University of Florida, Gainesville, Florida, United States of America
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20
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Abstract
Recent advances in brain-computer interface technology to restore and rehabilitate neurologic function aim to enable persons with disabling neurologic conditions to communicate, interact with the environment, and achieve other key activities of daily living and personal goals. Here we evaluate the principles, benefits, challenges, and future directions of brain-computer interfaces in the context of neurorehabilitation. We then explore the clinical translation of these technologies and propose an approach to facilitate implementation of brain-computer interfaces for persons with neurologic disease.
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Affiliation(s)
- Michael J Young
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - David J Lin
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
- School of Engineering and Carney Institute for Brain Science, Brown University, Providence, Rhode Island
- Department of Veterans Affairs Medical Center, VA RR&D Center for Neurorestoration and Neurotechnology, Providence, Rhode Island
| | - Leigh R Hochberg
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
- School of Engineering and Carney Institute for Brain Science, Brown University, Providence, Rhode Island
- Department of Veterans Affairs Medical Center, VA RR&D Center for Neurorestoration and Neurotechnology, Providence, Rhode Island
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21
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O'Brien JT, Nelson C. Assessing the Risks Posed by the Convergence of Artificial Intelligence and Biotechnology. Health Secur 2020; 18:219-227. [PMID: 32559154 PMCID: PMC7310294 DOI: 10.1089/hs.2019.0122] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2019] [Revised: 03/04/2020] [Accepted: 04/29/2020] [Indexed: 12/22/2022] Open
Abstract
Rapid developments are currently taking place in the fields of artificial intelligence (AI) and biotechnology, and applications arising from the convergence of these 2 fields are likely to offer immense opportunities that could greatly benefit human health and biosecurity. The combination of AI and biotechnology could potentially lead to breakthroughs in precision medicine, improved biosurveillance, and discovery of novel medical countermeasures as well as facilitate a more effective public health emergency response. However, as is the case with many preceding transformative technologies, new opportunities often present new risks in parallel. Understanding the current and emerging risks at the intersection of AI and biotechnology is crucial for health security specialists and unlikely to be achieved by examining either field in isolation. Uncertainties multiply as technologies merge, showcasing the need to identify robust assessment frameworks that could adequately analyze the risk landscape emerging at the convergence of these 2 domains.This paper explores the criteria needed to assess risks associated with Artificial intelligence and biotechnology and evaluates 3 previously published risk assessment frameworks. After highlighting their strengths and limitations and applying to relevant Artificial intelligence and biotechnology examples, the authors suggest a hybrid framework with recommendations for future approaches to risk assessment for convergent technologies.
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Affiliation(s)
- John T. O'Brien
- John T. O'Brien, MS, is a Research Associate, Bipartisan Commission on Biodefense, Washington, DC
| | - Cassidy Nelson
- Cassidy Nelson, MBBS, MPH, is a Research Scholar, Future of Humanity Institute, University of Oxford, Oxford, UK
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22
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Kögel J, Jox RJ, Friedrich O. What is it like to use a BCI? - insights from an interview study with brain-computer interface users. BMC Med Ethics 2020; 21:2. [PMID: 31906947 PMCID: PMC6945485 DOI: 10.1186/s12910-019-0442-2] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2019] [Accepted: 12/23/2019] [Indexed: 11/25/2022] Open
Abstract
Background The neurotechnology behind brain-computer interfaces (BCIs) raises various ethical questions. The ethical literature has pinpointed several issues concerning safety, autonomy, responsibility and accountability, psychosocial identity, consent, privacy and data security. This study aims to assess BCI users’ experiences, self-observations and attitudes in their own right and looks for social and ethical implications. Methods We conducted nine semi-structured interviews with BCI users, who used the technology for medical reasons. The transcribed interviews were analyzed according to the Grounded Theory coding method. Results BCI users perceive themselves as active operators of a technology that offers them social participation and impacts their self-definition. Each of these aspects bears its own opportunities and risks. BCIs can contribute to retaining or regaining human capabilities. At the same time, BCI use contains elements that challenge common experiences, for example when the technology is in conflict with the affective side of BCI users. The potential benefits of BCIs are regarded as outweighing the risks in that BCI use is considered to promote valuable qualities and capabilities. BCI users appreciate the opportunity to regain lost capabilities as well as to gain new ones. Conclusions BCI users appreciate the technology for various reasons. The technology is highly appreciated in cases where it is beneficial in terms of agency, participation and self-definitions. Rather than questioning human nature, the technology can retain and restore characteristics and abilities which enrich our lives.
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Affiliation(s)
- Johannes Kögel
- Institute of Ethics, History and Theory of Medicine, LMU Munich, Lessingstr. 2, 80336, Munich, Germany.
| | - Ralf J Jox
- Clinical Ethics Unit and Institute of Humanities in Medicine, Lausanne University Hospital and Faculty of Biology and Medicine, University of Lausanne, Avenue de Provence 82, CH-1007, Lausanne, Switzerland
| | - Orsolya Friedrich
- Institute of Philosophy, Faculty of Cultural and Social Sciences, FernUniversität in Hagen, Universitätsstr. 33, 58097, Hagen, Germany
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23
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Al-Taleb MKH, Purcell M, Fraser M, Petric-Gray N, Vuckovic A. Home used, patient self-managed, brain-computer interface for the management of central neuropathic pain post spinal cord injury: usability study. J Neuroeng Rehabil 2019; 16:128. [PMID: 31666096 PMCID: PMC6822418 DOI: 10.1186/s12984-019-0588-7] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2018] [Accepted: 09/06/2019] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND Central Neuropathic Pain (CNP) is a frequent chronic condition in people with spinal cord injury (SCI). Previously, we showed that using laboratory brain-computer interface (BCI) technology for neurofeedback (NFB) training, it was possible to reduce CNP in people with SCI. In this study, we show results of patient self-managed treatment in their homes with a BCI-NFB using a consumer EEG device. METHODS Users: People with chronic SCI (17 M, 3 F, 50.6 ± 14.1 years old), and CNP ≥4 on a Visual Numerical Scale. LOCATION Laboratory training (up to 4 sessions) followed by home self-managed NFB. User Activity: Upregulating the EEG alpha band power by 10% above a threshold and at the same time downregulating the theta and upper beta (20-30 Hz) band power by 10% at electrode location C4. Technology: A consumer grade multichannel EEG headset (Epoch, Emotiv, USA), a tablet computer and custom made NFB software. EVALUATION EEG analysis, before and after NFB assessment, interviews and questionnaires. RESULTS Effectiveness: Out of 20 initially assessed participants, 15 took part in the study. Participants used the system for 6.9 ± 5.5 (median 4) weeks. Twelve participants regulated their brainwaves in a frequency specific manner and were most successful upregulating the alpha band power. However they typically upregulated power around their individual alpha peak (7.6 ± 0.8 Hz) that was lower than in people without CNP. The reduction in pain experienced was statistically significant in 12 and clinically significant (greater than 30%) in 8 participants. Efficiency: The donning was between 5 and 15 min, and approximately 10-20% of EEG data recorded in the home environment was noise. Participants were mildly stressed when self-administering NFB at home (2.4 on a scale 1-10). User satisfaction: Nine participants who completed the final assessment reported a high level of satisfaction (QUESQ, 4.5 ± 0.8), naming effectiveness, ease of use and comfort as main priorities. The main factors influencing frequency of NFB training were: health related issues, free time and pain intensity. CONCLUSION Portable NFB is a feasible solution for home-based self-managed treatment of CNP. Compared to pharmacological treatments, NFB has less side effects and provides users with active control over pain. TRIAL REGISTRATION GN15NE124 , Registered 9th June 2016.
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Affiliation(s)
- M K H Al-Taleb
- Biomedical Engineering Research Division, University of Glasgow, Glasgow, UK.,Wasit University, Wasit, Iraq
| | - M Purcell
- Queen Elizabeth National Spinal Injuries Unit, Queen Elizabeth University Hospital, Glasgow, UK
| | - M Fraser
- Queen Elizabeth National Spinal Injuries Unit, Queen Elizabeth University Hospital, Glasgow, UK
| | - N Petric-Gray
- Biomedical Engineering Research Division, University of Glasgow, Glasgow, UK
| | - A Vuckovic
- Biomedical Engineering Research Division, University of Glasgow, Glasgow, UK.
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