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Bjelica B, Bartels MB, Hesebeck-Brinckmann J, Petri S. Non-motor symptoms in patients with amyotrophic lateral sclerosis: current state and future directions. J Neurol 2024; 271:3953-3977. [PMID: 38805053 PMCID: PMC11233299 DOI: 10.1007/s00415-024-12455-5] [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: 04/17/2024] [Revised: 05/14/2024] [Accepted: 05/16/2024] [Indexed: 05/29/2024]
Abstract
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by the progressive degeneration of both upper and lower motor neurons. A defining histopathological feature in approximately 97% of all ALS cases is the accumulation of phosphorylated trans-activation response (TAR) DNA-binding protein 43 protein (pTDP-43) aggregates in the cytoplasm of neurons and glial cells within the central nervous system. Traditionally, it was believed that the accumulation of TDP-43 aggregates and subsequent neurodegeneration primarily occurs in motor neurons. However, contemporary evidence suggests that as the disease progresses, other systems and brain regions are also affected. Despite this, there has been a limited number of clinical studies assessing the non-motor symptoms in ALS patients. These studies often employ various outcome measures, resulting in a wide range of reported frequencies of non-motor symptoms in ALS patients. The importance of assessing the non-motor symptoms reflects in a fact that they have a significant impact on patients' quality of life, yet they frequently go underdiagnosed and unreported during clinical evaluations. This review aims to provide an up-to-date overview of the current knowledge concerning non-motor symptoms in ALS. Furthermore, we address their diagnosis and treatment in everyday clinical practice.
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Affiliation(s)
- Bogdan Bjelica
- Department of Neurology, Hannover Medical School, 1, Carl-Neuberg-Strasse, 30625, Hannover, Germany.
| | - Maj-Britt Bartels
- Precision Neurology of Neuromuscular and Motoneuron Diseases, University of Luebeck, Lübeck, Germany
| | - Jasper Hesebeck-Brinckmann
- Neurology Department, Division for Neurodegenerative Diseases, University Medicine Mannheim, Heidelberg University, Mannheim Center for Translational Medicine, Mannheim, Germany
| | - Susanne Petri
- Department of Neurology, Hannover Medical School, 1, Carl-Neuberg-Strasse, 30625, Hannover, Germany
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Grevet E, Forge K, Tadiello S, Izac M, Amadieu F, Brunel L, Pillette L, Py J, Gasq D, Jeunet-Kelway C. Modeling the acceptability of BCIs for motor rehabilitation after stroke: A large scale study on the general public. FRONTIERS IN NEUROERGONOMICS 2023; 3:1082901. [PMID: 38235470 PMCID: PMC10790937 DOI: 10.3389/fnrgo.2022.1082901] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 12/09/2022] [Indexed: 01/19/2024]
Abstract
Introduction Strokes leave around 40% of survivors dependent in their activities of daily living, notably due to severe motor disabilities. Brain-computer interfaces (BCIs) have been shown to be efficiency for improving motor recovery after stroke, but this efficiency is still far from the level required to achieve the clinical breakthrough expected by both clinicians and patients. While technical levers of improvement have been identified (e.g., sensors and signal processing), fully optimized BCIs are pointless if patients and clinicians cannot or do not want to use them. We hypothesize that improving BCI acceptability will reduce patients' anxiety levels, while increasing their motivation and engagement in the procedure, thereby favoring learning, ultimately, and motor recovery. In other terms, acceptability could be used as a lever to improve BCI efficiency. Yet, studies on BCI based on acceptability/acceptance literature are missing. Thus, our goal was to model BCI acceptability in the context of motor rehabilitation after stroke, and to identify its determinants. Methods The main outcomes of this paper are the following: i) we designed the first model of acceptability of BCIs for motor rehabilitation after stroke, ii) we created a questionnaire to assess acceptability based on that model and distributed it on a sample representative of the general public in France (N = 753, this high response rate strengthens the reliability of our results), iii) we validated the structure of this model and iv) quantified the impact of the different factors on this population. Results Results show that BCIs are associated with high levels of acceptability in the context of motor rehabilitation after stroke and that the intention to use them in that context is mainly driven by the perceived usefulness of the system. In addition, providing people with clear information regarding BCI functioning and scientific relevance had a positive influence on acceptability factors and behavioral intention. Discussion With this paper we propose a basis (model) and a methodology that could be adapted in the future in order to study and compare the results obtained with: i) different stakeholders, i.e., patients and caregivers; ii) different populations of different cultures around the world; and iii) different targets, i.e., other clinical and non-clinical BCI applications.
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Affiliation(s)
- Elise Grevet
- CNRS, EPHE, INCIA, UMR5287, Université de Bordeaux, Bordeaux, France
| | - Killyam Forge
- CLLE, Université de Toulouse, CNRS, Toulouse, France
| | | | - Margaux Izac
- CNRS, EPHE, INCIA, UMR5287, Université de Bordeaux, Bordeaux, France
| | | | - Lionel Brunel
- Université Paul Valéry Montpellier 3, EPSYLON EA 4556, Montpellier, France
| | - Léa Pillette
- CNRS, EPHE, INCIA, UMR5287, Université de Bordeaux, Bordeaux, France
| | - Jacques Py
- CLLE, Université de Toulouse, CNRS, Toulouse, France
| | - David Gasq
- ToNIC, Université de Toulouse, INSERM, Toulouse, France
- Centre Hospitalier Universitaire Toulouse, Toulouse, France
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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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4
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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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Huggins JE, Krusienski D, Vansteensel MJ, Valeriani D, Thelen A, Stavisky S, Norton JJS, Nijholt A, Müller-Putz G, Kosmyna N, Korczowski L, Kapeller C, Herff C, Halder S, Guger C, Grosse-Wentrup M, Gaunt R, Dusang AN, Clisson P, Chavarriaga R, Anderson CW, Allison BZ, Aksenova T, Aarnoutse E. Workshops of the Eighth International Brain-Computer Interface Meeting: BCIs: The Next Frontier. BRAIN-COMPUTER INTERFACES 2022; 9:69-101. [PMID: 36908334 PMCID: PMC9997957 DOI: 10.1080/2326263x.2021.2009654] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2021] [Accepted: 11/15/2021] [Indexed: 12/11/2022]
Abstract
The Eighth International Brain-Computer Interface (BCI) Meeting was held June 7-9th, 2021 in a virtual format. The conference continued the BCI Meeting series' interactive nature with 21 workshops covering topics in BCI (also called brain-machine interface) research. As in the past, workshops covered the breadth of topics in BCI. Some workshops provided detailed examinations of specific methods, hardware, or processes. Others focused on specific BCI applications or user groups. Several workshops continued consensus building efforts designed to create BCI standards and increase the ease of comparisons between studies and the potential for meta-analysis and large multi-site clinical trials. Ethical and translational considerations were both the primary topic for some workshops or an important secondary consideration for others. The range of BCI applications continues to expand, with more workshops focusing on approaches that can extend beyond the needs of those with physical impairments. This paper summarizes each workshop, provides background information and references for further study, presents an overview of the discussion topics, and describes the conclusion, challenges, or initiatives that resulted from the interactions and discussion at the workshop.
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Affiliation(s)
- Jane E Huggins
- Department of Physical Medicine and Rehabilitation, Department of Biomedical Engineering, Neuroscience Graduate Program, University of Michigan, Ann Arbor, Michigan, United States 325 East Eisenhower, Room 3017; Ann Arbor, Michigan 48108-5744, 734-936-7177
| | - Dean Krusienski
- Department of Biomedical Engineering, Virginia Commonwealth University, Richmond, VA 23219
| | - Mariska J Vansteensel
- UMC Utrecht Brain Center, Dept of Neurosurgery, University Medical Center Utrecht, The Netherlands
| | | | - Antonia Thelen
- eemagine Medical Imaging Solutions GmbH, Berlin, Germany
| | | | - James J S Norton
- National Center for Adaptive Neurotechnologies, US Department of Veterans Affairs, 113 Holland Ave, Albany, NY 12208
| | - Anton Nijholt
- Faculty EEMCS, University of Twente, Enschede, The Netherlands
| | - Gernot Müller-Putz
- Institute of Neural Engineering, GrazBCI Lab, Graz University of Technology, Stremayrgasse 16/4, 8010 Graz, Austria
| | - Nataliya Kosmyna
- Massachusetts Institute of Technology (MIT), Media Lab, E14-548, Cambridge, MA 02139, Unites States
| | | | | | - Christian Herff
- School of Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | | | - Christoph Guger
- g.tec medical engineering GmbH/Guger Technologies OG, Austria, Sierningstrasse 14, 4521 Schiedlberg, Austria, +43725122240-0
| | - Moritz Grosse-Wentrup
- Research Group Neuroinformatics, Faculty of Computer Science, Vienna Cognitive Science Hub, Data Science @ Uni Vienna University of Vienna
| | - Robert Gaunt
- Rehab Neural Engineering Labs, Department of Physical Medicine and Rehabilitation, Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA, USA, 3520 5th Ave, Suite 300, Pittsburgh, PA 15213, 412-383-1426
| | - Aliceson Nicole Dusang
- Department of Electrical and Computer Engineering, School of Engineering, Brown University, Carney Institute for Brain Science, Brown University, Providence, RI
- Department of Veterans Affairs Medical Center, Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, Providence, RI
- Center for Neurotechnology and Neurorecovery, Neurology, Massachusetts General Hospital, Boston, MA
| | | | - Ricardo Chavarriaga
- IEEE Standards Association Industry Connections group on neurotechnologies for brain-machine interface, Center for Artificial Intelligence, School of Engineering, ZHAW-Zurich University of Applied Sciences, Switzerland, Switzerland
| | - Charles W Anderson
- Department of Computer Science, Molecular, Cellular and Integrative Neurosience Program, Colorado State University, Fort Collins, CO 80523
| | - Brendan Z Allison
- Dept. of Cognitive Science, Mail Code 0515, University of California at San Diego, La Jolla, United States, 619-534-9754
| | - Tetiana Aksenova
- University Grenoble Alpes, CEA, LETI, Clinatec, Grenoble 38000, France
| | - Erik Aarnoutse
- UMC Utrecht Brain Center, Department of Neurology & Neurosurgery, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
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Pitt KM, Dietz A. Applying Implementation Science to Support Active Collaboration in Noninvasive Brain-Computer Interface Development and Translation for Augmentative and Alternative Communication. AMERICAN JOURNAL OF SPEECH-LANGUAGE PATHOLOGY 2022; 31:515-526. [PMID: 34958737 DOI: 10.1044/2021_ajslp-21-00152] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
PURPOSE The purpose of this article is to consider how, alongside engineering advancements, noninvasive brain-computer interface (BCI) for augmentative and alternative communication (AAC; BCI-AAC) developments can leverage implementation science to increase the clinical impact of this technology. We offer the Consolidated Framework for Implementation Research (CFIR) as a structure to help guide future BCI-AAC research. Specifically, we discuss CFIR primary domains that include intervention characteristics, the outer and inner settings, the individuals involved in the intervention, and the process of implementation, alongside pertinent subdomains including adaptability, cost, patient needs and recourses, implementation climate, other personal attributes, and the process of engaging. The authors support their view with current citations from both the AAC and BCI-AAC fields. CONCLUSIONS The article aimed to provide thoughtful considerations for how future research may leverage the CFIR to support meaningful BCI-AAC translation for those with severe physical impairments. We believe that, although significant barriers to BCI-AAC development still exist, incorporating implementation research may be timely for the field of BCI-AAC and help account for diversity in end users, navigate implementation obstacles, and support a smooth and efficient translation of BCI-AAC technology. Moreover, the sooner clinicians, individuals who use AAC, their support networks, and engineers collectively improve BCI-AAC outcomes and the efficiency of translation, the sooner BCI-AAC may become an everyday tool in the AAC arsenal.
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Affiliation(s)
- Kevin M Pitt
- Department of Special Education and Communication Disorders, University of Nebraska-Lincoln
| | - Aimee Dietz
- Department of Communication Sciences and Disorders, Georgia State University, Atlanta
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Yuan H, Li Y, Yang J, Li H, Yang Q, Guo C, Zhu S, Shu X. State of the Art of Non-Invasive Electrode Materials for Brain-Computer Interface. MICROMACHINES 2021; 12:1521. [PMID: 34945371 PMCID: PMC8705666 DOI: 10.3390/mi12121521] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 12/01/2021] [Accepted: 12/02/2021] [Indexed: 02/02/2023]
Abstract
The brain-computer interface (BCI) has emerged in recent years and has attracted great attention. As an indispensable part of the BCI signal acquisition system, brain electrodes have a great influence on the quality of the signal, which determines the final effect. Due to the special usage scenario of brain electrodes, some specific properties are required for them. In this study, we review the development of three major types of EEG electrodes from the perspective of material selection and structural design, including dry electrodes, wet electrodes, and semi-dry electrodes. Additionally, we provide a reference for the current chaotic performance evaluation of EEG electrodes in some aspects such as electrochemical performance, stability, and so on. Moreover, the challenges and future expectations for EEG electrodes are analyzed.
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Affiliation(s)
- Haowen Yuan
- State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai 200240, China; (H.Y.); (J.Y.); (H.L.); (Q.Y.); (C.G.); (S.Z.)
| | - Yao Li
- State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai 200240, China; (H.Y.); (J.Y.); (H.L.); (Q.Y.); (C.G.); (S.Z.)
| | - Junjun Yang
- State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai 200240, China; (H.Y.); (J.Y.); (H.L.); (Q.Y.); (C.G.); (S.Z.)
| | - Hongjie Li
- State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai 200240, China; (H.Y.); (J.Y.); (H.L.); (Q.Y.); (C.G.); (S.Z.)
| | - Qinya Yang
- State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai 200240, China; (H.Y.); (J.Y.); (H.L.); (Q.Y.); (C.G.); (S.Z.)
| | - Cuiping Guo
- State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai 200240, China; (H.Y.); (J.Y.); (H.L.); (Q.Y.); (C.G.); (S.Z.)
| | - Shenmin Zhu
- State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai 200240, China; (H.Y.); (J.Y.); (H.L.); (Q.Y.); (C.G.); (S.Z.)
| | - Xiaokang Shu
- School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
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8
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Zulauf-Czaja A, Al-Taleb MKH, Purcell M, Petric-Gray N, Cloughley J, Vuckovic A. On the way home: a BCI-FES hand therapy self-managed by sub-acute SCI participants and their caregivers: a usability study. J Neuroeng Rehabil 2021; 18:44. [PMID: 33632262 PMCID: PMC7905902 DOI: 10.1186/s12984-021-00838-y] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Accepted: 02/10/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Regaining hand function is the top priority for people with tetraplegia, however access to specialised therapy outwith clinics is limited. Here we present a system for hand therapy based on brain-computer interface (BCI) which uses a consumer grade electroencephalography (EEG) device combined with functional electrical stimulation (FES), and evaluate its usability among occupational therapists (OTs) and people with spinal cord injury (SCI) and their family members. METHODS Users: Eight people with sub-acute SCI (6 M, 2F, age 55.4 ± 15.6) and their caregivers (3 M, 5F, age 45.3 ± 14.3); four OTs (4F, age 42.3 ± 9.8). User Activity: Researchers trained OTs; OTs subsequently taught caregivers to set up the system for the people with SCI to perform hand therapy. Hand therapy consisted of attempted movement (AM) of one hand to lower the power of EEG sensory-motor rhythm in the 8-12 Hz band and thereby activate FES which induced wrist flexion and extension. Technology: Consumer grade wearable EEG, multichannel FES, custom made BCI application. LOCATION Research space within hospital. Evaluation: donning times, BCI accuracy, BCI and FES parameter repeatability, questionnaires, focus groups and interviews. RESULTS Effectiveness: The BCI accuracy was 70-90%. Efficiency: Median donning times decreased from 40.5 min for initial session to 27 min during last training session (N = 7), dropping to 14 min on the last self-managed session (N = 3). BCI and FES parameters were stable from session to session. Satisfaction: Mean satisfaction with the system among SCI users and caregivers was 3.68 ± 0.81 (max 5) as measured by QUEST questionnaire. Main facilitators for implementing BCI-FES technology were "seeing hand moving", "doing something useful for the loved ones", good level of computer literacy (people with SCI and caregivers), "active engagement in therapy" (OT), while main barriers were technical complexity of setup (all groups) and "lack of clinical evidence" (OT). CONCLUSION BCI-FES has potential to be used as at home hand therapy by people with SCI or stroke, provided it is easy to use and support is provided. Transfer of knowledge of operating BCI is possible from researchers to therapists to users and caregivers. Trial registration Registered with NHS GG&C on December 6th 2017; clinicaltrials.gov reference number NCT03257982, url: https://clinicaltrials.gov/ct2/show/NCT03257982 .
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Affiliation(s)
- Anna Zulauf-Czaja
- Biomedical Engineering Research Division, University of Glasgow, Glasgow, UK.
| | - Manaf K H Al-Taleb
- Biomedical Engineering Research Division, University of Glasgow, Glasgow, UK.,Wasit University, Wasit, Iraq
| | - Mariel Purcell
- Queen Elizabeth National Spinal Injuries Unit, Elizabeth University Hospital, Glasgow, Queen, UK
| | - Nina Petric-Gray
- Biomedical Engineering Research Division, University of Glasgow, Glasgow, UK
| | - Jennifer Cloughley
- Queen Elizabeth National Spinal Injuries Unit, Elizabeth University Hospital, Glasgow, Queen, UK
| | - Aleksandra Vuckovic
- Biomedical Engineering Research Division, University of Glasgow, Glasgow, UK
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Abstract
Locked-in syndrome (LIS) is characterized by an inability to move or speak in the presence of intact cognition and can be caused by brainstem trauma or neuromuscular disease. Quality of life (QoL) in LIS is strongly impaired by the inability to communicate, which cannot always be remedied by traditional augmentative and alternative communication (AAC) solutions if residual muscle activity is insufficient to control the AAC device. Brain-computer interfaces (BCIs) may offer a solution by employing the person's neural signals instead of relying on muscle activity. Here, we review the latest communication BCI research using noninvasive signal acquisition approaches (electroencephalography, functional magnetic resonance imaging, functional near-infrared spectroscopy) and subdural and intracortical implanted electrodes, and we discuss current efforts to translate research knowledge into usable BCI-enabled communication solutions that aim to improve the QoL of individuals with LIS.
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Kögel J, Schmid JR, Jox RJ, Friedrich O. Using brain-computer interfaces: a scoping review of studies employing social research methods. BMC Med Ethics 2019; 20:18. [PMID: 30845952 PMCID: PMC6407281 DOI: 10.1186/s12910-019-0354-1] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2018] [Accepted: 02/22/2019] [Indexed: 12/11/2022] Open
Abstract
Background The rapid expansion of research on Brain-Computer Interfaces (BCIs) is not only due to the promising solutions offered for persons with physical impairments. There is also a heightened need for understanding BCIs due to the challenges regarding ethics presented by new technology, especially in its impact on the relationship between man and machine. Here we endeavor to present a scoping review of current studies in the field to gain insight into the complexity of BCI use. By examining studies related to BCIs that employ social research methods, we seek to demonstrate the multitude of approaches and concerns from various angles in considering the social and human impact of BCI technology. Methods For this scoping review of research on BCIs’ social and ethical implications, we systematically analyzed six databases, encompassing the fields of medicine, psychology, and the social sciences, in order to identify empirical studies on BCIs. The search yielded 73 publications that employ quantitative, qualitative, or mixed methods. Results Of the 73 publications, 71 studies address the user perspective. Some studies extend to consideration of other BCI stakeholders such as medical technology experts, caregivers, or health care professionals. The majority of the studies employ quantitative methods. Recurring themes across the studies examined were general user opinion towards BCI, central technical or social issues reported, requests/demands made by users of the technology, the potential/future of BCIs, and ethical aspects of BCIs. Conclusions Our findings indicate that while technical aspects of BCIs such as usability or feasibility are being studied extensively, comparatively little in-depth research has been done on the self-image and self-experience of the BCI user. In general there is also a lack of focus or examination of the caregiver’s perspective. Electronic supplementary material The online version of this article (10.1186/s12910-019-0354-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Johannes Kögel
- Institute of Ethics, History and Theory of Medicine, LMU Munich, Lessingstr. 2, D-80336, Munich, Germany.
| | - Jennifer R Schmid
- Institute of Ethics, History and Theory of Medicine, LMU Munich, Lessingstr. 2, D-80336, Munich, Germany
| | - Ralf J Jox
- Institute of Ethics, History and Theory of Medicine, LMU Munich, Lessingstr. 2, D-80336, Munich, Germany
| | - Orsolya Friedrich
- Institute of Ethics, History and Theory of Medicine, LMU Munich, Lessingstr. 2, D-80336, Munich, Germany
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11
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Pitt K, Brumberg J. A screening protocol incorporating brain-computer interface feature matching considerations for augmentative and alternative communication. Assist Technol 2018; 32:161-172. [DOI: 10.1080/10400435.2018.1512175] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Affiliation(s)
- Kevin Pitt
- Department of Speech-Language-Hearing: Sciences & Disorders, University of Kansas, Lawrence, Kansas, USA
| | - Jonathan Brumberg
- Department of Speech-Language-Hearing: Sciences & Disorders, University of Kansas, Lawrence, Kansas, USA
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12
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Hammer EM, Halder S, Kleih SC, Kübler A. Psychological Predictors of Visual and Auditory P300 Brain-Computer Interface Performance. Front Neurosci 2018; 12:307. [PMID: 29867319 PMCID: PMC5960704 DOI: 10.3389/fnins.2018.00307] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2017] [Accepted: 04/20/2018] [Indexed: 12/13/2022] Open
Abstract
Brain-Computer Interfaces (BCIs) provide communication channels independent from muscular control. In the current study we used two versions of the P300-BCI: one based on visual the other on auditory stimulation. Up to now, data on the impact of psychological variables on P300-BCI control are scarce. Hence, our goal was to identify new predictors with a comprehensive psychological test-battery. A total of N = 40 healthy BCI novices took part in a visual and an auditory BCI session. Psychological variables were measured with an electronic test-battery including clinical, personality, and performance tests. The personality factor "emotional stability" was negatively correlated (Spearman's rho = -0.416; p < 0.01) and an output variable of the non-verbal learning test (NVLT), which can be interpreted as ability to learn, correlated positively (Spearman's rho = 0.412; p < 0.01) with visual P300-BCI performance. In a linear regression analysis both independent variables explained 24% of the variance. "Emotional stability" was also negatively related to auditory P300-BCI performance (Spearman's rho = -0.377; p < 0.05), but failed significance in the regression analysis. Psychological parameters seem to play a moderate role in visual P300-BCI performance. "Emotional stability" was identified as a new predictor, indicating that BCI users who characterize themselves as calm and rational showed worse BCI performance. The positive relation of the ability to learn and BCI performance corroborates the notion that also for P300 based BCIs learning may constitute an important factor. Further studies are needed to consolidate or reject the presented predictors.
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Affiliation(s)
| | | | | | - Andrea Kübler
- Institute of Psychology, University of Würzburg, Würzburg, Germany
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Kellmeyer P, Grosse-Wentrup M, Schulze-Bonhage A, Ziemann U, Ball T. Electrophysiological correlates of neurodegeneration in motor and non-motor brain regions in amyotrophic lateral sclerosis-implications for brain-computer interfacing. J Neural Eng 2018; 15:041003. [PMID: 29676287 DOI: 10.1088/1741-2552/aabfa5] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
OBJECTIVE For patients with amyotrophic lateral sclerosis (ALS) who are suffering from severe communication or motor problems, brain-computer interfaces (BCIs) can improve the quality of life and patient autonomy. However, current BCI systems are not as widely used as their potential and patient demand would let assume. This underutilization is a result of technological as well as user-based limitations but also of the comparatively poor performance of currently existing BCIs in patients with late-stage ALS, particularly in the locked-in state. APPROACH Here we review a broad range of electrophysiological studies in ALS patients with the aim to identify electrophysiological correlates of ALS-related neurodegeneration in motor and non-motor brain regions in to better understand potential neurophysiological limitations of current BCI systems for ALS patients. To this end we analyze studies in ALS patients that investigated basic sensory evoked potentials, resting-state and task-based paradigms using electroencephalography or electrocorticography for basic research purposes as well as for brain-computer interfacing. Main results and significance. Our review underscores that, similarly to mounting evidence from neuroimaging and neuropathology, electrophysiological measures too indicate neurodegeneration in non-motor areas in ALS. Furthermore, we identify an unexpected gap of basic and advanced electrophysiological studies in late-stage ALS patients, particularly in the locked-in state. We propose a research strategy on how to fill this gap in order to improve the design and performance of future BCI systems for this patient group.
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Affiliation(s)
- Philipp Kellmeyer
- Translational Neurotechnology Lab, Department of Neurosurgery, Medical Center-University of Freiburg, Freiburg im Breisgau, Germany. Cluster of Excellence BrainLinks-BrainTools, University of Freiburg, Freiburg im Breisgau, Germany
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Brumberg JS, Nguyen A, Pitt KM, Lorenz SD. Examining sensory ability, feature matching and assessment-based adaptation for a brain-computer interface using the steady-state visually evoked potential. Disabil Rehabil Assist Technol 2018; 14:241-249. [PMID: 29385839 DOI: 10.1080/17483107.2018.1428369] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
PURPOSE We investigated how overt visual attention and oculomotor control influence successful use of a visual feedback brain-computer interface (BCI) for accessing augmentative and alternative communication (AAC) devices in a heterogeneous population of individuals with profound neuromotor impairments. BCIs are often tested within a single patient population limiting generalization of results. This study focuses on examining individual sensory abilities with an eye toward possible interface adaptations to improve device performance. METHODS Five individuals with a range of neuromotor disorders participated in four-choice BCI control task involving the steady state visually evoked potential. The BCI graphical interface was designed to simulate a commercial AAC device to examine whether an integrated device could be used successfully by individuals with neuromotor impairment. RESULTS All participants were able to interact with the BCI and highest performance was found for participants able to employ an overt visual attention strategy. For participants with visual deficits to due to impaired oculomotor control, effective performance increased after accounting for mismatches between the graphical layout and participant visual capabilities. CONCLUSION As BCIs are translated from research environments to clinical applications, the assessment of BCI-related skills will help facilitate proper device selection and provide individuals who use BCI the greatest likelihood of immediate and long term communicative success. Overall, our results indicate that adaptations can be an effective strategy to reduce barriers and increase access to BCI technology. These efforts should be directed by comprehensive assessments for matching individuals to the most appropriate device to support their complex communication needs. Implications for Rehabilitation Brain computer interfaces using the steady state visually evoked potential can be integrated with an augmentative and alternative communication device to provide access to language and literacy for individuals with neuromotor impairment. Comprehensive assessments are needed to fully understand the sensory, motor, and cognitive abilities of individuals who may use brain-computer interfaces for proper feature matching as selection of the most appropriate device including optimization device layouts and control paradigms. Oculomotor impairments negatively impact brain-computer interfaces that use the steady state visually evoked potential, but modifications to place interface stimuli and communication items in the intact visual field can improve successful outcomes.
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Affiliation(s)
- Jonathan S Brumberg
- a Department of Speech-Language-Hearing: Sciences & Disorders , University of Kansas , Lawrence , KS , USA
| | - Anh Nguyen
- b Department of Speech Language & Hearing Sciences , College of Health & Rehabilitation Sciences: Sargent College, Boston University , Boston , MA , USA
| | - Kevin M Pitt
- a Department of Speech-Language-Hearing: Sciences & Disorders , University of Kansas , Lawrence , KS , USA
| | - Sean D Lorenz
- c Center for Computational Neuroscience and Neural Technology , Boston University , Boston , MA , USA
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15
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Brain computer interface with the P300 speller: Usability for disabled people with amyotrophic lateral sclerosis. Ann Phys Rehabil Med 2017; 61:5-11. [PMID: 29024794 DOI: 10.1016/j.rehab.2017.09.004] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2017] [Revised: 09/19/2017] [Accepted: 09/19/2017] [Indexed: 12/13/2022]
Abstract
OBJECTIVES Amyotrophic lateral sclerosis (ALS), a progressive neurodegenerative disease, restricts patients' communication capacity a few years after onset. A proof-of-concept of brain-computer interface (BCI) has shown promise in ALS and "locked-in" patients, mostly in pre-clinical studies or with only a few patients, but performance was estimated not high enough to support adoption by people with physical limitation of speech. Here, we evaluated a visual BCI device in a clinical study to determine whether disabled people with multiple deficiencies related to ALS would be able to use BCI to communicate in a daily environment. METHODS After clinical evaluation of physical, cognitive and language capacities, 20 patients with ALS were included. The P300 speller BCI system consisted of electroencephalography acquisition connected to real-time processing software and separate keyboard-display control software. It was equipped with original features such as optimal stopping of flashes and word prediction. The study consisted of two 3-block sessions (copy spelling, free spelling and free use) with the system in several modes of operation to evaluate its usability in terms of effectiveness, efficiency and satisfaction. RESULTS The system was effective in that all participants successfully achieved all spelling tasks and was efficient in that 65% of participants selected more than 95% of the correct symbols. The mean number of correct symbols selected per minute ranged from 3.6 (without word prediction) to 5.04 (with word prediction). Participants expressed satisfaction: the mean score was 8.7 on a 10-point visual analog scale assessing comfort, ease of use and utility. Patients quickly learned how to operate the system, which did not require much learning effort. CONCLUSION With its word prediction and optimal stopping of flashes, which improves information transfer rate, the BCI system may be competitive with alternative communication systems such as eye-trackers. Remaining requirements to improve the device for suitable ergonomic use are in progress.
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Riccio A, Pichiorri F, Schettini F, Toppi J, Risetti M, Formisano R, Molinari M, Astolfi L, Cincotti F, Mattia D. Interfacing brain with computer to improve communication and rehabilitation after brain damage. PROGRESS IN BRAIN RESEARCH 2016; 228:357-87. [PMID: 27590975 DOI: 10.1016/bs.pbr.2016.04.018] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Communication and control of the external environment can be provided via brain-computer interfaces (BCIs) to replace a lost function in persons with severe diseases and little or no chance of recovery of motor abilities (ie, amyotrophic lateral sclerosis, brainstem stroke). BCIs allow to intentionally modulate brain activity, to train specific brain functions, and to control prosthetic devices, and thus, this technology can also improve the outcome of rehabilitation programs in persons who have suffered from a central nervous system injury (ie, stroke leading to motor or cognitive impairment). Overall, the BCI researcher is challenged to interact with people with severe disabilities and professionals in the field of neurorehabilitation. This implies a deep understanding of the disabled condition on the one hand, and it requires extensive knowledge on the physiology and function of the human brain on the other. For these reasons, a multidisciplinary approach and the continuous involvement of BCI users in the design, development, and testing of new systems are desirable. In this chapter, we will focus on noninvasive EEG-based systems and their clinical applications, highlighting crucial issues to foster BCI translation outside laboratories to eventually become a technology usable in real-life realm.
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Affiliation(s)
- A Riccio
- Neuroelectrical Imaging and Brain-Computer Interface Laboratory, Fondazione Santa Lucia IRCCS, Rome, Italy
| | - F Pichiorri
- Neuroelectrical Imaging and Brain-Computer Interface Laboratory, Fondazione Santa Lucia IRCCS, Rome, Italy; Sapienza University of Rome, Rome, Italy
| | - F Schettini
- Neuroelectrical Imaging and Brain-Computer Interface Laboratory, Fondazione Santa Lucia IRCCS, Rome, Italy
| | - J Toppi
- Neuroelectrical Imaging and Brain-Computer Interface Laboratory, Fondazione Santa Lucia IRCCS, Rome, Italy; Sapienza University of Rome, Rome, Italy
| | - M Risetti
- Neuroelectrical Imaging and Brain-Computer Interface Laboratory, Fondazione Santa Lucia IRCCS, Rome, Italy
| | - R Formisano
- Post-Coma Unit, Fondazione Santa Lucia IRCCS, Rome, Italy
| | - M Molinari
- Spinal Cord Unit, IRCCS Santa Lucia Foundation, Rome, Italy
| | - L Astolfi
- Neuroelectrical Imaging and Brain-Computer Interface Laboratory, Fondazione Santa Lucia IRCCS, Rome, Italy; Sapienza University of Rome, Rome, Italy
| | - F Cincotti
- Neuroelectrical Imaging and Brain-Computer Interface Laboratory, Fondazione Santa Lucia IRCCS, Rome, Italy; Sapienza University of Rome, Rome, Italy
| | - D Mattia
- Neuroelectrical Imaging and Brain-Computer Interface Laboratory, Fondazione Santa Lucia IRCCS, Rome, Italy.
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Geronimo A, Simmons Z, Schiff SJ. Performance predictors of brain–computer interfaces in patients with amyotrophic lateral sclerosis. J Neural Eng 2016; 13:026002. [DOI: 10.1088/1741-2560/13/2/026002] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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