The DOI matches its Crossref record; 50 of the 50 references it cites were found in a registry or an index.
Brain-computer interfaces and communication in paralysis: extinction of goal directed thinking in completely paralysed patients?
Open accessAbstract
Objective To investigate the relationship between physical impairment and brain-computer interface (BCI) performance.Method We present a meta-analysis of 29 patients with amyotrophic lateral sclerosis and six patients with other severe neurological diseases in different stages of physical impairment who were trained with a BCI. In most cases voluntary regulation of slow cortical potentials has been used as input signal for BCI-control. More recently sensorimotor rhythms and the P300 event-related brain potential were recorded.Results A strong correlation has been found between physical impairment and BCI performance, indicating that performance worsens as impairment increases. Seven patients were in the complete locked-in state (CLIS) with no communication possible. After removal of these patients from the analysis, the relationship between physical impairment and BCI performance disappeared. The lack of a relation between physical impairment and BCI performance was confirmed when adding BCI data of patients from other BCI research groups.Conclusions Basic communication (yes/no) was not restored in any of the CLIS patients with a BCI. Whether locked-in patients can transfer learned brain control to the CLIS remains an open empirical question.Significance Voluntary brain regulation for communication is possible in all stages of paralysis except the CLIS.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Firstly, works where users acquired BCI control (able-bodied [3,25] and end-users [40,41,51,62,63]) do not report any learning metric over time.”
From The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users (2018) · cites this paper as [62]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Experimental Design: Procedures for the Behavioral Sciences
Kirk, R. (2013) · doi:10.4135/9781483384733 · Cited by 8,539
Electroencephalography—Basic principles, clinical applications and related fields
(1982) · Journal of the Autonomic Nervous System · doi:10.1016/0165-1838(82)90067-4 · Cited by 3,449
Neuronal ensemble control of prosthetic devices by a human with tetraplegia
Hochberg, L. R., Serruya, M. D., Friehs, G. M., Mukand, J. A., Saleh, M., Caplan, A. H., Branner, A., Chen, D., Penn, R. D., & Donoghue, J. P. (2006) · Nature · doi:10.1038/nature04970 · Cited by 3,295
Farwell, L. A., & Donchin, E. (1988) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/0013-4694(88)90149-6 · Cited by 3,228
Brain-computer interface technology: a review of the first international meeting
Wolpaw, J. R., Birbaumer, N., Heetderks, W., McFarland, D. J., Peckham, P. H., Schalk, G., Donchin, E., Quatrano, L. A., Robinson, C. J., & Vaughan, T. M. (2000) · IEEE Transactions on Rehabilitation Engineering · doi:10.1109/tre.2000.847807 · Cited by 2,322
Self-citationDetecting awareness in the vegetative state
Owen, A. M., Coleman, M. R., Boly, M., Davis, M. H., Laureys, S., & Pickard, J. D. (2006) · Science · doi:10.1126/science.1130197 · Cited by 1,978
A spelling device for the paralysed
Birbaumer, N., Ghanayim, N., Hinterberger, T., Iversen, I., Kotchoubey, B., Kübler, A., Perelmouter, J., Taub, E., & Flor, H. (1999) · Nature · doi:10.1038/18581 · Cited by 1,577
Self-citationControl of a two-dimensional movement signal by a noninvasive brain-computer interface in humans
Wolpaw, J. R., & McFarland, D. J. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0403504101 · Cited by 1,512
Slow potentials of the cerebral cortex and behavior.
Birbaumer, N., Elbert, T. R., Canavan, A. G. M., & Rockstroh, B. S. (1990) · Physiological Reviews · doi:10.1152/physrev.1990.70.1.1 · Cited by 1,099
Self-citationBrain function in coma, vegetative state, and related disorders
Laureys, S., Owen, A. M., & Schiff, N. D. (2004) · The Lancet Neurology · doi:10.1016/s1474-4422(04)00852-x · Cited by 1,033
Cited by
Sorted by citations
Items 401–441 of 441
A Concept-Based P300 Communication System
Smith, C. D. D. (2012) · TSpace (University of Toronto)
Separable Spatio-spectral Patterns in EEG signals During Motor-imagery Tasks
Aghaei, A. S. (2014) · TSpace (University of Toronto)
Nishifuji, S., Matsubara, A., Iwata, A., Sugita, Y., Tanaka, F., & Hirano, H. (2016) · IEEE Global Conference on Consumer Electronics (GCCE) · doi:10.1109/gcce.2016.7800454
Zhou, S., Chen, L., Zhang, Y., Jin, J., & Wang, X. (2016) · IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS) · doi:10.1109/ccis.2016.7790234
Interfejsy BCI jako nowy kanał komunikacji dla osób z niepełnosprawnością ruchową
Sójka, A., Janiak, K., Sikorska-Nowak, A., & Smółka, K. (2016) · Roczniki Kolegium Analiz Ekonomicznych
Continuous use of ERP-based BCIs with different visual angles in ALS patientsPreprint
Jin, J., Allison, B. Z., Zhang, Y., Chen, Y., Zhou, S., Dong, Y., Wang, X., & Chchocki, A. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1706.09089
Pan, J., Xie, Q., Lin, Q. H., Huang, H., Fei, W., Yu, R., & Li, Y. (2017) · International IEEE/EMBS Conference on Neural Engineering · doi:10.1109/ner.2017.8008379
Detecting Emotional Response to Music using Near-infrared Spectroscopy of the Prefrontal Cortex
Moghimi, S. (2014) · TSpace (University of Toronto)
Research on the correlation between micro force stimulation and sEMG signals
Wang, H., Shuliang, Z. H. O. U., Ge, Y., & Qiu, Y. (2017) · IEEE International Conference on Information and Automation (ICIA) · doi:10.1109/icinfa.2017.8078918
House, S. C. (2018) · TSpace (University of Toronto)
Towards Context-aware Brain-computer Interfaces
Myrden, A. (2016) · TSpace (University of Toronto)
Brain Computer Interface Using Response of Alpha Wave to Word Task
Nishifuji, S., Yasunaga, K., Matsubara, A., & Nakashima, S. (2021) · IEEE Global Conference on Consumer Electronics (GCCE) · doi:10.1109/gcce53005.2021.9621831
Robotic Technologies and Fundamental Rights
Koops, B., Carlo, A. D., Nocco, L., Casamassima, V., & Stradella, E. (2014) · IGI Global eBooks · doi:10.4018/978-1-4666-6433-3.ch065
(2019) · Elsevier eBooks · doi:10.1016/b978-0-12-816179-1.00042-6
Wang, F., Wan, Y., Li, Z., Qi, F., & Li, J. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.1167125
Krauß, P. (2023) · Springer eBooks · doi:10.1007/978-3-662-67179-5_9
Exploring connectivity of resting-state EEG between BCI-literate and -illiterate groupsPreprint
Park, H., & Jun, S. C. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.11.25.568691
Krauß, P. (2024) · Springer eBooks · doi:10.1007/978-3-662-68980-6_9
Sawada, N., Uehara, A., Kawamoto, H., & Sankai, Y. (2025) · IEEE/SICE International Symposium on System Integration (SII) · doi:10.1109/sii59315.2025.10871110
Noninvasive BCI for Communication
Chaudhary, U. (2025) · Springer eBooks · doi:10.1007/978-3-031-78991-5_4
Kushwah, P., Tiwari, V., Shukla, S. K., & Tiwari, A. (2025) · IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI) · doi:10.1109/iatmsi64286.2025.10984968
Transforming Communication Protocols
Ramaraj, S., Kumar, N., Sreeja, B. P., Anusha, P., Saidala, R. K., Selvameena, R., & Pandey, D. (2025) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-5122-3.ch001
NeuroCommTrainer: Toward an Adaptive and Wearable Multimodal Brain–Computer Interface
Scherer, J., Finke, A., Everding, V., Lindenbaum, L., Kayser, C., & Kissler, J. M. (2025) · Brain Connectivity · doi:10.1177/21580014251393151
Eye Blink Based Smart Assistance System for ALS Patients Using EAR Algorithm
Arun Kumar, S., Sahana, S. S., Kumar, M. A., Chinmayi, D., Nimje, A. P., & Sohan, D. N. (2025) · International Conference on New Frontiers in Communication, Automation, Management and Security (ICCAMS) · doi:10.1109/iccams65118.2025.11234028
Lodhi, S., Ibrahim, H., Rizwan, I., & Saleem, A. (2025) · International Conference on Electrical, Communication, and Computer Engineering (ICECCE) · doi:10.1109/icecce67514.2025.11258070
Yamaguchi, T., Hashimoto, R., & Sato, H. R. (2025) · Brain Topography · doi:10.1007/s10548-025-01162-7
Kerchove, A. V. D., Meunier, J., de Moura, M., Willemssens, A., Geeurickx, D., Schiettecatte, E., Damme, P. V., Si-Mohammed, H., Cabestaing, F., Allart, E., et al. (2025) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-025-01836-0
Subdomain Adaption Method for Cross-Domain Emotion Recognition and Clinical Consciousness Detection
Pan, J., He, Z., Zhu, J., Liang, R., Chen, Z., Xie, Q., Li, J., & Li, Y. (2026) · IEEE Internet of Things Journal · doi:10.1109/jiot.2025.3650676
UGR-MINDVOICE: A multimodal EEG-audio dataset for overt and covert Iberian Spanish speech production
Cortina, I. V., Khanday, O. M., Ouellet, M., Pérez-Córdoba, J. L., Esteban, P. R.-S., Miccoli, L., Galdón, A., Granados, G. O., & González, J. A. (2026) · Computer Speech & Language · doi:10.1016/j.csl.2026.101964 · Cited by 1
A visual Brain-Computer Interface for gaze-free communication : Algorithms & applications
Kerchove, A. V. D. (2024) · theses.fr (ABES) · doi:10.70675/7ee5680eze506z4dbdz8078z01924f3e063a
Gao, T. (2026) · BIO Web of Conferences · doi:10.1051/bioconf/202623703002 · Cited by 2
Frycz, S., Więcławski, W., Skotniczny, M., & Binder, M. (2026) · Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration · doi:10.1080/21678421.2026.2688249
Huggins, J. E., Mattia, D., Aarnoutse, E. J., Allison, B. Z., Berezutskaya, J., Bianchi, L., Chavarriaga, R., Corsi, M., Dean, H., Fernandes, F., et al. (2026) · Research in Biomedical Engineering and Technology · doi:10.1080/29960355.2026.2731643
Settgast, T., Shriki, O., Northoff, G., Zilio, F., Borgheai, S. B., Shahriari, Y., & Kübler, A. (2026) · Research Square · doi:10.21203/rs.3.rs-10422321/v1
Self-citationYang, Y., Zan, X., Niu, C., Ma, J., & Gao, M. (2026) · Research Square · doi:10.21203/rs.3.rs-10725532/v1
Towards a Neurodata Protection Framework in Australia
Revis, R., & Singh, A. (2026) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn69854.2026.11728729
Lobo-Prat, J. (2013) · Research Repository (Delft University of Technology)
Metadata
- Authors
- Kübler, A., & Birbaumer, N.
- Affiliations
- University of Tübingen (DE)
- National Institutes of Health (US)
- Corresponding author
- Kübler, A.
- Venue
- Clinical Neurophysiology
- Publisher
- Elsevier BV
- Published
- 2008-11
- Volume
- 119
- Issue
- 11
- Pages
- 2658-2666
- ISSN
- 1388-2457 (ISSN-L)
- PMC
- PMC2644824
- OpenAlex
- W1972606226
- Cited by
- 441
- References
- 50
- Citations by year
- 2026: 10 · 2025: 20 · 2024: 14 · 2023: 14 · 2022: 13 · 2021: 18 · 2020: 26 · 2019: 20 · 2018: 26 · 2017: 22 · 2016: 35 · 2015: 33 · 2014: 35 · 2013: 43 · 2012: 39
- FWCI
- 12.57
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Clinical Neurophysiology (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Deutsche Forschungsgemeinschaft
- National Institute of Neurological Disorders and Stroke
- National Institute of Biomedical Imaging and Bioengineering (EB 00856, R01EB000856)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD030146, HD30146)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Physical Sciences › Computer Science › Human-Computer Interaction › Gaze Tracking and Assistive Technology
- Health Sciences › Medicine › Rehabilitation › Stroke Rehabilitation and Recovery
- Keywords
- brain-computer interface, paralysis, amyotrophic lateral sclerosis, locked-in state, physical impairment, communication, slow cortical potentials, sensorimotor rhythm, P300
- MeSH terms
- Adult, Aged, Brain Diseases, Communication Devices for People with Disabilities, Computer Systems, Electroencephalography, Female, Goals, Humans, Male, Middle Aged, Paralysis, Periodicity, Thinking, User-Computer Interface, Meta-Analysis as Topic, Event-Related Potentials, P300
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
