Noninvasive brain-computer interface enables communication after brainstem stroke
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An individual “locked-in” by a brainstem stroke was able to communicate using noninvasive brain-computer interface technology.
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The emergence of interfaces based on evoked responses (P300, SSVEP) as the most efficient BCI solution for communication has promoted the use of machine learning because the margin for humans to learn to regulate evoked potentials is considered narrow.
“On the one hand, the emergence of interfaces based on evoked responses (P300, steady-state visually evoked potentials [SSVEP]) as the most efficient BCI solution for communication [13–16] has promoted the use of machine learning because the margin for humans to learn to regulate evoked potentials is considered to be narrow.”
From The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users (2018) · cites this paper as [14]
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- Authors
- Sellers, E. W., Ryan, D. B., & Hauser, C. K.
- Affiliations
- East Tennessee State University (US)
- Venue
- Science Translational Medicine
- Published
- 2014-10-08
- Volume
- 6
- Issue
- 257
- Pages
- 257re7-257re7
- ISSN
- 1946-6234 (ISSN-L)
- 1946-6242
- PMC
- PMC4711808
- OpenAlex
- W2122424463
- Cited by
- 140
- References
- 24
- Citations by year
- 2026: 10 · 2025: 9 · 2024: 7 · 2023: 9 · 2022: 9 · 2021: 8 · 2020: 9 · 2019: 15 · 2018: 19 · 2017: 17 · 2016: 14 · 2015: 11 · 2014: 3
- FWCI
- 8.36
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science Translational Medicine (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Digital Commons - East Tennessee State University (East Tennessee State University) (submittedVersion)
- Funders
- National Institute on Deafness and Other Communication Disorders (R33DC010470)
- National Institute of Biomedical Imaging and Bioengineering (EB 00856, R01EB000856)
- 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, brainstem infarction, locked-in syndrome, P300 event-related potential, communication aids, amyotrophic lateral sclerosis, assistive technology, neurodegenerative diseases
- MeSH terms
- Algorithms, Communication Devices for People with Disabilities, Electroencephalography, Humans, Male, Neuropsychological Tests, Quadriplegia, Task Performance and Analysis, Event-Related Potentials, P300, Brain Stem Infarctions, Diffusion Magnetic Resonance Imaging, Translational Research, Biomedical, Brain-Computer Interfaces
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