A brain-computer interface for long-term independent home use
Abstract
Our objective was to develop and validate a new brain-computer interface (BCI) system suitable for long-term independent home use by people with severe motor disabilities. The BCI was used by a 51-year-old male with ALS who could no longer use conventional assistive devices. Caregivers learned to place the electrode cap, add electrode gel, and turn on the BCI. After calibration, the system allowed the user to communicate via EEG. Re-calibration was performed remotely (via the internet), and BCI accuracy assessed in periodic tests. Reports of BCI usefulness by the user and the family were also recorded. Results showed that BCI accuracy remained at 83% (r = -.07, n.s.) for over 2.5 years (1.4% expected by chance). The BCI user and his family state that the BCI had restored his independence in social interactions and at work. He uses the BCI to run his NIH-funded research laboratory and to communicate via e-mail with family, friends, and colleagues. In addition to this first user, several other similarly disabled people are now using the BCI in their daily lives. In conclusion, long-term independent home use of this BCI system is practical for severely disabled people, and can contribute significantly to quality of life and productivity.
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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 [13]
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- Authors
- Sellers, E. W., Vaughan, T. M., & Wolpaw, J. R.
- Affiliations
- East Tennessee State University (US)
- New York State Department of Health (US)
- Corresponding author
- Sellers, Eric W.
- Venue
- Amyotrophic Lateral Sclerosis
- Publisher
- Informa UK Limited
- Published
- 2010-06-29
- Volume
- 11
- Issue
- 5
- Pages
- 449-455
- ISSN
- 1471-180X (ISSN-L)
- 1748-2968
- OpenAlex
- W1973921785
- Cited by
- 400
- References
- 30
- Citations by year
- 2026: 5 · 2025: 12 · 2024: 12 · 2023: 9 · 2022: 12 · 2021: 17 · 2020: 26 · 2019: 21 · 2018: 23 · 2017: 27 · 2016: 31 · 2015: 47 · 2014: 48 · 2013: 37 · 2012: 33
- FWCI
- 21.08
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Amyotrophic Lateral Sclerosis (publishedVersion)
- PubMed (publishedVersion)
- Digital Commons - East Tennessee State University (East Tennessee State University) (submittedVersion)
- Funders
- ALS Hope Foundation
- 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)
- National Center for Medical Rehabilitation Research
- 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 › Health Professions › Occupational Therapy › Assistive Technology in Communication and Mobility
- Keywords
- brain-computer interface, severe motor impairment, EEG-based communication, assistive technology, caregiver education, quality of life
- MeSH terms
- Amyotrophic Lateral Sclerosis, Brain, Communication Devices for People with Disabilities, Electroencephalography, Persons with Disabilities, Humans, Male, Middle Aged, User-Computer Interface, Homebound Persons, Event-Related Potentials, P300
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