Patients with ALS can use sensorimotor rhythms to operate a brain-computer interface
Abstract
People with severe motor disabilities can maintain an acceptable quality of life if they can communicate. Brain-computer interfaces (BCIs), which do not depend on muscle control, can provide communication. Four people severely disabled by ALS learned to operate a BCI with EEG rhythms recorded over sensorimotor cortex. These results suggest that a sensorimotor rhythm-based BCI could help maintain quality of life for people with ALS.
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Evidence that co-adaptive MI BCIs might also be able to promote and increase the ability of users to voluntarily modulate their brain signals (subject learning) is scarce, most often indirect and rather inconclusive.
“Evidence that co-adaptive MI BCIs might also be able to promote and increase the ability of the users to voluntary modulate their brain signals (subject learning) is, in fact, scarce, most often indirect and rather inconclusive.”
From The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users (2018) · cites this paper as [30]
Mutual learning has been claimed mostly on the grounds of adequate and improved BCI classification accuracy or application performances.
“Indeed, mutual learning has been claimed mostly on the grounds of adequate and improved BCI classification accuracy [25,27,30–35] or application performances [36,37].”
From The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users (2018) · cites this paper as [30]
Other training studies claim learnability in BCIs only on the grounds of improved online classification accuracy or application performances.
“Secondly, other training studies claim learnability in BCIs only on the grounds of improved online classification accuracy [9,27,30,31,33,35,51] or application performances [36,37].”
From The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users (2018) · cites this paper as [30]
Neural signals from the brain have been used in applications ranging from medical to engineering fields, such as epilepsy surgery using ECoG and brain computer interface applications using EEG.
“Such signals were used in various applications ranging from medical to engineering fields, such as an epilepsy surgery using ECoG 88 and brain computer interface applications using EEG.89,90”
From From flexible electronics technology in the era of IoT and artificial intelligence toward future implanted body sensor networks (2019) · cites this paper as [90]
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- Authors
- Kübler, A., Nijboer, F., Mellinger, J., Vaughan, T. M., Pawelzik, H., Schalk, G., McFarland, D. J., Birbaumer, N., & Wolpaw, J. R.
- Affiliations
- University of Tübingen (DE)
- University at Albany, State University of New York (US)
- IRCCS San Camillo Hospital (IT)
- Venue
- Neurology
- Published
- 2005-05-24
- Volume
- 64
- Issue
- 10
- Pages
- 1775-1777
- ISSN
- 0028-3878 (ISSN-L)
- 1526-632X
- OpenAlex
- W2014320934
- Cited by
- 539
- References
- 9
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 11 · 2023: 15 · 2022: 13 · 2021: 28 · 2020: 23 · 2019: 23 · 2018: 26 · 2017: 25 · 2016: 35 · 2015: 35 · 2014: 36 · 2013: 52 · 2012: 40
- FWCI
- 12.69
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Neurology (publishedVersion)
- PubMed (publishedVersion)
- Institutional Research Information System (Università degli Studi di Trento) (submittedVersion)
- Funders
- Eberhard Karls Universität Tübingen
- 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
- amyotrophic lateral sclerosis, brain-computer interface, sensorimotor rhythm, EEG, motor impairment, communication, sensorimotor cortex, assistive technology
- MeSH terms
- Aged, Amyotrophic Lateral Sclerosis, Electroencephalography, Evoked Potentials, Somatosensory, Female, Humans, Imagination, Male, Middle Aged, Motor Cortex, Movement, Paralysis, Photic Stimulation, Somatosensory Cortex, User-Computer Interface, Treatment Outcome, Evoked Potentials, Motor, Prostheses and Implants
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