The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.
Clinical application of an EEG-based brain–computer interface: a case study in a patient with severe motor impairment
Abstract
Objective This case study describes how a completely paralyzed patient, diagnosed with severe cerebral palsy, was trained over a period of several months to use an electroencephalography (EEG)-based brain-computer interface (BCI) for verbal communication.Methods EEG feedback training was performed in the patient's home (clinic), supervised from a distant laboratory with the help of a 'telemonitoring system'. Online feedback computation was based on single-trial analysis and classification of specific band power features of the spontaneous EEG. Task-related changes in brain oscillations over the course of training steps was investigated by quantifying time-frequency maps of event-related (de-)synchronization (ERD/ERS).Results The patient learned to 'produce' two distinct EEG patterns, beta band ERD during movement imagery vs. no ERD during relaxing, and to use this for BCI-controlled spelling. Significant learning progress was found as a function of training session, resulting in an average accuracy level of 70% (correct responses) for letter selection. 'Copy spelling' was performed with a rate of approximately one letter per min.Conclusions The proposed BCI training procedure, based on electroencephalogram (EEG) biofeedback and concomitant adaptation of feature extraction and classification, may improve actual levels of communication ability in locked-in patients. 'Telemonitoring-assisted' BCI training facilitates clinical application in a larger number of patients.
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“Direct evidence of learned SMR modulation at the BCI feature level is, in fact, rare or incomplete, derived in able-bodied populations and not longitudinal [10,23,26,28,38–41].”
From The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users (2018) · cites this paper as [10]
In the citing paper
“The most complete evidence of subject learning with obvious translational implications is offered in [9], [10], and [42].”
From The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users (2018) · cites this paper as [10]
In the citing paper
“Furthermore, [10] and [42] substantiate learning effects with event-related desynchronization/synchronization (ERD/ERS) maps and SMR topographies, respectively, over 3–4 time points throughout the training period.”
From The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users (2018) · cites this paper as [10]
In the citing paper
“These works report on longitudinal training and involve end-users.”
From The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users (2018) · cites this paper as [10]
Citations
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Self-citationA spelling device for the paralysed
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Self-citationToward Direct Brain-Computer Communication
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A brain–computer interface using electrocorticographic signals in humans
Leuthardt, E. C., Schalk, G., Wolpaw, J. R., Ojemann, J. G., & Moran, D. W. (2004) · Journal of Neural Engineering · doi:10.1088/1741-2560/1/2/001 · Cited by 1,188
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Brain-Computer Interfaces in Medicine
Shih, J. J., Krusienski, D. J., & Wolpaw, J. R. (2012) · Mayo Clinic Proceedings · doi:10.1016/j.mayocp.2011.12.008 · Cited by 796
Breaking the silence: Brain-computer interfaces (BCI) for communication and motor control
Birbaumer, N. (2006) · Psychophysiology · doi:10.1111/j.1469-8986.2006.00456.x · Cited by 722
Self-citationNeurophysiological predictor of SMR-based BCI performance
Blankertz, B., Sannelli, C., Halder, S., Hammer, E. M., Kübler, A., Müller, K.-R., Curio, G., & Dickhaus, T. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.03.022 · Cited by 674
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Metadata
- Authors
- Neuper, C., Müller, G. R., Kübler, A., Birbaumer, N., & Pfurtscheller, G.
- Affiliations
- Graz University of Technology (AT)
- University of Tübingen (DE)
- University of Trento (IT)
- Corresponding author
- Neuper, C
- Venue
- Clinical Neurophysiology
- Publisher
- Elsevier BV
- Published
- 2003-03
- Volume
- 114
- Issue
- 3
- Pages
- 399-409
- ISSN
- 1388-2457 (ISSN-L)
- OpenAlex
- W2018281395
- Cited by
- 317
- References
- 47
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 4 · 2023: 4 · 2022: 7 · 2021: 5 · 2020: 12 · 2019: 13 · 2018: 15 · 2017: 10 · 2016: 21 · 2015: 22 · 2014: 19 · 2013: 27 · 2012: 28
- FWCI
- 4.89
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Clinical Neurophysiology (publishedVersion)
- PubMed (publishedVersion)
- 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
- EEG-based brain-computer interface, severe cerebral palsy, locked-in syndrome, motor impairment, remote patient monitoring, event-related desynchronization, event-related synchronization, beta band, movement imagery, spelling, verbal communication
- MeSH terms
- Adult, Biofeedback, Psychology, Cerebral Palsy, Communication Devices for People with Disabilities, Communication Barriers, Electroencephalography, Humans, Male, Motor Cortex, Paralysis, Severity of Illness Index, Somatosensory Cortex, User-Computer Interface
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