The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
Separability of EEG signals recorded during right and left motor imagery using adaptive autoregressive parameters
Abstract
Electroencephalogram (EEG) recordings during right and left motor imagery can be used to move a cursor to a target on a computer screen. Such an EEG-based brain-computer interface (BCI) can provide a new communication channel to replace an impaired motor function. It can be used by, e.g., patients with amyotrophic lateral sclerosis (ALS) to develop a simple binary response in order to reply to specific questions. Four subjects participated in a series of on-line sessions with an EEG-based cursor control. The EEG was recorded from electrodes overlying sensory-motor areas during left and right motor imagery. The EEG signals were analyzed in subject-specific frequency bands and classified on-line by a neural network. The network output was used as a feedback signal. The on-line error (100%-perfect classification) was between 10.0 and 38.1%. In addition, the single-trial data were also analyzed off-line by using an adaptive autoregressive (AAR) model of order 6. With a linear discriminant analysis the estimated parameters for left and right motor imagery were separated. The error rate obtained varied between 5.8 and 32.8% and was, on average, better than the on-line results. By using the AAR-model for on-line classification an improvement in the error rate can be expected, however, with a classification delay around 1 s.
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.
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
Neural networks for pattern recognition
(1994) · Choice Reviews Online · doi:10.5860/choice.31-5500 · Cited by 18,538
Kohonen, T. (1990) · Proceedings of the IEEE · doi:10.1109/5.58325 · Cited by 8,414
Synchronization of cortical activity and its putative role in information processing and learning
Singer, W. (1993) · Annual Review of Physiology · doi:10.1146/annurev.ph.55.030193.002025 · Cited by 1,685
Toward Direct Brain-Computer Communication
Vidal, J. J. (1973) · Annual Review of Biophysics and Bioengineering · doi:10.1146/annurev.bb.02.060173.001105 · Cited by 1,287
Event-related synchronization (ERS): an electrophysiological correlate of cortical areas at rest
Pfurtscheller, G. (1992) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/0013-4694(92)90133-3 · Cited by 981
Self-citationEEG-based discrimination between imagination of right and left hand movement
Pfurtscheller, G., Neuper, C., Flotzinger, D., & Pregenzer, M. (1997) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/s0013-4694(97)00080-1 · Cited by 904
Self-citationJasper, H., & Penfield, W. (1949) · Archiv f�r Psychiatrie und Nervenkrankheiten · doi:10.1007/bf01062488 · Cited by 682
Cooper, R., Winter, A. L., Crow, H. J., & Walter, W. G. (1965) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/0013-4694(65)90088-x · Cited by 561
Patterns of cortical activation during planning of voluntary movement
Pfurtscheller, G., & Berghold, A. (1989) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/0013-4694(89)90250-2 · Cited by 521
Self-citationBrain-Computer Interface—a new communication device for handicapped persons
Pfurtscheller, G., Flotzinger, D., & Kalcher, J. (1993) · Journal of Microcomputer Applications · doi:10.1006/jmca.1993.1030 · Cited by 502
Self-citation
Cited by
Brain–computer interfaces for communication and control
Wolpaw, J. R., Birbaumer, N., McFarland, D. J., Pfurtscheller, G., & Vaughan, T. M. (2002) · Clinical Neurophysiology · doi:10.1016/s1388-2457(02)00057-3 · Cited by 7,927
Self-citationA review of classification algorithms for EEG-based brain–computer interfaces
Lotte, F., Congedo, M., Lécuyer, A., Lamarche, F., & Arnaldi, B. (2007) · Journal of Neural Engineering · doi:10.1088/1741-2560/4/2/r01 · Cited by 2,665
Optimal spatial filtering of single trial EEG during imagined hand movement
Ramoser, H., Muller-Gerking, J., & Pfurtscheller, G. (2000) · IEEE Transactions on Rehabilitation Engineering · doi:10.1109/86.895946 · Cited by 2,457
Self-citationKushida, C. A., Littner, M. R., Morgenthaler, T., Alessi, C. A., Bailey, D., Coleman, J., Friedman, L., Hirshkowitz, M., Kapen, S., Kramer, M., et al. (2005) · Sleep · doi:10.1093/sleep/28.4.499 · Cited by 2,054
Motor imagery and direct brain-computer communication
Pfurtscheller, G., & Neuper, C. (2001) · Proceedings of the IEEE · doi:10.1109/5.939829 · Cited by 1,990
Self-citation
Metadata
- Authors
- Pfurtscheller, G., Neuper, C., Schlogl, A., & Lugger, K.
- Venue
- IEEE Transactions on Rehabilitation Engineering
- Published
- 1998
- Volume
- 6
- Issue
- 3
- Pages
- 316-325
- ISSN
- 1063-6528 (ISSN-L)
- OpenAlex
- W2156832349
- Cited by
- 553
- References
- 22
- FWCI
- 5.27
- Type
- journal article
- Language
- en
- Open access
- closed
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Separability of EEG signals recorded during right and left motor imagery using adaptive autoregressive parameters. https://app.cochat.ai/papers/10.1109/86.712230
- The paper
- Pfurtscheller, G., Neuper, C., Schlogl, A., & Lugger, K. (1998). Separability of EEG signals recorded during right and left motor imagery using adaptive autoregressive parameters. IEEE Transactions on Rehabilitation Engineering. https://doi.org/10.1109/86.712230
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
