The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Brain–Computer Communication: Motivation, Aim, and Impact of Exploring a Virtual Apartment
Open accessAbstract
The step away from a synchronized or cue-based brain-computer interface (BCI) and from laboratory conditions towards real world applications is very important and crucial in BCI research. This work shows that ten naive subjects can be trained in a synchronous paradigm within three sessions to navigate freely through a virtual apartment, whereby at every junction the subjects could decide by their own, how they wanted to explore the virtual environment (VE). This virtual apartment was designed similar to a real world application, with a goal-oriented task, a high mental workload, and a variable decision period for the subject. All subjects were able to perform long and stable motor imagery over a minimum time of 2 s. Using only three electroencephalogram (EEG) channels to analyze these imaginations, we were able to convert them into navigation commands. Additionally, it could be demonstrated that motivation is a very crucial factor in BCI research; motivated subjects perform much better than unmotivated ones.
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Cites
Neural networks for pattern recognition
(1994) · Choice Reviews Online · doi:10.5860/choice.31-5500 · Cited by 18,538
Neural Networks for Pattern Recognition
Bishop, C. M. (1995) · doi:10.1093/oso/9780198538493.001.0001 · Cited by 12,287
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-citationThe ten-twenty electrode system of the international federation
Jasper, H. H. (1958) · Electroencephalography and Clinical Neurophysiology · Cited by 6,567
Floating search methods in feature selection
Pudil, P., Novovičová, J., & Kittler, J. (1994) · Pattern Recognition Letters · doi:10.1016/0167-8655(94)90127-9 · Cited by 3,098
Report of the committee on methods of clinical examination in electroencephalography
(1958) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/0013-4694(58)90053-1 · Cited by 2,717
Brain-computer interface technology: a review of the first international meeting
Wolpaw, J. R., Birbaumer, N., Heetderks, W. J., McFarland, D. J., Peckham, P. H., Schalk, G., Donchin, E., Quatrano, L. A., Robinson, C. J., & Vaughan, T. M. (2000) · IEEE Transactions on Rehabilitation Engineering · doi:10.1109/tre.2000.847807 · Cited by 2,324
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-citationNeural networks for pattern recognition
Marshall, J. A. (1995) · Neural Networks · doi:10.1016/0893-6080(95)90002-0 · Cited by 1,889
Mu rhythm (de)synchronization and EEG single-trial classification of different motor imagery tasks
Pfurtscheller, G., Brunner, C., Schlögl, A., & Lopes da Silva, F. H. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2005.12.003 · Cited by 1,587
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Review of the BCI Competition IV
Tangermann, M., Müller, K.-R., Aertsen, A., Birbaumer, N., Braun, C., Brunner, C., Leeb, R., Mehring, C., Miller, K. J., Müller-Putz, G. R., et al. (2012) · Frontiers in Neuroscience · doi:10.3389/fnins.2012.00055 · Cited by 1,288
Self-citationFilter Bank Common Spatial Pattern Algorithm on BCI Competition IV Datasets 2a and 2b
Ang, K. K., Chin, Z. Y., Wang, C., Guan, C., & Zhang, H. (2012) · Frontiers in Neuroscience · doi:10.3389/fnins.2012.00039 · Cited by 1,264
A novel deep learning approach for classification of EEG motor imagery signals
Tabar, Y. R., & Halici, U. (2017) · Journal of Neural Engineering · doi:10.1088/1741-2560/14/1/016003 · Cited by 859
Nijboer (2010) · Frontiers in Neuroscience · doi:10.3389/fnins.2010.00055 · Cited by 323
Huang, D., Qian, K., Fei, D.-Y., Jia, W., Chen, X., & Bai, O. (2012) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2012.2190299 · Cited by 237
Metadata
- Authors
- Leeb, R., Lee, F., Keinrath, C., Scherer, R., Bischof, H., & Pfurtscheller, G.
- Venue
- IEEE Transactions on Neural Systems and Rehabilitation Engineering
- Published
- 2007-12
- Volume
- 15
- Issue
- 4
- Pages
- 473-482
- ISSN
- 1534-4320 (ISSN-L)
- 1558-0210
- OpenAlex
- W2133565549
- Cited by
- 513
- References
- 28
- FWCI
- 8.20
- Type
- journal article
- Language
- en
- Open access
- green
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- Leeb, R., Lee, F., Keinrath, C., Scherer, R., Bischof, H., & Pfurtscheller, G. (2007). Brain–Computer Communication: Motivation, Aim, and Impact of Exploring a Virtual Apartment. IEEE Transactions on Neural Systems and Rehabilitation Engineering. https://doi.org/10.1109/tnsre.2007.906956
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