The DOI matches its Crossref record; 63 of the 63 references it cites were found in a registry or an index.
Open Access Dataset for EEG+NIRS Single-Trial Classification
Abstract
We provide an open access dataset for hybrid brain-computer interfaces (BCIs) using electroencephalography (EEG) and near-infrared spectroscopy (NIRS). For this, we con-ducted two BCI experiments (left vs. right hand motor imagery; mental arithmetic vs. resting state). The dataset was validated using baseline signal analysis methods, with which classification performance was evaluated for each modality and a combination of both modalities. As already shown in previous literature, the capability of discriminating different mental states can be en-hanced by using a hybrid approach, when comparing to single modality analyses. This makes the provided data highly suitable for hybrid BCI investigations. Since our open access dataset also comprises motion artifacts and physiological data, we expect that it can be used in a wide range of future validation approaches in multimodal BCI research.
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Cites
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Brain–computer interfaces for communication and control
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A 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
Regularized Discriminant Analysis
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Optimizing Spatial filters for Robust EEG Single-Trial Analysis
Blankertz, B., Tomioka, R., Lemm, S., Kawanabe, M., & Muller, K.-R. (2008) · IEEE Signal Processing Magazine · doi:10.1109/msp.2008.4408441 · Cited by 2,080
Self-citationMotor imagery and direct brain-computer communication
Pfurtscheller, G., & Neuper, C. (2001) · Proceedings of the IEEE · doi:10.1109/5.939829 · Cited by 1,990
Brain–machine interfaces: past, present and future
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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-citationSingle-trial analysis and classification of ERP components — A tutorial
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Self-citationBrain–Computer InterfacesPrinciples and Practice
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Cited by
Kwon, J., Shin, J., & Im, C.-H. (2020) · PLOS ONE · doi:10.1371/journal.pone.0230491 · Cited by 53
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Metadata
- Authors
- Shin, J., von Luhmann, A., Blankertz, B., Kim, D.-W., Jeong, J., Hwang, H.-J., & Muller, K.-R.
- Venue
- IEEE Transactions on Neural Systems and Rehabilitation Engineering
- Published
- 2017-10
- Volume
- 25
- Issue
- 10
- Pages
- 1735-1745
- ISSN
- 1534-4320 (ISSN-L)
- 1558-0210
- OpenAlex
- W2552578398
- Cited by
- 287
- References
- 63
- FWCI
- 7.05
- Type
- journal article
- Language
- en
- Open access
- closed
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- Shin, J., von Luhmann, A., Blankertz, B., Kim, D.-W., Jeong, J., Hwang, H.-J., & Muller, K.-R. (2017). Open Access Dataset for EEG+NIRS Single-Trial Classification. IEEE Transactions on Neural Systems and Rehabilitation Engineering. https://doi.org/10.1109/tnsre.2016.2628057
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