The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
A general framework for brain-computer interface design
Abstract
The Brain-Computer Interface (BCI) research community has acknowledged that researchers are experiencing difficulties when they try to compare the BCI techniques described in the literature. In response to this situation, the community has stressed the need for objective methods to compare BCI technologies. Suggested improvements have included the development and use of benchmark applications and standard data sets. However, as a young, multidisciplinary research field, the BCI community lacks a common vocabulary. As a result, this deficiency leads to poor intergroup communication, which hinders the development of the desired methods of comparison. One of the principle reasons for the lack of common vocabulary is the absence of a common functional model of a BCI System. This paper proposes a new functional model for BCI System design. The model supports many features that facilitate the comparison of BCI technologies with other BCI and non-BCI user interface technologies. From this model, taxonomy for BCI System design is developed. Together the model and taxonomy are considered a general framework for BCI System design. The representational power of the proposed framework was evaluated by applying it to a set of existing BCI technologies. The framework could effectively describe all of the BCI System designs tested.
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Cites
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Cited by
Brain Computer Interfaces, a Review
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Bashashati, A., Fatourechi, M., Ward, R. K., & Birch, G. E. (2007) · Journal of Neural Engineering · doi:10.1088/1741-2560/4/2/r03 · Cited by 907
Self-citationNijboer (2010) · Frontiers in Neuroscience · doi:10.3389/fnins.2010.00055 · Cited by 323
A Survey on Measuring Cognitive Workload in Human-Computer Interaction
Kosch, T., Karolus, J., Zagermann, J., Reiterer, H., Schmidt, A., & Woźniak, P. W. (2023) · ACM Computing Surveys · doi:10.1145/3582272 · Cited by 304
“EEG is commonly leveraged in clinical applications and yields a non-invasive method to estimate cortical activity [166, 180, 254].”
A Comprehensive Survey of Brain Interface Technology Designs
Mason, S. G., Bashashati, A., Fatourechi, M., Navarro, K. F., & Birch, G. E. (2007) · Annals of Biomedical Engineering · doi:10.1007/s10439-006-9170-0 · Cited by 299
Self-citation
Metadata
- Authors
- Mason, S. G., & Birch, G. E.
- Venue
- IEEE Transactions on Neural Systems and Rehabilitation Engineering
- Published
- 2003-03
- Volume
- 11
- Issue
- 1
- Pages
- 70-85
- ISSN
- 1534-4320 (ISSN-L)
- 1558-0210
- OpenAlex
- W2122149860
- Cited by
- 331
- References
- 22
- FWCI
- 5.01
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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