Estimating and approaching the maximum information rate of noninvasive visual brain-computer interface Article Swipe
Nanlin Shi
,
Yining Miao
,
Changxing Huang
,
Xiang Li
,
Yonghao Song
,
Xiaogang Chen
,
Yijun Wang
,
Xiaorong Gao
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.neuroimage.2024.120548
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.neuroimage.2024.120548
An essential priority of visual brain-computer interfaces (BCIs) is to enhance the information transfer rate (ITR) to achieve high-speed communication. Despite notable progress, noninvasive visual BCIs have encountered a plateau in ITRs, leaving it uncertain whether higher ITRs are achievable. In this study, we used information theory to study the characteristics and capacity of the visual-evoked channel, which leads us to investigate whether and how we can decode higher information rates in a visual BCI system. Using information theory, we estimate the upper and lower bounds of the information rate with the white noise (WN) stimulus. Consequently, we found out that the information rate is determined by the signal-to-noise ratio (SNR) in the frequency domain, which reflects the spectrum resources of the channel. Based on this discovery, we propose a broadband WN BCI by implementing stimuli on a broader frequency band than the steady-state visual evoked potentials (SSVEPs)-based BCI. Through validation, the broadband BCI outperforms the SSVEP BCI by an impressive 7 bps, setting a record of 50 bps. The integration of information theory and the decoding analysis presented in this study offers valuable insights applicable to general sensory-evoked BCIs, providing a potential direction of next-generation human-machine interaction systems.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.neuroimage.2024.120548
- OA Status
- gold
- Cited By
- 19
- References
- 59
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4391928533
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4391928533Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1016/j.neuroimage.2024.120548Digital Object Identifier
- Title
-
Estimating and approaching the maximum information rate of noninvasive visual brain-computer interfaceWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-02-19Full publication date if available
- Authors
-
Nanlin Shi, Yining Miao, Changxing Huang, Xiang Li, Yonghao Song, Xiaogang Chen, Yijun Wang, Xiaorong GaoList of authors in order
- Landing page
-
https://doi.org/10.1016/j.neuroimage.2024.120548Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1016/j.neuroimage.2024.120548Direct OA link when available
- Concepts
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Computer science, Interface (matter), Brain–computer interface, Human–computer interaction, Artificial intelligence, Neuroscience, Psychology, Operating system, Electroencephalography, Bubble, Maximum bubble pressure methodTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
19Total citation count in OpenAlex
- Citations by year (recent)
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2025: 15, 2024: 4Per-year citation counts (last 5 years)
- References (count)
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59Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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