Non-Gaussianity Detection of EEG Signals Based on a Multivariate Scale Mixture Model for Diagnosis of Epileptic Seizures Article Swipe
Akira Furui
,
Ryota Onishi
,
Akihito Takeuchi
,
Tomoyuki Akiyama
,
Toshio Tsuji
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1109/tbme.2020.3006246
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1109/tbme.2020.3006246
The stochastic fluctuations of EEG quantified by the proposed model can help detect epileptic seizures with high accuracy.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/tbme.2020.3006246
- OA Status
- green
- Cited By
- 32
- References
- 40
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3038515764
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3038515764Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1109/tbme.2020.3006246Digital Object Identifier
- Title
-
Non-Gaussianity Detection of EEG Signals Based on a Multivariate Scale Mixture Model for Diagnosis of Epileptic SeizuresWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-07-01Full publication date if available
- Authors
-
Akira Furui, Ryota Onishi, Akihito Takeuchi, Tomoyuki Akiyama, Toshio TsujiList of authors in order
- Landing page
-
https://doi.org/10.1109/tbme.2020.3006246Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2007.00898Direct OA link when available
- Concepts
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Electroencephalography, Pattern recognition (psychology), Epilepsy, Feature (linguistics), Computer science, Artificial intelligence, Multivariate statistics, Receiver operating characteristic, Psychology, Machine learning, Neuroscience, Philosophy, LinguisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
32Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 5, 2024: 9, 2023: 7, 2022: 6, 2021: 5Per-year citation counts (last 5 years)
- References (count)
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40Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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