Time-frequency analysis combined with recurrence quantification for classification of onset of dementia using data from the oddball BCI paradigm-Reference-Cited by-同舟云学术

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Time-frequency analysis combined with recurrence quantification for classification of onset of dementia using data from the oddball BCI paradigm

Published:2022-11-29 Issue: Volume: Page:
ISSN:
Container-title:2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS)
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Author:

Derezinski Krystian¹,Tolpa Krzysztof²,Furman Lukasz³,Rutkowski Tomasz M.⁴,Duch Wtodzislaw³

Affiliation:

1. Nicolaus Copernicus University,Academia Rerum Socialium,Toruń,Poland,87-100

2. Nicolaus Copernicus University,Faculty of Philosophy and Social Sciences,Toruń,Poland,87-100

3. Nicolaus Copernicus University,Faculty of Physics, Astronomy and Informatics,Dept. of Informatics,Toruń,Poland,87-100

4. Cognitive Behavioral Assistive Technology Team RIKEN AIP,Tokyo,Japan,103-0027

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10001867/10001868/10001959.pdf?arnumber=10001959

Reference27 articles.

1. Understanding neurodynamical systems via Fuzzy Symbolic Dynamics

2. A spectrogram image based intelligent technique for automatic detection of autism spectrum disorder from EEG

3. Comparison of P300 responses in auditory, visual and audiovisual spatial speller BCI paradigms;chang;Proceedings of the Fifth International Brain-Computer Interface Meeting 2013 (Asilomar Conference Center Pacific Grove CA USA),2013

4. A Method for the computation of entropy in the Recurrence Quantification Analysis of categorical time series

5. Deep learning for electroencephalogram (EEG) classification tasks: a review

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