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Articles Published Processes
10/10/2026 9:09:45 AM | Browse: 0 | Download: 0
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Received |
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2026-05-11 06:15 |
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Peer-Review Started |
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2026-05-11 06:17 |
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First Decision by Editorial Office Director |
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Return for Revision |
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2026-07-13 05:14 |
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Revised |
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2026-07-23 15:49 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2026-09-03 02:51 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-09-04 09:15 |
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Articles in Press |
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2026-09-04 09:15 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-09-22 09:12 |
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Publish the Manuscript Online |
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2026-10-10 09:09 |
| ISSN |
2220-3206 (online) |
| Open Access |
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc. |
| Copyright |
©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Computer Science, Artificial Intelligence |
| Manuscript Type |
Retrospective Study |
| Article Title |
FusedNeXt-based anxiety detection from electroencephalography topographic maps: A comparative analysis of alpha, beta, and theta bands
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Suheda Kaya, Gulay Tasci, İlknur Tuncer, Burak Tasci, Nursena Baygın, Irem Tasci, Mehmet Baygin, Sengul Dogan and Turker Tuncer |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Burak Tasci, Vocational School of Technical Sciences, Firat University, Cahit Arf Street, Elazig 23119, Türkiye. btasci@firat.edu.tr |
| Key Words |
Anxiety detection; Electroencephalography; FusedNeXt; Topographic map; Deep learning; Lightweight architecture; Hyper-connection; Alpha, beta and theta bands; Decision support system |
| Core Tip |
This study presents a lightweight FusedNeXt-based framework for anxiety detection using electroencephalography (EEG) topographic map images. Instead of relying on handcrafted numerical features, alpha, beta, and theta frequency bands were converted into spatial scalp maps and evaluated under the same architecture, data split, and test protocol. The theta band achieved the best overall performance, while the beta band reduced false anxiety predictions in control samples. The proposed model provides competitive accuracy with low computational cost, supporting its potential use in fast EEG-based decision-support systems. |
| Publish Date |
2026-10-10 09:09 |
| Citation |
Kaya S, Tasci G, Tuncer İ, Tasci B, Baygın N, Tasci I, Baygin M, Dogan S, Tuncer T. FusedNeXt-based anxiety detection from electroencephalography topographic maps: A comparative analysis of alpha, beta, and theta bands. World J Psychiatry 2026; 16(10): 123156
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| URL |
https://www.wjgnet.com/2220-3206/full/v16/i10/123156.htm |
| DOI |
https://doi.org/10.5498/wjp.123156 |
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