Exploring Frequency Band-Based Biomarkers of EEG Signals for Mild Cognitive Impairment Detection
Article
Article Title | Exploring Frequency Band-Based Biomarkers of EEG Signals for Mild Cognitive Impairment Detection |
---|---|
ERA Journal ID | 5044 |
Article Category | Article |
Authors | Tawhid, Md. Nurul Ahad, Siuly, Siuly, Kabir, Enamul and Li, Yan |
Journal Title | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
Journal Citation | 32, pp. 189-199 |
Number of Pages | 11 |
Year | 2024 |
Publisher | IEEE (Institute of Electrical and Electronics Engineers) |
Place of Publication | United States |
ISSN | 1534-4320 |
1558-0210 | |
Digital Object Identifier (DOI) | https://doi.org/10.1109/TNSRE.2023.3347032 |
Web Address (URL) | https://ieeexplore.ieee.org/document/10373947 |
Abstract | — Mild Cognitive Impairment (MCI) is often |
Keywords | CNN; deep learning; electroencephalogram (EEG); frequency sub-band; mild cognitive impairment (MCI); spectrogram |
Article Publishing Charge (APC) Funding | Researcher |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 460299. Artificial intelligence not elsewhere classified |
Byline Affiliations | University of Dhaka, Bangladesh |
Centre for Health Research | |
Victoria University | |
School of Mathematics, Physics and Computing |
https://research.usq.edu.au/item/z3wz3/exploring-frequency-band-based-biomarkers-of-eeg-signals-for-mild-cognitive-impairment-detection
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Exploring_Frequency_Band-Based_Biomarkers_of_EEG_Signals_for_Mild_Cognitive_Impairment_Detection.pdf | ||
License: CC BY 4.0 | ||
File access level: Anyone |
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