Novel automated PD detection system using aspirin pattern with EEG signals
Article
Article Title | Novel automated PD detection system using aspirin pattern with EEG signals |
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ERA Journal ID | 5040 |
Article Category | Article |
Authors | Barua, Prabal Datta, Dogan, Sengul, Tuncer, Turker, Baygin, Mehmet and Acharya, Rajendra |
Journal Title | Computers in Biology and Medicine |
Journal Citation | 137 |
Article Number | 104841 |
Number of Pages | 10 |
Year | 2021 |
Publisher | Elsevier |
Place of Publication | United Kingdom |
ISSN | 0010-4825 |
1879-0534 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.compbiomed.2021.104841 |
Web Address (URL) | ttps://www.sciencedirect.com/science/article/abs/pii/S0010482521006351 |
Abstract | Background and objective Method Results Conclusion |
Keywords | Aspirin pattern; Neighborhood component analysis ; Maximum absolute pooling ; PD detection ; EEG signal Classification |
ANZSRC Field of Research 2020 | 400306. Computational physiology |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | School of Management and Enterprise |
University of Technology Sydney | |
Firat University, Turkey | |
Ardahan University, Turkiye | |
Ngee Ann Polytechnic, Singapore | |
Asia University, Taiwan | |
Singapore University of Social Sciences (SUSS), Singapore |
https://research.usq.edu.au/item/z1v64/novel-automated-pd-detection-system-using-aspirin-pattern-with-eeg-signals
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