Automated anxiety detection using probabilistic binary pattern with ECG signals
Article
Article Title | Automated anxiety detection using probabilistic binary pattern with ECG signals |
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ERA Journal ID | 5039 |
Article Category | Article |
Authors | Baygin, Mehmet, Barua, Prabal Datta, Dogan, Sengul, Tuncer, Turker, Hong, Tan Jen, March, Sonja, Tan, Ru-San, Molinari, Filippo and Acharya, U. Rajendra |
Journal Title | Computer Methods and Programs in Biomedicine |
Journal Citation | 247 |
Article Number | 108076 |
Number of Pages | 12 |
Year | 2024 |
Publisher | Elsevier |
Place of Publication | Ireland |
ISSN | 0169-2607 |
1872-7565 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.cmpb.2024.108076 |
Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S0169260724000725 |
Abstract | Background and aim Materials and methods Results Conclusions |
Keywords | combinational majority voting; Probabilistic binary pattern ; ECG-based mood detection ; ECG signal classification ; Feature engineering |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 420313. Mental health services |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Erzurum Technical University, Turkey |
School of Business | |
Firat University, Turkey | |
Singapore General Hospital, Singapore | |
Centre for Health Research | |
School of Psychology and Wellbeing | |
National Heart Centre, Singapore | |
Duke-NUS Medical School, Singapore | |
PoliToBIOMed Lab, Italy | |
School of Mathematics, Physics and Computing |
https://research.usq.edu.au/item/z5q9x/automated-anxiety-detection-using-probabilistic-binary-pattern-with-ecg-signals
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