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A novel Transformer-based Anomaly Detection approach for ECG Monitoring Healthcare System
Nguyen, Thi Thuy Van; Heuchenne, Cédric; Tran, Kim Duc et al.
2023In The Seventh International Conference on Safety and Security with IoT, Edition 1
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Keywords :
Anomaly detection; Transformer; Variational autoencoder; Multivariate exponentially weighted moving average; Support vector data description; Control chart; Federated learning; Embedded artificial intelligence
Abstract :
[en] Anomaly detection plays a crucial role across various domains, including healthcare, where identifying deviations from normal patterns can help with early intervention and improved outcomes. In healthcare, such as in ECG analysis, detecting abnormal signals is essential for timely diagnosis and treatment, as it can help identify potentially life-threatening conditions that could otherwise go undetected. In this work, by focusing on ECG anomaly detection as an illustrative healthcare application, we propose to use a transformer-based variational autoencoder network together with a MEWMA-SVDD control chart to achieve anomaly detection. By employing this approach, we can effectively control the false alarm rate to minimize unnecessary alerts. Our proposed framework not only excels in terms of accuracy but also reduces the false alarm rate, making it a favorable choice compared to existing methods
Disciplines :
Computer science
Author, co-author :
Nguyen, Thi Thuy Van  ;  Université de Liège - ULiège > HEC Liège Research
Heuchenne, Cédric ;  Université de Liège - ULiège > HEC Liège : UER > UER Opérations : Statistique appliquée à la gestion et à l'économie
Tran, Kim Duc;  Dong A University, Vietnam > International Research Institute for Artificial Intelligence and Data Science
Tran, Kim Phuc;  University of Lille, France > ENSAIT, GEMTEX
Language :
English
Title :
A novel Transformer-based Anomaly Detection approach for ECG Monitoring Healthcare System
Publication date :
25 October 2023
Event name :
7th EAI International Conference on Safety and Security in Internet of Things
Event place :
Bratislava, Slovakia
Event date :
October 24-26, 2023
Audience :
International
Main work title :
The Seventh International Conference on Safety and Security with IoT, Edition 1
Publisher :
Springer, Cham
ISBN/EAN :
978-3-031-53027-2
Pages :
111–129
Peer reviewed :
Peer reviewed
Available on ORBi :
since 25 January 2024

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