A novel Transformer-based Anomaly Detection approach for ECG Monitoring Healthcare System

Nguyen, Thi Thuy Van; Heuchenne, Cédric; Tran, Kim Duc; Tran, Kim Phuc

doi:10.1007/978-3-031-53028-9_7

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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.

2024 • In The Seventh International Conference on Safety and Security with IoT, Edition 1

Peer reviewed Dataset

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https://hdl.handle.net/2268/311904

DOI
10.1007/978-3-031-53028-9_7

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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 : UER > UER Opérations

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 :

05 January 2024

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

Additional URL :

https://link.springer.com/chapter/10.1007/978-3-031-53028-9_7

Data Set :

https://doi.org/10.1007/978-3-031-53028-9_7

Available on ORBi :

since 25 January 2024

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