FADE: Forecasting for anomaly detection on ECG
Our proposed approach exhibited superior performance in the early detection of cardiac anomalies in ECG signals, surpassing previous methods that predominantly identify a limited range of anomalies. FADE effectively detects both abnormal heartbeats and arrhythmias, offering significant advantages in healthcare through cost reduction, facilitation of remote monitoring, and efficient processing of large-scale ECG data.
Authors
- Paula Ruiz-Barroso (ORCID: https://orcid.org/0000-0003-0731-1074)
- Denisa-Andreea Constantinescu (ORCID: https://orcid.org/0000-0001-6736-5715)
- Nicolás Guil (ORCID: https://orcid.org/0000-0003-3431-6516)
- Francisco M. Castro (ORCID: https://orcid.org/0000-0002-7340-4976)
- José Miranda (ORCID: https://orcid.org/0000-0002-7275-4616)
- David Atienza (ORCID: https://orcid.org/0000-0001-9536-4947)
Institutions
- École Polytechnique Fédérale de Lausanne (CH)
- Universidad de Málaga (ES)
Publication Details
- Journal
- Computer Methods and Programs in Biomedicine
- Published
- 2025-04-22
- DOI
- https://doi.org/10.1016/j.cmpb.2025.108780
- Citations
- 5
- Primary Topic
- ECG Monitoring and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 6.94