Abstract
Continuous ECG monitoring is crucial for early heart disease predictions; however, traditional data management and model training may risk the exposure of sensitive patient information. We propose a secure ECG monitoring system by integrating federated learning with blockchain technology. A mobile app helps patients monitor their heart condition and the doctors provide feedback, all connected through a private blockchain server. In addition, Federated learning allows secure and scalable ECG classification model training across a large number of patient devices. In our simulated experiment, the federated learning system managed up to 500 clients, which demonstrated its capability to handle large amounts of clients.
Recommended Citation
Nijhum, Ifran Rahman; Sarker, Md Rabiul Ali; Mahmud, Hasib; and Rahman, Tanzilur, "Scalable and Secure ECG Monitoring System Using Federated Learning and Blockchain" (2025). CAPSI 2025 Proceedings. 36.
https://aisel.aisnet.org/capsi2025/36