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Prototypical clustered federated learning for heart rate prediction
Regular Papers | Updated:2025-11-18
    • Prototypical clustered federated learning for heart rate prediction

      Enhanced Publication
    • 面向心率预测的原型聚类联邦学习
    • “In the realm of heart rate prediction, a novel framework named PCFedH has been introduced, leveraging personalized federated learning and prototypical contrastive learning to enhance privacy protection and address data heterogeneity. This approach, which includes a federated clustering module and a soft clustered federated learning module, has been proven to significantly outperform existing methods, with a notable 3.1% reduction in mean squared error across datasets. The personalization component stands out as a key contributor to the framework's success.”
    • Frontiers of Information Technology & Electronic Engineering   Vol. 26, Issue 10, Pages: 1896-1912(2025)
    • DOI:10.1631/FITEE.2500062    

      CLC: TP391
    • Received:27 January 2025,

      Revised:2025-04-06,

      Published:2025-10

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  • Yongjie YIN, Hui RUAN, Yang CHEN, et al. Prototypical clustered federated learning for heart rate prediction[J]. Frontiers of Information Technology & Electronic Engineering, 2025, 26(10): 1896-1912. DOI: 10.1631/FITEE.2500062.

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