Real-Time Concept Drift Detection and Its Application to ECG Data

International Journal of Online and Biomedical Engineering

Swati Shinde¹  Ketan Sanjay Desale¹ 

[1] Pimpri Chinchwad College of Engineering;

关键词: concept drift;    electrocardiogram signal;    drift detection method;    data streams;   

DOI  :  10.3991/ijoe.v17i10.25473

来源: DOAJ

【 摘 要 】

Prediction of cardiac disease is one the most crucial topics in the sector of medical info evaluation. The stochastic nature and the variation concerning time in electrocardiogram (ECG) signals make it burdensome to investigate its characteristics. Being evolving in nature, it requires a dynamic predictive model. With the presence of concept drift, the model performance will get worse. Thus learning algorithms require an apt adaptive mechanism to accurately handle the drifting data streams. This paper proposes an inceptive approach, Corazon Concept Drift Detection Method (Corazon CDDM), to detect drifts and adapt to them in real-time in electrocardiogram signals. The proposed methodology results in achieving competitive results compared to the methods proposed in the literature for all types of datasets like synthetic, real-world & time-series datasets.

【 授权许可】

Unknown