181 / 2019-06-28 15:30:57

ECG-Signal Classification using SVM with Multi-feature

Bioelectric Signal,,Electrocardiogram,Heartbeat classification,Support vector machine (SVM)

Automated bioelectric signal analysis has an important application in the wisdom medical care. In this paper, we propose a novel approach for cardiac arrhythmia diseases classification. We designed a novel analysis framework which extract different feature transformations from ECG signals. And we trained the SVM model for multi-feature to obtain the prediction. Finally, we tested our approach on the public MIT-BIH arrhythmia database. Experiments on the datasets demonstrate our model has better classification performance than other approaches of the state-of-the-art.