A novel technique for cardiac arrhythmia classification using spectral correlation and support vector machines
作者：
Highlights：
• A method for arrhythmia classification based on spectral correlation is proposed.
• Statistical features for the spectral correlation coefficients were calculated.
• Features were subjected to principal component analysis and fisher score.
• Raw spectral correlation data, PCA data and FS data were classified using SVM.
• The best performance is achieved using raw spectral correlation data.
摘要
•A method for arrhythmia classification based on spectral correlation is proposed.•Statistical features for the spectral correlation coefficients were calculated.•Features were subjected to principal component analysis and fisher score.•Raw spectral correlation data, PCA data and FS data were classified using SVM.•The best performance is achieved using raw spectral correlation data.
论文关键词：Electrocardiogram,Arrhythmia,Spectral correlation,Support vector machine,Classification
论文评审过程：Available online 30 June 2015, Version of Record 6 August 2015.
论文官网地址：https://doi.org/10.1016/j.eswa.2015.06.046
