Before revision:  For non-ST-elevation ECG obtained from public database, a classification tree structure comprising consecutive ECG waveforms spanning from unstable angina to healthy control is presented . Support vector machine (SVM) shows classification accuracyof 99.8\%.
After revision:  We model each beat or pulse to be a point lying on a manifold, like a surface, and use the diffusion map (DMap) to establish the relationship among those pulses. For ECG datasets, first we analyzed the non-ST-elevation ECG obtained from public database, a classification tree structure comprising consecutive ECG waveforms spanning from unstable angina to healthy control is presented . Support vector machine (SVM) shows classification accuracyof 99.8\%.