Statistical analysis of cross-correlation index for identifying abnormal ECG signals

In this study, we propose conducting a statistical analysis on the cross-correlation index of a given electrocardiogram (ECG) signal to swiftly ascertain whether the signal corresponds to a healthy heart. This information serves as a rapid triage for patients presenting with chest pain, facilitating the prompt exclusion of the possibility of a heart disease. The results illustrate that the proposed algorithm adeptly classified as much as 80% of the normal signals alongside up to 85% of the abnormal signals under specific parameter configurations. This indicates its effectiveness in detecting the presence of abnormal signals.