Sudden cardiac death (SCD) is a major health concern. In time domain, detection of such condition involving monitoring the 24-h ambulatory ECG is a big issue. Here, the presented work describes higher order spectral analysis carried out on the normal portion of SCD-ECG and the analyzed parameters are compared with that of healthy person ECG. The developed algorithm detects the chances of myocardial infarction in prior, on the basis of higher order spectral analysis of an SCD-ECG. Specifically, quadratic phase coupling techniques are applied on QRS complex to extract information from the SCD-ECG signal providing the basis with which a signal suggesting predisposition of the patient to suffer a cardiac arrest can be differentiated from a normal ECG signal. The algorithm requires short segments of ECG to detect the possibility of SCD. The proposed algorithm is tested on MIT-BIH database signals and the results obtained established that it is possible to analyze and predict whether an individual is susceptible to cardiac arrest or not. Certain parameters like energy are evaluated and analyzed from the normal portion of QRS complex of SCD-ECG and are compared with that of the healthy person ECG. This primitive idea can extend the research aspect in view of analyzing the ECG signal to identify the predisposition to other cardiac diseases.