Identification of sudden cardiac death using spectral domain analysis of Electrocardiogram(ECG)

Sudden death from cardiac arrest is a major health problem and is responsible for almost half of all heart disease deaths. This paper introduces work that has been done to distinguish the Electrocardiogram (ECG) of a normal healthy human from that of a patient who may suffer from Sudden Cardiac Death (SCD), but this condition has not been detected. In SCD, the cardiac arrest occurs for a very short time which is preceded and followed by normal ECG. In time domain, detection of such condition would involve monitoring the ECG for over 24 hrs which is not at all feasible. Therefore we worked on normal portion of SCD ECG and compared its parameters with those of a healthy person's ECG. The intention is to design an algorithm that may enable doctors to detect chances of myocardial infarction beforehand on the basis of spectral analysis of an ECG. Fast Fourier Transform (FFT) on QRS complex was used to extract information from the ECG signals providing the basis with which a signal suggesting predisposition of the patient to suffer a cardiac arrest can be differentiated from a normal signal. In this way, instead of waiting for over 24 hrs, 4-5 min. of ECG of any patient is enough to detect possibility of SCD. The algorithm was tested on MIT-BIH (Massachusetts Institute of Technology- Beth Israel Hospital) Databases and the results verified our hypothesis that given an individual's ECG signal during normal function of the heart, it is possible to analyze it and predict whether he is susceptible to cardiac arrest. Further research is being carried out by utilizing the concept for analyzing an ECG signal to identify predisposition to other diseases.