A novel algorithm for sudden cardiac death risk estimation using Lab VIEW

The need for quick diagnosis of cardiac abnormalities cannot be underestimated. Sudden cardiac death (SCD) is one such disease that needs immediate attention as it is fatal and is a leading cause of cardiovascular mortality. Most of the cardiovascular aberrations are due to irregular heart rhythm resulting in abnormal PQRST values which can be traced from the patient´s ECG. ECG is a simple, non-invasive test that records the heart´s electrical activity. This is used to detect and locate the sources of severe heart problems such as SCD. This project is aimed at developing novel algorithms to estimate the risk of sudden cardiac death using ECG analysis. The developed algorithms improve the best results reported in other papers using different algorithms evaluated on the same database[1]. ECG signals from MIT BIH database are used to validate the algorithm. The proposed system integrates two separate modules: SCD detection and SCD prediction. The preprocessing of ECG signals is done using Fast Fourier Transform (FFT) as the first step since the signals are subjected to various artifacts and noise. Then the detection of the abnormalities is taken up. The implementation is done using Lab VIEW which is a versatile graphical programming tool for real-time systems design simulation and virtual instrumentation. After having formulated a robust algorithm and a reliable solution for SCD detection the work will be extended towards predicting SCD with reasonable accuracy.