Review and Comparison of QRS Detection Algorithms for Arrhythmia Diagnosis

The electrocardiogram is the graphical representation of the bio potential generated by the movement of the heart and is used to diagnose different types of heart diseases. The main purpose is to compute Heart Rate and RR interval using QRS complex detection algorithm. Several algorithms for QRS complex detection have been discussed on the basis of pre-processing and decision making stages. Evaluation of these algorithms is supported on the basis of different performance parameters such as sensitivity and positive predictive rate. After reviewing different papers, authors came across Entropy based wavelet transform, which gives better performance for QRS detection. The implementation of an existing algorithm on different ECG databases is done. Further QRS based heart diseases were discussed based on Heart Rate and RR intervals.