QRS Detection for Heart Rate Monitoring

Abstract

Fast and efficient QRS detection algorithm is a essential prerequisite for analyzing disease related to heart. A study and analysis of first differentiation based QRS detection method, first and second differentiation based QRS detection method and High speed QRS detection method (Hamilton and Tompkins) was done. Algorithms based on differentiation method of QRS detection are efficient as far as computation is concerned. This method can be used for real time analysis of large data set. On a standard data set first differentiation method has highest detection accuracy but also the largest time error (Average time error is 12.05ms). For the first and second differentiation based QRS detection method sensitivity and positive predictivity are 96.4 and 97.7, data error rate is 4.64 and Average Time error is 7.26ms.For the third method sensitivity and positive predictivity is 100 percent and data error rate is zero. Average time error is 9.13ms and is having better performance as compared to differentiation based methods.