QRS Detection Algorithm for Electrocardiogram Signal-IJAERD

For analysing ECG recordings QRS detection algorithms are necessary. There are many QRS detection techniques published in literature. Most of the techniques published are focus on clean clinical data. In this paper an algorithm is proposed which is suitable for both clinical ECG data and telehealth ECG data. The proposed algorithm is compared with two recently published algorithms i.e., Gutierrez-Rivas (GR) algorithm, UNSW algorithm and one standard unofficial benchmark algorithm i.e., Pan-Tompkins (PT) algorithm. This algorithms are implemented in 4 databasesMIT-BIH ARR (Arrhythmia) Data base, MIT-BIH NST (Noise Stress Test) Data Base, Telehealth Data Base, NSR Database. Sensitivity and Positive Predictivity are two parameters which are used to analyse the algorithms. Compared to previous algorithms proposed algorithm performs better sensitivity and positive predictivity. Keywords-Electrocardiogram (ECG), QRS, Telemedicine, Databases. Sensitivity, Positive Predictivity.

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