Title :
Review: Comparison of QRS detection algorithms
Author :
Saraswat, Shipra ; Srivastava, Geetika ; Shukla, Sachchidanand
Author_Institution :
ASET, Amity Univ., Lucknow, India
Abstract :
An Electrocardiogram (ECG) is graphical representation of the electrical movement of human heart and used in diagnosis of various heart diseases. The primary function of ECG analysis is correct detection of QRS complex and other ECG characteristics [1]. In this review paper, researchers provide a comparative study between four popular algorithms: namely Window pair algorithm, Dynamic Plosion Index algorithm, KNN algorithm, Slope vector waveform algorithm [2-5] against three assessment criteria 1) Cross Validation, 2) Threshold and 3) Robustness to noise in order to obtain a fast, robust and highly accurate QRS detection algorithm which helps in the development of a more robust clinical instrument by making the front end signal processing more effective [6].
Keywords :
diseases; electrocardiography; medical signal detection; signal representation; ECG analysis; KNN algorithm; QRS detection algorithm comparison; cross validation; dynamic plosion index algorithm; electrocardiogram; front end signal processing; heart disease diagnosis; human heart electrical movement graphical representation; noise robustness; slope vector waveform algorithm; threshold; window pair algorithm; Automation; Electrocardiography; Heuristic algorithms; Indexes; Noise; Signal processing algorithms; Software algorithms; DPI; ECG; KNN; QRS; Slope Vector; Windowpair;
Conference_Titel :
Computing, Communication & Automation (ICCCA), 2015 International Conference on
Conference_Location :
Noida
Print_ISBN :
978-1-4799-8889-1
DOI :
10.1109/CCAA.2015.7148443