QRS Detection Algorithm for Electrocardiogram Signal

Authors

  • V. Phalguna Kumar PG Scholar, Department of Electronics and communication, G. Pulla Reddy Engineering College (Autonomous), Kurnool-518007, Andhra Pradesh, India.
  • G. Amjad Khan Assistant professor, Department of Electronics and communication, G. Pulla Reddy Engineering College (Autonomous), Kurnool-518007, Andhra Pradesh, India.

Keywords:

Electrocardiogram (ECG), QRS, Telemedicine, Databases. Sensitivity, Positive Predictivity

Abstract

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.

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Published

2017-08-25

How to Cite

V. Phalguna Kumar, & G. Amjad Khan. (2017). QRS Detection Algorithm for Electrocardiogram Signal. International Journal of Advance Engineering and Research Development (IJAERD), 4(8), 357–363. Retrieved from https://ijaerd.org/index.php/IJAERD/article/view/3501

Issue

Vol. 4 No. 8 (2017): Volume 4 Issue 8 AUGUST 2017

Section

Articles