Chapter 20 An Approach for Detecting Heart Rate Analyzing QRS Complex in Noise and Saturation Filtered ECG Signal Sanjana Khan Shammi, Faysal Bin Hasan, and Jia Uddin 1 Introduction QRS complexes and ventricular beats in an electrocardiogram represent the depo- larization phenomenon of the ventricles and yield useful information about their behavior [1]. Beat detection is a procedure preceding any kind of ECG processing and analysis. For morphological analysis, this is the reference for the detection of other ECG waves and parameters. This process analysis requires the classification of QRS and other ventricular beat complexes as normal and abnormal. Real-time ven- tricular beat detection is essential for monitoring of patients in critical heart condition [2, 3]. Since it reflects the electrical activity within the heart during the ventricular contraction, the time of its occurrence, as well as its shape, provides much information about the current state of the heart. In ECG QRS heartbeat experiment, it is observed that abnormalities of the left heart, abnormalities of the right heart, and abnormali- ties of the atria with an abnormally fast rates or abnormally slow rates (bradycardia and conduction blocks) cause the heart attacks. As QRS is the most essential part of this topic, we considered two parameters for our experimental approach—ECG heartbeat rate and QRS peak measurement. This approaches guided us to find peaks with efficiency and calculate heartbeat rate from noisy signal. The rest of the paper is organized as follows. Section 2 shows the literature review on related works. Section 3 describes the proposed QRS detection methodology, and S. K. Shammi · F. Bin Hasan Department of Computer Science and Engineering, Brac University, 66 Mohakhali, Dhaka 1212, Bangladesh e-mail: shammisanjana@gmail.com F. Bin Hasan e-mail: mahinhasan56@gmail.com J. Uddin (B ) Department of Technology Studies, Woosong University, Daejeon, South Korea e-mail: jia.uddin@wsu.ac.kr © Springer Nature Singapore Pte Ltd. 2020 M. S. Uddin and J. C. Bansal (eds.), Proceedings of International Joint Conference on Computational Intelligence, Algorithms for Intelligent Systems, https://doi.org/10.1007/978-981-15-3607-6_20 253