Copyright © 2018 Authors. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. International Journal of Engineering & Technology, 7 (4.12) (2018) 1-5 International Journal of Engineering & Technology Website: www.sciencepubco.com/index.php/IJET Research paper Denoising of Ecg Signals Using Fir & Iir Filter: a Performance Analysis Dr. Chhavi Saxena 1 *, Dr. Avinash Sharma 2 Dr. Rahul Srivastav 3 , Dr. Hemant Kumar Gupta 4 1 Arya College of Engineering & I.T. Jaipur, Rajasthan, India 2 Maharishi Markandeshwar University, Ambala, Haryana 3 Arya College of Engineering & I.T. Jaipur, Rajasthan, India 4 Poornima College of Engineering, Jaipur, Rajasthan, India *Corresponding author E-mail:chhavisaxena_81@rediffmail.com, asharma Abstract Electrocardiogram (ECG) signal is the electrical recording of coronary heart activity. It is a common routine and vital cardiac diagnostic tool in which in electric signals are measured and recorded to recognize the practical status of heart, but ECG signal can be distorted with noise as, numerous artifacts corrupt the unique ECG signal and decreases it quality. Consequently, there may be a need to eliminate such artifacts from the authentic signal and enhance its quality for better interpretation. ECG signals are very low frequency signals of approx- imately 0.5Hz-100Hz and digital filters are used as efficient approach for noise removal of such low frequency signals. Noise may be any interference because of movement artifacts or due to power device that are present wherein ECG has been taken. Consequently, ECG signal processing has emerged as a common and effective tool for research and clinical practices. This paper gives the comparative eval- uation of FIR and IIR filters and their performances from the ECG signal for proper understanding and display of the ECG signal. Keywords: Baseline Noise; ECG; FIR Filter; IIR Filter; Noise. 1. Introduction Heart associated illnesses are a few of the essential causes of hu- man deaths everywhere in the world. Therefore, to apprehend the physiological and practical fame of heart, an efficient tools and techniques for effective prognosis of the cardiac ailment are need- ed. Electrocardiography (ECG) is a tool extensively used to ap- prehend the condition of the heart. Now-a-days, computerized ECG evaluation is considered as a primary and reliable technique for the prognosis of cardiac related illnesses. The ECG recordings received by means of setting electrodes on the subject’s chest and limbs get contaminated with specific kinds of artifacts which in- cludes power line interference, Baseline drift, movement artifacts, Electrode contact noise, Instrumentation noise because of elec- tronic gadgets, amongst unique noises, the noise from electric power device is a prime source of noise throughout the recording or monitoring of ECG. Exclusive noises have unique frequencies; the noise with low frequency creates problem with ECG signal and a while high frequency noises additionally interfere ECG i.e. cellular smartphone. The frequency is measured in cycle/second or in "Hertz". As an instance the electric power utilized in daily life is 50 Hz in India [3]. In this paper, the principle aim is to eliminate the noises of the electrocardiogram (ECG) using FIR and IIR fil- ters. Because of Baseline noise interference, it becomes hard to research the ECG records either manually or by way of automatic means. 2. Digital Filters Digital filter is a mathematical algorithm implemented in hard ware and software. Digital input signal is produce a digital output signal for purpose of achieving a filter objec- tive. A digital filter is used for two general purposes: (i) Separation of signal that have been combined and (ii) resto- rations of signal that have been distorted in some way sig- nal separations needed when signal has been contaminated with interference, noise, or other signal. Filters may be:  Linear or non-linear.  Time-invariant or time-variant.  Causal or non-causal.  Analog or Digital.  Discrete-time (sampled) or continuous-time.  Passive or active type of continuous-time filter  Infinite impulse response (IIR) or finite impulse re- sponse (FIR) type of discrete-time or digital filter. 3. Methodology Filter can be implemented either in software as a program, or hardware as a circuit. For our simulation purpose, MATLAB is necessary and effective software to attain the convincible results. MATLAB has some advantages compared with conventional computer languages for technical problem solving. Among them are following [6].