Medical field plays an important role in today’s world. There are various emerging needs in the field of medical science due to various factors. Malfunctioning of the heart is one of the major disorders that affect many people. This disorder can be easily detected by using Electrocardiography (ECG). The process of recording the electrical activity of the heart over a period of time is called ECG. For analysis of ECG signal several pre-processing techniques are required such as filtering, beats detection and feature extraction. When these processes are not performed effectively then there will be an inaccurate measurement of ECG signal. So, pre-processing requires an effective technique to obtain the real ECG signal, eliminating the noises present in it. In this paper, we applied Ramanujan sums and Fractional Fourier transforms to eliminate the noise in ECG signal. Comparison and detection of different artifact in ECG signal by using Adaptive filtering algorithms like LMS, NLMS, SLMS, and RLS.
Volume 11 | 04-Special Issue
Pages: 1222-1228