High Frequency Noise Removal From Electrocardiogram Using Fir Low Pass Filter Bassed On Window Technique
Journal Title: International Journal of engineering Research and Applications - Year 2018, Vol 8, Issue 1
Abstract
ECG Signal is widely used for detection and diagnosis of various heart related diseases. Feature extraction through ECG is a new application that is rapidly growing these days. While acquiring ECG signal, it gets contaminated to a number of sources with various type of artifacts such as baseline wander interference, motion artifacts, instrumentation noise, electrode contact noise, EMG noise etc. In this research work, different window technique to remove noise in corrupted ECG signal has been analyzed through this model. The windows used are Kaiser, Rectangular, Hanning, Hamming and Blackman Window. The output was analyzed and compared using SNR and MSE. This research work gives an optimal ECG noise removal windowing system that concludes which particular window should be applied for a better denoised signal and better SNR and MSE. Thus, this research concludes that Hamming Window followed by Rectangular Window gives better SNR. Kaiser Window followed by Hanning Window gives better MSE than others. Moreover, all the windows have been optimized for best sampling rate.
Authors and Affiliations
Manakdeep Kaur, Sangeet Pal Kaur
Keywords
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