Adaptive Kalman filter approach and Butterworth filter technique for ECG signal enhancement

Bharati Sharma, Jenkin Suji, Amlan Basu

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Citations (Scopus)
117 Downloads (Pure)


About 15 million people alive today have been influenced by coronary illness. This is a major and critical issue in recent days. There are so many people have been lost their lives due to heart attack and other heart related issues. So, early on analysis and proper cure of heart disease is required to minimize the death rate due to heart disease. For better diagnosis we need exact and consistent tools for determine the fitness of human hearts to analysis the disease ahead of time before it makes around an undesirable changes in human body. For heart diagnosis one of the tools is Electrocardiogram (ECG) and the obtained signal is labeled ECG signal. This ECG signal contaminated by an amount of motion artifacts and noisy elements and deduction of these noisy elements from ECG signal must important before the ECG signal could be utilized for illness diagnosis purpose. There are various filter methods available for denoising ECG signal and select the best one on the dependence of performance parameter like signal to noise ratio (SNR) and power spectrum density (PSD).
Original languageEnglish
Title of host publicationInformation and Communication Technology for Sustainable Development
EditorsD. Mishra, M. Nayak, A. Joshi
Place of PublicationSingapore
Number of pages8
ISBN (Print)9789811039195
Publication statusPublished - 8 Nov 2017

Publication series

NameLecture Notes in Networks and Systems
ISSN (Print)2367-3370


  • electrocardiogram
  • Kalman filter
  • Butterworth filter
  • denoising
  • signal to noise ratio
  • power spectrum density


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