A New Approach of Noise Elimination Methodology for ECG Signal

Jannatul Robaiat Mou, Sheikh Md. Rabiul Islam, Xu HUANG, Keng Liang Ou

Research output: A Conference proceeding or a Chapter in BookConference contribution

Abstract

ECG machines are usually used for medical diagnosis of heart activities of human body now days. It has created different types of noise and interference based on
interfaces between ECG machines and human body. It can change the real amplitude and duration of the signal. In this paper we improved moving average filter and proposed moving average weighted window filter. We have also proposed an algorithm based on forward difference quotient and threshold for noise elimination of ECG signal. The numerical value of different performance
parameters such as 23dB of SNR, lower of MSE, and approximately 1 of correlation is provide better clarification of simulation results than others and prove the robustness of the algorithms.
Original languageEnglish
Title of host publicationInternational Conference on Electrical, Computer and Communication Engineering (ECCE 2017)
EditorsMohammad Shamsul Arefin
Place of PublicationTaiwan
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages921-927
Number of pages7
ISBN (Electronic)9781509056279
ISBN (Print)9781509056286
DOIs
Publication statusPublished - 16 Feb 2017
EventInternational Conference on Electrical, Computer and Communication Engineering (ECCE) - Bangladesh, Bangladesh, Bangladesh
Duration: 16 Feb 201718 Feb 2017

Conference

ConferenceInternational Conference on Electrical, Computer and Communication Engineering (ECCE)
Abbreviated titleECCE 2017
CountryBangladesh
CityBangladesh
Period16/02/1718/02/17

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  • Cite this

    Mou, J. R., Islam, S. M. R., HUANG, X., & Ou, K. L. (2017). A New Approach of Noise Elimination Methodology for ECG Signal. In M. S. Arefin (Ed.), International Conference on Electrical, Computer and Communication Engineering (ECCE 2017) (pp. 921-927). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ECACE.2017.7913035