Extraction of Linear and Non-Linear Features of Electrocardiogram Signal and Classification

Sudip Deb, Sheikh Md Rabiul Islam, Fatema Tuj Johura, Xu Huang

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

5 Citations (Scopus)

Abstract

ECG signal for a private creature is totally different because of the distinctive heart structure. The ambition of feature extraction of electrocardiogram signal would permit productive detection of irregularities and economic projection due to any kind of heart confusion. Some dominant feature options are going to be extracted from ECG signals namely frequency, mean, median, skewness, kurtosis, standard deviation, different kinds of norms and so on. So, there is a need for strong and robust mathematical model to extract such helpful parameters. This research work is related to an associate degree reconciling mathematical analysis model i.e. Hilbert Huang Transform (HHT). The Hilbert-Huang transform technique is enforced to evaluate the nonlinear and non-stationary representation of the graphical signal. It is distinctive and totally disparate from the current ways of investigation and will not crave a prior function supporting information. The efficiency of the planned theme is confirmed through different classification techniques.

Original languageEnglish
Title of host publicationICEEE 2017
Subtitle of host publication2nd International Conference on Electrical and Electronic Engineering
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages1-4
Number of pages4
ISBN (Electronic)9781538633410
ISBN (Print)9781538633403
DOIs
Publication statusPublished - 27 Dec 2017
Event2nd International Conference on Electrical and Electronic Engineering, ICEEE 2017 - Rajshahi, Bangladesh
Duration: 27 Dec 201729 Dec 2017

Conference

Conference2nd International Conference on Electrical and Electronic Engineering, ICEEE 2017
Country/TerritoryBangladesh
CityRajshahi
Period27/12/1729/12/17

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