ECG disease detection & feature extraction by wavelet transformation

This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2016.

Bibliographic Details
Main Authors:	Imam, Saif, Tabassum, Tasbiha, ZarinIrtiza
Other Authors:	Ali, Md. Haider
Format:	Thesis
Language:	English
Published:	BRAC University 2016
Subjects:	Computer science and engineering Wavelet transformation
Online Access:	http://hdl.handle.net/10361/5417

id	10361-5417
record_format	dspace
spelling	10361-54172022-01-26T10:21:50Z ECG disease detection & feature extraction by wavelet transformation Imam, Saif Tabassum, Tasbiha ZarinIrtiza Ali, Md. Haider Department of Computer Science and Engineering, BRAC University Computer science and engineering Wavelet transformation This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2016. Cataloged from PDF version of thesis report. Includes bibliographical references (page 22-23). ECG is the most common and basic test to run on patients to check any kind of anomalies in the heart. In the ECG result 10 to 20 minutes long continuous data of a patient’s heart is down sampled and printed as a 1D graph. We have develop a program which will take the continuous dataset from the ECG machine and analyses the data and extracts various features of the ECG wave. At first we decompose the data using Wavelet decomposition. Then the data is reconstructed in 4 levels which removes the noise from the signal. In the same time we detect major components of the ECG wave which is P wave, QRS complex and T wave. Then we calculate ST deviation, heart rate and extract other features such as location and amplitude of each waves in order to detect anomalies. Finally our output provides the heart status (healthy, if any disease found, if any major or minor risk) in a language that the patient can understand and also some detailed wave properties in medical term for the doctors. Saif Imam TasbihaTabassum ZarinIrtiza B. Computer Science and Engineering 2016-05-31T11:23:39Z 2016-05-31T11:23:39Z 2016 2016-03 Thesis ID 16101122 ID 12101087 ID 11101070 http://hdl.handle.net/10361/5417 en BRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 39 pages application/pdf BRAC University
institution	Brac University
collection	Institutional Repository
language	English
topic	Computer science and engineering Wavelet transformation
spellingShingle	Computer science and engineering Wavelet transformation Imam, Saif Tabassum, Tasbiha ZarinIrtiza ECG disease detection & feature extraction by wavelet transformation
description	This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2016.
author2	Ali, Md. Haider
author_facet	Ali, Md. Haider Imam, Saif Tabassum, Tasbiha ZarinIrtiza
format	Thesis
author	Imam, Saif Tabassum, Tasbiha ZarinIrtiza
author_sort	Imam, Saif
title	ECG disease detection & feature extraction by wavelet transformation
title_short	ECG disease detection & feature extraction by wavelet transformation
title_full	ECG disease detection & feature extraction by wavelet transformation
title_fullStr	ECG disease detection & feature extraction by wavelet transformation
title_full_unstemmed	ECG disease detection & feature extraction by wavelet transformation
title_sort	ecg disease detection & feature extraction by wavelet transformation
publisher	BRAC University
publishDate	2016
url	http://hdl.handle.net/10361/5417
work_keys_str_mv	AT imamsaif ecgdiseasedetectionfeatureextractionbywavelettransformation AT tabassumtasbiha ecgdiseasedetectionfeatureextractionbywavelettransformation AT zarinirtiza ecgdiseasedetectionfeatureextractionbywavelettransformation
_version_	1814309610182410240

ECG disease detection & feature extraction by wavelet transformation

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