Features Extraction Technique for ECG Recording Paper

Generally the ECG is recorded on a thermal paper which cannot be stored for a long time, because thermal trace over time becomes erased gradually. However some hospitals are saving the ECG thermal papers as scanning images in the electronic equipments (like computers) to maintain medical records,...

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Main Authors:	Khleaf, Hussain Kareem, Kamarul Hawari, Ghazali, Abdalla, Ahmed N.
Format:	Conference or Workshop Item
Language:	English
Published:	2013
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/5954/ http://umpir.ump.edu.my/id/eprint/5954/ http://umpir.ump.edu.my/id/eprint/5954/1/Features_extraction_technique_for_ECG_recording_paper.pdf

id	ump-5954
recordtype	eprints
spelling	ump-59542018-10-03T07:36:57Z http://umpir.ump.edu.my/id/eprint/5954/ Features Extraction Technique for ECG Recording Paper Khleaf, Hussain Kareem Kamarul Hawari, Ghazali Abdalla, Ahmed N. TK Electrical engineering. Electronics Nuclear engineering Generally the ECG is recorded on a thermal paper which cannot be stored for a long time, because thermal trace over time becomes erased gradually. However some hospitals are saving the ECG thermal papers as scanning images in the electronic equipments (like computers) to maintain medical records, but this method needs to high memory capacity, and use less scanning resolution that gives signal accuracy is less at preview. In this paper image processing techniques are developed for an electrocardiogram (ECG) feature extraction and signal regeneration as a digital time series signal. The 12-lead ECG signals extracted from the recording paper and converting it to a digital time series signals. Feature extraction and the digital time series signal were tested on 30 of 12-lead ECG paper records from the MIT-BIH arrhythmia database, and the accuracy was between 96.31% and 98.25%. In addition this techniques also can be used for features extraction to perform an automatic heart disease classification using one of the artificial intelligence methods. 2013 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/5954/1/Features_extraction_technique_for_ECG_recording_paper.pdf Khleaf, Hussain Kareem and Kamarul Hawari, Ghazali and Abdalla, Ahmed N. (2013) Features Extraction Technique for ECG Recording Paper. In: Proceedings of International Conference on Artificial Intelligence in Computer Science and ICT (AICS 2013), 25 - 26 November 2013 , Bayview Hotel, Langkawi, Malaysia. pp. 1-6.. http://worldconferences.net/proceedings/aics2013/toc/papers_aics2013/A065%20-%20HUSSAIN%20K.%20KHLEAF%20-%20Features%20Extraction%20Technique%20for%20ECG%20recording%20Paper.pdf
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Khleaf, Hussain Kareem Kamarul Hawari, Ghazali Abdalla, Ahmed N. Features Extraction Technique for ECG Recording Paper
description	Generally the ECG is recorded on a thermal paper which cannot be stored for a long time, because thermal trace over time becomes erased gradually. However some hospitals are saving the ECG thermal papers as scanning images in the electronic equipments (like computers) to maintain medical records, but this method needs to high memory capacity, and use less scanning resolution that gives signal accuracy is less at preview. In this paper image processing techniques are developed for an electrocardiogram (ECG) feature extraction and signal regeneration as a digital time series signal. The 12-lead ECG signals extracted from the recording paper and converting it to a digital time series signals. Feature extraction and the digital time series signal were tested on 30 of 12-lead ECG paper records from the MIT-BIH arrhythmia database, and the accuracy was between 96.31% and 98.25%. In addition this techniques also can be used for features extraction to perform an automatic heart disease classification using one of the artificial intelligence methods.
format	Conference or Workshop Item
author	Khleaf, Hussain Kareem Kamarul Hawari, Ghazali Abdalla, Ahmed N.
author_facet	Khleaf, Hussain Kareem Kamarul Hawari, Ghazali Abdalla, Ahmed N.
author_sort	Khleaf, Hussain Kareem
title	Features Extraction Technique for ECG Recording Paper
title_short	Features Extraction Technique for ECG Recording Paper
title_full	Features Extraction Technique for ECG Recording Paper
title_fullStr	Features Extraction Technique for ECG Recording Paper
title_full_unstemmed	Features Extraction Technique for ECG Recording Paper
title_sort	features extraction technique for ecg recording paper
publishDate	2013
url	http://umpir.ump.edu.my/id/eprint/5954/ http://umpir.ump.edu.my/id/eprint/5954/ http://umpir.ump.edu.my/id/eprint/5954/1/Features_extraction_technique_for_ECG_recording_paper.pdf
first_indexed	2023-09-18T22:01:25Z
last_indexed	2023-09-18T22:01:25Z
_version_	1777414423442358272

Features Extraction Technique for ECG Recording Paper

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