Determination of the onset of ventricular tachycardia
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| Format: | Working Paper |
| Language: | en |
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Institute of Electrical and Electronics Engineers (IEEE)
2012
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| Online Access: | http://dspace.unimap.edu.my/123456789/20573 |
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| _version_ | 1831786596754522112 |
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| author | Mohd Afzan, Othman Norlaili, Mat Safri Sinan S., Mohammed Sheet |
| author2 | norlaili@fke.utm.my |
| author_facet | norlaili@fke.utm.my Mohd Afzan, Othman Norlaili, Mat Safri Sinan S., Mohammed Sheet |
| author_sort | Mohd Afzan, Othman |
| building | UniMAP Library |
| collection | Institutional Repository |
| content_provider | Universiti Malaysia Perlis |
| content_source | UniMAP Library Digital Repository |
| continent | Asia |
| country | Malaysia |
| description | Link to publisher's homepage at http://ieeexplore.ieee.org/ |
| format | Working Paper |
| id | my.unimap-20573 |
| institution | Universiti Malaysia Perlis |
| language | en |
| publishDate | 2012 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | my.unimap-205732012-08-03T06:06:56Z Determination of the onset of ventricular tachycardia Mohd Afzan, Othman Norlaili, Mat Safri Sinan S., Mohammed Sheet norlaili@fke.utm.my Ventricular tachycardia Electrocardiogram Semantic mining Heart disease Link to publisher's homepage at http://ieeexplore.ieee.org/ Ventricular tachycardia is ventricular cardiac arrhythmia that could be calamitous and life threatening. The ability to provide accurate and well-timed predictions of ventricular tachycardia events can save lives. This research investigates the possibility of using a semantic mining algorithm to predict the onset of ventricular tachycardia in electrocardiogram (ECG) signals. A total of thirteen subjects were obtained from Creighton University Ventricular Tachyarrhythmia Database and MIT-BIH Arrhythmia Database. Based on these downloaded data, damping ratios, natural frequencies and input parameters were extracted using semantic mining algorithm. The data were segmented into ten sec periods before applying them to semantic mining. It was found that extracted parameters from the semantic mining were successful in forecasting ventricular tachycardia one to four minutes earlier than the onset. In brief, this work provides a new method for advanced researches in predicting the onset of heart rhythm irregularities. 2012-08-03T06:06:56Z 2012-08-03T06:06:56Z 2012-02-27 Working Paper p. 1-5 978-145771989-9 http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=06178976 http://dspace.unimap.edu.my/123456789/20573 en Proceedings of the 2012 International Conference on Biomedical Engineering (ICoBE) Institute of Electrical and Electronics Engineers (IEEE) |
| spellingShingle | Ventricular tachycardia Electrocardiogram Semantic mining Heart disease Mohd Afzan, Othman Norlaili, Mat Safri Sinan S., Mohammed Sheet Determination of the onset of ventricular tachycardia |
| title | Determination of the onset of ventricular tachycardia |
| title_full | Determination of the onset of ventricular tachycardia |
| title_fullStr | Determination of the onset of ventricular tachycardia |
| title_full_unstemmed | Determination of the onset of ventricular tachycardia |
| title_short | Determination of the onset of ventricular tachycardia |
| title_sort | determination of the onset of ventricular tachycardia |
| topic | Ventricular tachycardia Electrocardiogram Semantic mining Heart disease |
| url | http://dspace.unimap.edu.my/123456789/20573 |
| url_provider | http://dspace.unimap.edu.my/ |