The Feature Extraction to Determine the Wave’s Peaks in the Electrocardiogram Graphic Image
The electrocardiogram (ECG) will create the characteristic in the form of the wave’s peak pattern. The first peak and the next one in one ECG wave have their own value and names, namely PQRST peaks. The process of feature extraction is very significant to determine the certain pattern. The use of fe...
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Veröffentlicht in: | International journal of image, graphics and signal processing graphics and signal processing, 2017-06, Vol.9 (6), p.1-13 |
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creator | Hartati, Sri Wardoyo, Retantyo Yuli Setianto, Budi |
description | The electrocardiogram (ECG) will create the characteristic in the form of the wave’s peak pattern. The first peak and the next one in one ECG wave have their own value and names, namely PQRST peaks. The process of feature extraction is very significant to determine the certain pattern. The use of feature extraction will be useful to help to detect certain case, including the determination of PQRST peaks according to the ECG print-out. This study makes a method to determine the ECG peaks (PQRST), the heart rate, and ST-deviation according to the ECG graphic image. The input data is in the form of ECG graphic image which is derived from the ECG 12 lead record. This study employs segmentation method (grayscale and binary), morphology (dilation and erosion), and produce the graphic image which is read as the ECG signal in the pre-processing stage, and use the Pan-Tompkins algorithm for the feature extraction method. The result of the peak determination is validated by cardiologists. The validation shows that the result of up and down deflection computation from the isoelectric of each P, Q, R, S, and T wave has represented the ECG calculation clinically; including the calculation to determine the R-R interval, heart rate, and ST-deviation. |
doi_str_mv | 10.5815/ijigsp.2017.06.01 |
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The first peak and the next one in one ECG wave have their own value and names, namely PQRST peaks. The process of feature extraction is very significant to determine the certain pattern. The use of feature extraction will be useful to help to detect certain case, including the determination of PQRST peaks according to the ECG print-out. This study makes a method to determine the ECG peaks (PQRST), the heart rate, and ST-deviation according to the ECG graphic image. The input data is in the form of ECG graphic image which is derived from the ECG 12 lead record. This study employs segmentation method (grayscale and binary), morphology (dilation and erosion), and produce the graphic image which is read as the ECG signal in the pre-processing stage, and use the Pan-Tompkins algorithm for the feature extraction method. The result of the peak determination is validated by cardiologists. The validation shows that the result of up and down deflection computation from the isoelectric of each P, Q, R, S, and T wave has represented the ECG calculation clinically; including the calculation to determine the R-R interval, heart rate, and ST-deviation.</description><identifier>ISSN: 2074-9074</identifier><identifier>EISSN: 2074-9082</identifier><identifier>DOI: 10.5815/ijigsp.2017.06.01</identifier><language>eng</language><publisher>Hong Kong: Modern Education and Computer Science Press</publisher><subject>Deviation ; Echocardiography ; Electrocardiography ; Erosion ; Feature extraction ; Heart rate ; Image segmentation ; Mathematical analysis ; Signal processing</subject><ispartof>International journal of image, graphics and signal processing, 2017-06, Vol.9 (6), p.1-13</ispartof><rights>Copyright Modern Education and Computer Science Press Jun 2017</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,27905,27906</link.rule.ids></links><search><creatorcontrib>Hartati, Sri</creatorcontrib><creatorcontrib>Wardoyo, Retantyo</creatorcontrib><creatorcontrib>Yuli Setianto, Budi</creatorcontrib><creatorcontrib>Department of Computer Science and Electronics, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Yogyakarta, Indonesia</creatorcontrib><title>The Feature Extraction to Determine the Wave’s Peaks in the Electrocardiogram Graphic Image</title><title>International journal of image, graphics and signal processing</title><description>The electrocardiogram (ECG) will create the characteristic in the form of the wave’s peak pattern. The first peak and the next one in one ECG wave have their own value and names, namely PQRST peaks. The process of feature extraction is very significant to determine the certain pattern. The use of feature extraction will be useful to help to detect certain case, including the determination of PQRST peaks according to the ECG print-out. This study makes a method to determine the ECG peaks (PQRST), the heart rate, and ST-deviation according to the ECG graphic image. The input data is in the form of ECG graphic image which is derived from the ECG 12 lead record. This study employs segmentation method (grayscale and binary), morphology (dilation and erosion), and produce the graphic image which is read as the ECG signal in the pre-processing stage, and use the Pan-Tompkins algorithm for the feature extraction method. The result of the peak determination is validated by cardiologists. The validation shows that the result of up and down deflection computation from the isoelectric of each P, Q, R, S, and T wave has represented the ECG calculation clinically; including the calculation to determine the R-R interval, heart rate, and ST-deviation.</description><subject>Deviation</subject><subject>Echocardiography</subject><subject>Electrocardiography</subject><subject>Erosion</subject><subject>Feature extraction</subject><subject>Heart rate</subject><subject>Image segmentation</subject><subject>Mathematical analysis</subject><subject>Signal processing</subject><issn>2074-9074</issn><issn>2074-9082</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNo9kM1KAzEQx4MoWGofwFvA866ZbPYjR6ltLRT0UPEkId3MtqndD5NU9OZr-Ho-iVsrzmWG4ccM_x8hl8DitID02m7t2ncxZ5DHLIsZnJABZ7mIJCv46f-ci3My8n7L-spSSHIxIM_LDdIp6rB3SCfvweky2LahoaW3GNDVtkEaeuZJv-H355enD6hfPLXN73aywzK4ttTO2HbtdE1nTncbW9J5rdd4Qc4qvfM4-utD8jidLMd30eJ-Nh_fLKISIIHIrApMOEoDyDJZSCOrIjOl4dxI5GYlcsERQDAEiTpJqjQ1fbKK8ZRnPBXJkFwd73aufd2jD2rb7l3Tv1QgiywTrA_bU3CkStd677BSnbO1dh8KmDqIVEeR6iBSsUwxSH4AUi1nxA</recordid><startdate>20170608</startdate><enddate>20170608</enddate><creator>Hartati, Sri</creator><creator>Wardoyo, Retantyo</creator><creator>Yuli Setianto, Budi</creator><general>Modern Education and Computer Science Press</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7XB</scope><scope>8AL</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BVBZV</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>M0N</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope></search><sort><creationdate>20170608</creationdate><title>The Feature Extraction to Determine the Wave’s Peaks in the Electrocardiogram Graphic Image</title><author>Hartati, Sri ; 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The first peak and the next one in one ECG wave have their own value and names, namely PQRST peaks. The process of feature extraction is very significant to determine the certain pattern. The use of feature extraction will be useful to help to detect certain case, including the determination of PQRST peaks according to the ECG print-out. This study makes a method to determine the ECG peaks (PQRST), the heart rate, and ST-deviation according to the ECG graphic image. The input data is in the form of ECG graphic image which is derived from the ECG 12 lead record. This study employs segmentation method (grayscale and binary), morphology (dilation and erosion), and produce the graphic image which is read as the ECG signal in the pre-processing stage, and use the Pan-Tompkins algorithm for the feature extraction method. The result of the peak determination is validated by cardiologists. 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subjects | Deviation Echocardiography Electrocardiography Erosion Feature extraction Heart rate Image segmentation Mathematical analysis Signal processing |
title | The Feature Extraction to Determine the Wave’s Peaks in the Electrocardiogram Graphic Image |
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