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An Optimized Automatic P Wave Delineation Method Based on Phasor Transform
Accurate P wave detection is important for arrhythmia diagnosis, e.g. P wave absence or P duration for atrial fibrillation diagnosis and other atrial arrhythmias. Phasor transform is an effective method for ECG fiducial points delineation. It maps each ECG sample into a phasor to enhance slight vari...
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creator | Yan, Jiayi Xie, Hanshuang Zhu, Huaiyu Liu, Yamin Wu, Fan Pan, Yun |
description | Accurate P wave detection is important for arrhythmia diagnosis, e.g. P wave absence or P duration for atrial fibrillation diagnosis and other atrial arrhythmias. Phasor transform is an effective method for ECG fiducial points delineation. It maps each ECG sample into a phasor to enhance slight variations and preserves morphology and magnitude characteristics. In this paper, we optimized the automatic P wave delineation method based on phasor transform in four aspects, i.e., signal denoising, wave localization, candidate points detection, and optimal points selection. In our experiments, the length of the search window and the degree of phasor transform were established through various trials. Especially, along with zero-crossing points of the phasor signal, intersections of the phasor signal and the original ECG signal are obtained as candidates, which make the most contribution to delineation results. For validation, the QT Database with 3194 P wave annotations from 105 records of two leads is adopted. As a result, we reached F1 scores of 94.67% and 93.56% with detection error rates (DERs) of 10.80% and 13.06% for P wave onset and offset points detection, respectively. The F 1 score and DER for P peak detection under a tolerance of 75 ms were 95.33% and 9.46%, respectively, which outperforms other reproducible works and their combinations. |
doi_str_mv | 10.22489/CinC.2022.122 |
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Phasor transform is an effective method for ECG fiducial points delineation. It maps each ECG sample into a phasor to enhance slight variations and preserves morphology and magnitude characteristics. In this paper, we optimized the automatic P wave delineation method based on phasor transform in four aspects, i.e., signal denoising, wave localization, candidate points detection, and optimal points selection. In our experiments, the length of the search window and the degree of phasor transform were established through various trials. Especially, along with zero-crossing points of the phasor signal, intersections of the phasor signal and the original ECG signal are obtained as candidates, which make the most contribution to delineation results. For validation, the QT Database with 3194 P wave annotations from 105 records of two leads is adopted. As a result, we reached F1 scores of 94.67% and 93.56% with detection error rates (DERs) of 10.80% and 13.06% for P wave onset and offset points detection, respectively. 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Phasor transform is an effective method for ECG fiducial points delineation. It maps each ECG sample into a phasor to enhance slight variations and preserves morphology and magnitude characteristics. In this paper, we optimized the automatic P wave delineation method based on phasor transform in four aspects, i.e., signal denoising, wave localization, candidate points detection, and optimal points selection. In our experiments, the length of the search window and the degree of phasor transform were established through various trials. Especially, along with zero-crossing points of the phasor signal, intersections of the phasor signal and the original ECG signal are obtained as candidates, which make the most contribution to delineation results. For validation, the QT Database with 3194 P wave annotations from 105 records of two leads is adopted. As a result, we reached F1 scores of 94.67% and 93.56% with detection error rates (DERs) of 10.80% and 13.06% for P wave onset and offset points detection, respectively. The F 1 score and DER for P peak detection under a tolerance of 75 ms were 95.33% and 9.46%, respectively, which outperforms other reproducible works and their combinations.</description><subject>Arrhythmia</subject><subject>Atrial fibrillation</subject><subject>Error analysis</subject><subject>Location awareness</subject><subject>Morphology</subject><subject>Transforms</subject><issn>2325-887X</issn><isbn>9798350300970</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2022</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotjEtLw0AUhUdBsNRsXbmYP5B4ZybzWsb4ptIuKrorN8kNHWmSkomC_noDejaH7_BxGLsUkEmZO39dhr7MJEiZCSlPWOKtd0qDAvAWTtlCKqlT5-z7OUti_IA52jpv3II9Fz1fH6fQhR9qePE5DR1OoeYb_oZfxG_pEHqal6HnLzTth4bfYJzNmTd7jMPItyP2sR3G7oKdtXiIlPz3kr3e323Lx3S1fngqi1UahPYyzRWJRrXC2brJNTZQGyMA20p5k1MNZBGxMnWu0CtDwmvQlXCirUg4tKiW7OrvNxDR7jiGDsfvnQBwwnijfgFuaE0s</recordid><startdate>2022</startdate><enddate>2022</enddate><creator>Yan, Jiayi</creator><creator>Xie, Hanshuang</creator><creator>Zhu, Huaiyu</creator><creator>Liu, Yamin</creator><creator>Wu, Fan</creator><creator>Pan, Yun</creator><general>Creative Commons</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>2022</creationdate><title>An Optimized Automatic P Wave Delineation Method Based on Phasor Transform</title><author>Yan, Jiayi ; Xie, Hanshuang ; Zhu, Huaiyu ; Liu, Yamin ; Wu, Fan ; Pan, Yun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i1592-43e1d3f187cd45ad0c6610afb3964ec0e7aaab6c43a936e19505b181fbe18a7a3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Arrhythmia</topic><topic>Atrial fibrillation</topic><topic>Error analysis</topic><topic>Location awareness</topic><topic>Morphology</topic><topic>Transforms</topic><toplevel>online_resources</toplevel><creatorcontrib>Yan, Jiayi</creatorcontrib><creatorcontrib>Xie, Hanshuang</creatorcontrib><creatorcontrib>Zhu, Huaiyu</creatorcontrib><creatorcontrib>Liu, Yamin</creatorcontrib><creatorcontrib>Wu, Fan</creatorcontrib><creatorcontrib>Pan, Yun</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Yan, Jiayi</au><au>Xie, Hanshuang</au><au>Zhu, Huaiyu</au><au>Liu, Yamin</au><au>Wu, Fan</au><au>Pan, Yun</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>An Optimized Automatic P Wave Delineation Method Based on Phasor Transform</atitle><btitle>2022 Computing in Cardiology (CinC)</btitle><stitle>CINC</stitle><date>2022</date><risdate>2022</risdate><volume>498</volume><spage>1</spage><epage>4</epage><pages>1-4</pages><eissn>2325-887X</eissn><eisbn>9798350300970</eisbn><abstract>Accurate P wave detection is important for arrhythmia diagnosis, e.g. P wave absence or P duration for atrial fibrillation diagnosis and other atrial arrhythmias. Phasor transform is an effective method for ECG fiducial points delineation. It maps each ECG sample into a phasor to enhance slight variations and preserves morphology and magnitude characteristics. In this paper, we optimized the automatic P wave delineation method based on phasor transform in four aspects, i.e., signal denoising, wave localization, candidate points detection, and optimal points selection. In our experiments, the length of the search window and the degree of phasor transform were established through various trials. Especially, along with zero-crossing points of the phasor signal, intersections of the phasor signal and the original ECG signal are obtained as candidates, which make the most contribution to delineation results. For validation, the QT Database with 3194 P wave annotations from 105 records of two leads is adopted. As a result, we reached F1 scores of 94.67% and 93.56% with detection error rates (DERs) of 10.80% and 13.06% for P wave onset and offset points detection, respectively. The F 1 score and DER for P peak detection under a tolerance of 75 ms were 95.33% and 9.46%, respectively, which outperforms other reproducible works and their combinations.</abstract><pub>Creative Commons</pub><doi>10.22489/CinC.2022.122</doi><tpages>4</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Arrhythmia Atrial fibrillation Error analysis Location awareness Morphology Transforms |
title | An Optimized Automatic P Wave Delineation Method Based on Phasor Transform |
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