Heat map visualization for electrocardiogram data analysis

Abstract Background Most electrocardiogram (ECG) studies still take advantage of traditional statistical functions, and the results are mostly presented in tables, histograms, and curves. Few papers display ECG data by visual means. The aim of this study was to analyze and show data for electrocardi...

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Main Authors: Haisen Guo, Weidai Zhang, Chumin Ni, Zhixiong Cai, Songming Chen, Xiansheng Huang
Format: Article
Language:English
Published: BMC 2020-06-01
Series:BMC Cardiovascular Disorders
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12872-020-01560-8
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spelling doaj-69318eadebf347519b72cae5d2851ffd2020-11-25T01:59:21ZengBMCBMC Cardiovascular Disorders1471-22612020-06-012011810.1186/s12872-020-01560-8Heat map visualization for electrocardiogram data analysisHaisen Guo0Weidai Zhang1Chumin Ni2Zhixiong Cai3Songming Chen4Xiansheng Huang5Department of Cardiology, Shantou Central HospitalDepartment of Cardiology, Shantou Central HospitalDepartment of Cardiology, Shantou Central HospitalDepartment of Cardiology, Shantou Central HospitalDepartment of Cardiology, the First Affiliated Hospital of Shantou University Medical CollegeDepartment of Cardiology, the First Affiliated Hospital of Shantou University Medical CollegeAbstract Background Most electrocardiogram (ECG) studies still take advantage of traditional statistical functions, and the results are mostly presented in tables, histograms, and curves. Few papers display ECG data by visual means. The aim of this study was to analyze and show data for electrocardiographic left ventricular hypertrophy (LVH) with ST-segment elevation (STE) by a heat map in order to explore the feasibility and clinical value of heat mapping for ECG data visualization. Methods We sequentially collected the electrocardiograms of inpatients in the First Affiliated Hospital of Shantou University Medical College from July 2015 to December 2015 in order to screen cases of LVH with STE. HemI 1.0 software was used to draw heat maps to display the STE of each lead of each collected ECG. Cluster analysis was carried out based on the heat map and the results were drawn as tree maps (pedigree maps) in the heat map. Results In total, 60 cases of electrocardiographic LVH with STE were screened and analyzed. STE leads were mainly in the V1, V2 and V3 leads. The ST-segment shifts of each lead of each collected ECG could be conveniently visualized in the heat map. According to cluster analysis in the heat map, STE leads were clustered into two categories, comprising of the right precordial leads (V1, V2, V3) and others (V4, V5, V6, I, II, III, aVF, aVL, aVR). Moreover, the STE amplitude in 40% (24 out of 60) of cases reached the threshold specified in the STEMI guideline. These cases also could be fully displayed and visualized in the heat map. Cluster analysis in the heat map showed that the III, aVF and aVR leads could be clustered together, the V1, V2, V3 and V4 leads could be clustered together, and the V5, V6, I and aVL leads could be clustered together. Conclusion Heat maps and cluster analysis can be used to fully display every lead of each electrocardiogram and provide relatively comprehensive information.http://link.springer.com/article/10.1186/s12872-020-01560-8Heat mapVisualizationElectrocardiogramData analysis
collection DOAJ
language English
format Article
sources DOAJ
author Haisen Guo
Weidai Zhang
Chumin Ni
Zhixiong Cai
Songming Chen
Xiansheng Huang
spellingShingle Haisen Guo
Weidai Zhang
Chumin Ni
Zhixiong Cai
Songming Chen
Xiansheng Huang
Heat map visualization for electrocardiogram data analysis
BMC Cardiovascular Disorders
Heat map
Visualization
Electrocardiogram
Data analysis
author_facet Haisen Guo
Weidai Zhang
Chumin Ni
Zhixiong Cai
Songming Chen
Xiansheng Huang
author_sort Haisen Guo
title Heat map visualization for electrocardiogram data analysis
title_short Heat map visualization for electrocardiogram data analysis
title_full Heat map visualization for electrocardiogram data analysis
title_fullStr Heat map visualization for electrocardiogram data analysis
title_full_unstemmed Heat map visualization for electrocardiogram data analysis
title_sort heat map visualization for electrocardiogram data analysis
publisher BMC
series BMC Cardiovascular Disorders
issn 1471-2261
publishDate 2020-06-01
description Abstract Background Most electrocardiogram (ECG) studies still take advantage of traditional statistical functions, and the results are mostly presented in tables, histograms, and curves. Few papers display ECG data by visual means. The aim of this study was to analyze and show data for electrocardiographic left ventricular hypertrophy (LVH) with ST-segment elevation (STE) by a heat map in order to explore the feasibility and clinical value of heat mapping for ECG data visualization. Methods We sequentially collected the electrocardiograms of inpatients in the First Affiliated Hospital of Shantou University Medical College from July 2015 to December 2015 in order to screen cases of LVH with STE. HemI 1.0 software was used to draw heat maps to display the STE of each lead of each collected ECG. Cluster analysis was carried out based on the heat map and the results were drawn as tree maps (pedigree maps) in the heat map. Results In total, 60 cases of electrocardiographic LVH with STE were screened and analyzed. STE leads were mainly in the V1, V2 and V3 leads. The ST-segment shifts of each lead of each collected ECG could be conveniently visualized in the heat map. According to cluster analysis in the heat map, STE leads were clustered into two categories, comprising of the right precordial leads (V1, V2, V3) and others (V4, V5, V6, I, II, III, aVF, aVL, aVR). Moreover, the STE amplitude in 40% (24 out of 60) of cases reached the threshold specified in the STEMI guideline. These cases also could be fully displayed and visualized in the heat map. Cluster analysis in the heat map showed that the III, aVF and aVR leads could be clustered together, the V1, V2, V3 and V4 leads could be clustered together, and the V5, V6, I and aVL leads could be clustered together. Conclusion Heat maps and cluster analysis can be used to fully display every lead of each electrocardiogram and provide relatively comprehensive information.
topic Heat map
Visualization
Electrocardiogram
Data analysis
url http://link.springer.com/article/10.1186/s12872-020-01560-8
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AT weidaizhang heatmapvisualizationforelectrocardiogramdataanalysis
AT chuminni heatmapvisualizationforelectrocardiogramdataanalysis
AT zhixiongcai heatmapvisualizationforelectrocardiogramdataanalysis
AT songmingchen heatmapvisualizationforelectrocardiogramdataanalysis
AT xianshenghuang heatmapvisualizationforelectrocardiogramdataanalysis
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