Digitizing ECG image: A new method and open-source software code

•We presented a new paper-ECG digitization algorithm, converting an ECG image to signal.•The digitized ECG was in substantial agreement with the digitally recorded ECG.•The disagreement was due to differences in simultaneous vs. asynchronous ECG leads.•We provided open-source Python code that will f...

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Published inComputer methods and programs in biomedicine Vol. 221; p. 106890
Main Authors Fortune, Julian D., Coppa, Natalie E., Haq, Kazi T., Patel, Hetal, Tereshchenko, Larisa G.
Format Journal Article
LanguageEnglish
Published Ireland Elsevier B.V 01.06.2022
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Online AccessGet full text
ISSN0169-2607
1872-7565
1872-7565
DOI10.1016/j.cmpb.2022.106890

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Abstract •We presented a new paper-ECG digitization algorithm, converting an ECG image to signal.•The digitized ECG was in substantial agreement with the digitally recorded ECG.•The disagreement was due to differences in simultaneous vs. asynchronous ECG leads.•We provided open-source Python code that will facilitate further development of the tool. We aimed to develop and validate an open-source code ECG-digitizing tool and assess agreements of ECG measurements across three types of median beats, comprised of digitally recorded simultaneous and asynchronous ECG leads and digitized asynchronous ECG leads. We used the data of clinical studies participants (n = 230; mean age 30±15 y; 25% female; 52% had the cardiovascular disease) with available both digitally recorded and printed on paper and then scanned ECGs, split into development (n = 150) and validation (n = 80) datasets. The agreement between ECG and VCG measurements on the digitally recorded time-coherent median beat, representative asynchronous digitized, and digitally recorded beats was assessed by Bland-Altman analysis. The sample-per-sample comparison of digitally recorded and digitized signals showed a very high correlation (0.977), a small mean difference (9.3 µV), and root mean squared error (25.9 µV). Agreement between digitally recorded and digitized representative beat was high [area spatial ventricular gradient (SVG) elevation bias 2.5(95% limits of agreement [LOA] -7.9–13.0)°; precision 96.8%; inter-class correlation [ICC] 0.988; Lin's concordance coefficient ρc 0.97(95% confidence interval [CI] 0.95–0.98)]. Agreement between digitally recorded asynchronous and time-coherent median beats was moderate for area-based VCG metrics (spatial QRS-T angle bias 1.4(95%LOA -33.2–30.3)°; precision 94.8%; ICC 0.95; Lin's concordance coefficient ρc 0.90(95%CI 0.82–0.95)]. We developed and validated an open-source software tool for paper-ECG digitization. Asynchronous ECG leads are the primary source of disagreement in measurements on digitally recorded and digitized ECGs.
AbstractList We aimed to develop and validate an open-source code ECG-digitizing tool and assess agreements of ECG measurements across three types of median beats, comprised of digitally recorded simultaneous and asynchronous ECG leads and digitized asynchronous ECG leads. We used the data of clinical studies participants (n = 230; mean age 30±15 y; 25% female; 52% had the cardiovascular disease) with available both digitally recorded and printed on paper and then scanned ECGs, split into development (n = 150) and validation (n = 80) datasets. The agreement between ECG and VCG measurements on the digitally recorded time-coherent median beat, representative asynchronous digitized, and digitally recorded beats was assessed by Bland-Altman analysis. The sample-per-sample comparison of digitally recorded and digitized signals showed a very high correlation (0.977), a small mean difference (9.3 µV), and root mean squared error (25.9 µV). Agreement between digitally recorded and digitized representative beat was high [area spatial ventricular gradient (SVG) elevation bias 2.5(95% limits of agreement [LOA] -7.9-13.0)°; precision 96.8%; inter-class correlation [ICC] 0.988; Lin's concordance coefficient ρ 0.97(95% confidence interval [CI] 0.95-0.98)]. Agreement between digitally recorded asynchronous and time-coherent median beats was moderate for area-based VCG metrics (spatial QRS-T angle bias 1.4(95%LOA -33.2-30.3)°; precision 94.8%; ICC 0.95; Lin's concordance coefficient ρ 0.90(95%CI 0.82-0.95)]. We developed and validated an open-source software tool for paper-ECG digitization. Asynchronous ECG leads are the primary source of disagreement in measurements on digitally recorded and digitized ECGs.
•We presented a new paper-ECG digitization algorithm, converting an ECG image to signal.•The digitized ECG was in substantial agreement with the digitally recorded ECG.•The disagreement was due to differences in simultaneous vs. asynchronous ECG leads.•We provided open-source Python code that will facilitate further development of the tool. We aimed to develop and validate an open-source code ECG-digitizing tool and assess agreements of ECG measurements across three types of median beats, comprised of digitally recorded simultaneous and asynchronous ECG leads and digitized asynchronous ECG leads. We used the data of clinical studies participants (n = 230; mean age 30±15 y; 25% female; 52% had the cardiovascular disease) with available both digitally recorded and printed on paper and then scanned ECGs, split into development (n = 150) and validation (n = 80) datasets. The agreement between ECG and VCG measurements on the digitally recorded time-coherent median beat, representative asynchronous digitized, and digitally recorded beats was assessed by Bland-Altman analysis. The sample-per-sample comparison of digitally recorded and digitized signals showed a very high correlation (0.977), a small mean difference (9.3 µV), and root mean squared error (25.9 µV). Agreement between digitally recorded and digitized representative beat was high [area spatial ventricular gradient (SVG) elevation bias 2.5(95% limits of agreement [LOA] -7.9–13.0)°; precision 96.8%; inter-class correlation [ICC] 0.988; Lin's concordance coefficient ρc 0.97(95% confidence interval [CI] 0.95–0.98)]. Agreement between digitally recorded asynchronous and time-coherent median beats was moderate for area-based VCG metrics (spatial QRS-T angle bias 1.4(95%LOA -33.2–30.3)°; precision 94.8%; ICC 0.95; Lin's concordance coefficient ρc 0.90(95%CI 0.82–0.95)]. We developed and validated an open-source software tool for paper-ECG digitization. Asynchronous ECG leads are the primary source of disagreement in measurements on digitally recorded and digitized ECGs.
We aimed to develop and validate an open-source code ECG-digitizing tool and assess agreements of ECG measurements across three types of median beats, comprised of digitally recorded simultaneous and asynchronous ECG leads and digitized asynchronous ECG leads.BACKGROUND AND OBJECTIVEWe aimed to develop and validate an open-source code ECG-digitizing tool and assess agreements of ECG measurements across three types of median beats, comprised of digitally recorded simultaneous and asynchronous ECG leads and digitized asynchronous ECG leads.We used the data of clinical studies participants (n = 230; mean age 30±15 y; 25% female; 52% had the cardiovascular disease) with available both digitally recorded and printed on paper and then scanned ECGs, split into development (n = 150) and validation (n = 80) datasets. The agreement between ECG and VCG measurements on the digitally recorded time-coherent median beat, representative asynchronous digitized, and digitally recorded beats was assessed by Bland-Altman analysis.METHODSWe used the data of clinical studies participants (n = 230; mean age 30±15 y; 25% female; 52% had the cardiovascular disease) with available both digitally recorded and printed on paper and then scanned ECGs, split into development (n = 150) and validation (n = 80) datasets. The agreement between ECG and VCG measurements on the digitally recorded time-coherent median beat, representative asynchronous digitized, and digitally recorded beats was assessed by Bland-Altman analysis.The sample-per-sample comparison of digitally recorded and digitized signals showed a very high correlation (0.977), a small mean difference (9.3 µV), and root mean squared error (25.9 µV). Agreement between digitally recorded and digitized representative beat was high [area spatial ventricular gradient (SVG) elevation bias 2.5(95% limits of agreement [LOA] -7.9-13.0)°; precision 96.8%; inter-class correlation [ICC] 0.988; Lin's concordance coefficient ρc 0.97(95% confidence interval [CI] 0.95-0.98)]. Agreement between digitally recorded asynchronous and time-coherent median beats was moderate for area-based VCG metrics (spatial QRS-T angle bias 1.4(95%LOA -33.2-30.3)°; precision 94.8%; ICC 0.95; Lin's concordance coefficient ρc 0.90(95%CI 0.82-0.95)].RESULTSThe sample-per-sample comparison of digitally recorded and digitized signals showed a very high correlation (0.977), a small mean difference (9.3 µV), and root mean squared error (25.9 µV). Agreement between digitally recorded and digitized representative beat was high [area spatial ventricular gradient (SVG) elevation bias 2.5(95% limits of agreement [LOA] -7.9-13.0)°; precision 96.8%; inter-class correlation [ICC] 0.988; Lin's concordance coefficient ρc 0.97(95% confidence interval [CI] 0.95-0.98)]. Agreement between digitally recorded asynchronous and time-coherent median beats was moderate for area-based VCG metrics (spatial QRS-T angle bias 1.4(95%LOA -33.2-30.3)°; precision 94.8%; ICC 0.95; Lin's concordance coefficient ρc 0.90(95%CI 0.82-0.95)].We developed and validated an open-source software tool for paper-ECG digitization. Asynchronous ECG leads are the primary source of disagreement in measurements on digitally recorded and digitized ECGs.CONCLUSIONSWe developed and validated an open-source software tool for paper-ECG digitization. Asynchronous ECG leads are the primary source of disagreement in measurements on digitally recorded and digitized ECGs.
ArticleNumber 106890
Author Patel, Hetal
Fortune, Julian D.
Coppa, Natalie E.
Tereshchenko, Larisa G.
Haq, Kazi T.
AuthorAffiliation 4 Cleveland Clinic Lerner Research Institute, Department of Quantitative Health Sciences, Cleveland, OH
1 Oregon State University, Corvallis, OR
3 Chicago Medical School at Rosalind Franklin University, IL
2 Oregon Health & Science University, Knight Cardiovascular Institute, Portland, OR
AuthorAffiliation_xml – name: 3 Chicago Medical School at Rosalind Franklin University, IL
– name: 4 Cleveland Clinic Lerner Research Institute, Department of Quantitative Health Sciences, Cleveland, OH
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  organization: Oregon State University, Corvallis, OR, United States
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Keywords ECG
Digitization
Paper ECG digitizing
ECG paper digital conversion
Paper-to-digital conversion
Language English
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Snippet •We presented a new paper-ECG digitization algorithm, converting an ECG image to signal.•The digitized ECG was in substantial agreement with the digitally...
We aimed to develop and validate an open-source code ECG-digitizing tool and assess agreements of ECG measurements across three types of median beats,...
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StartPage 106890
SubjectTerms Adolescent
Adult
Digitization
ECG
ECG paper digital conversion
Electrocardiography - methods
Female
Heart Ventricles
Humans
Male
Middle Aged
Paper ECG digitizing
Paper-to-digital conversion
Signal Processing, Computer-Assisted
Software
Young Adult
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Title Digitizing ECG image: A new method and open-source software code
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