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 in | Computer methods and programs in biomedicine Vol. 221; p. 106890 | 
|---|---|
| Main Authors | , , , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
        Ireland
          Elsevier B.V
    
        01.06.2022
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| Subjects | |
| Online Access | Get full text | 
| ISSN | 0169-2607 1872-7565 1872-7565  | 
| DOI | 10.1016/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. | 
    
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| 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 – name: 1 Oregon State University, Corvallis, OR – name: 2 Oregon Health & Science University, Knight Cardiovascular Institute, Portland, OR  | 
    
| Author_xml | – sequence: 1 givenname: Julian D. surname: Fortune fullname: Fortune, Julian D. organization: Oregon State University, Corvallis, OR, United States – sequence: 2 givenname: Natalie E. orcidid: 0000-0002-6338-2814 surname: Coppa fullname: Coppa, Natalie E. organization: Oregon State University, Corvallis, OR, United States – sequence: 3 givenname: Kazi T. surname: Haq fullname: Haq, Kazi T. organization: Oregon Health and Science University, Knight Cardiovascular Institute, Portland, OR, United States – sequence: 4 givenname: Hetal surname: Patel fullname: Patel, Hetal organization: Oregon Health and Science University, Knight Cardiovascular Institute, Portland, OR, United States – sequence: 5 givenname: Larisa G. orcidid: 0000-0002-6976-1313 surname: Tereshchenko fullname: Tereshchenko, Larisa G. email: tereshl@ccf.org organization: Oregon Health and Science University, Knight Cardiovascular Institute, Portland, OR, United States  | 
    
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| CitedBy_id | crossref_primary_10_3390_s24082484 crossref_primary_10_1088_1361_6579_ad4954 crossref_primary_10_1016_j_cmpb_2024_108053 crossref_primary_10_1016_j_eswa_2024_124381 crossref_primary_10_1159_000542399  | 
    
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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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| 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 | 
    
| URI | https://www.clinicalkey.com/#!/content/1-s2.0-S0169260722002723 https://dx.doi.org/10.1016/j.cmpb.2022.106890 https://www.ncbi.nlm.nih.gov/pubmed/35598436 https://www.proquest.com/docview/2668218745 https://pubmed.ncbi.nlm.nih.gov/PMC9286778 https://www.ncbi.nlm.nih.gov/pmc/articles/9286778  | 
    
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