Complementary Photoplethysmogram Synthesis From Electrocardiogram Using Generative Adversarial Network Article Swipe
Heean Shin
,
Sukkyu Sun
,
Joonnyong Lee
,
Hee Chan Kim
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1109/access.2021.3078534
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1109/access.2021.3078534
Photoplethysmogram (PPG) is one of the most widely measured biosignals alongside electrocardiogram (ECG). Due to the simplicity of measurement and the advent of wearable devices, there have been growing interest in using PPG for a variety of healthcare applications such as cardiac function estimation. However, unlike ECG, there are not many large databases available for clinically significant analyses of PPG. To overcome this issue, a Generative Adversarial Network-based model to generate PPG using ECG as input is proposed. The network was trained using a large open database of biosignals measured from surgical patients and was externally validated using an alternative database sourced from another hospital. The generated PPG was compared with the reference PPG using percent root mean square difference (PRD) and Pearson correlation coefficient to evaluate the morphological similarity. Additionally, heart rate measured from the reference ECG, reference PPG, and generated PPG, and compared through repeated measure analysis of variance to test for any significant differences. The mean PRD was 32± 10% and the mean correlation coefficient was 0.95± 0.05 in the test dataset. The HR from the three biosignals showed no significant difference with a -value of 0.473. When the optimized GAN model was tested on atrial fibrillation ECG from a third dataset, the mean correlation coefficient between the generated PPG heart rate and the ECG heart rate was 0.94± 0.15, with paired t-test resulting in -value of 0.64. The results indicate that the proposed method may provide a valuable alternative to augmenting biosignal databases that are abundant in one signal while lacking in another.
Related Topics
Concepts
Photoplethysmogram
Correlation coefficient
Pattern recognition (psychology)
Computer science
Pearson product-moment correlation coefficient
Artificial intelligence
Correlation
Electrocardiography
Mathematics
Medicine
Statistics
Cardiology
Filter (signal processing)
Machine learning
Computer vision
Geometry
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/access.2021.3078534
- https://ieeexplore.ieee.org/ielx7/6287639/9312710/09426908.pdf
- OA Status
- gold
- Cited By
- 18
- References
- 104
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3163705825
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3163705825Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/access.2021.3078534Digital Object Identifier
- Title
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Complementary Photoplethysmogram Synthesis From Electrocardiogram Using Generative Adversarial NetworkWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2021Year of publication
- Publication date
-
2021-01-01Full publication date if available
- Authors
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Heean Shin, Sukkyu Sun, Joonnyong Lee, Hee Chan KimList of authors in order
- Landing page
-
https://doi.org/10.1109/access.2021.3078534Publisher landing page
- PDF URL
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https://ieeexplore.ieee.org/ielx7/6287639/9312710/09426908.pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://ieeexplore.ieee.org/ielx7/6287639/9312710/09426908.pdfDirect OA link when available
- Concepts
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Photoplethysmogram, Correlation coefficient, Pattern recognition (psychology), Computer science, Pearson product-moment correlation coefficient, Artificial intelligence, Correlation, Electrocardiography, Mathematics, Medicine, Statistics, Cardiology, Filter (signal processing), Machine learning, Computer vision, GeometryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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18Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2, 2024: 6, 2023: 4, 2022: 4, 2021: 2Per-year citation counts (last 5 years)
- References (count)
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104Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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