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Machine Learning-Ba...
Machine Learning-Based Classification of Hypertension using CnD Features from Acceleration Photoplethysmography and Clinical Parameters
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- Abdullah, Saad (author)
- Mälardalens universitet,Inbyggda system
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- Abdelakram, Hafid (author)
- Mälardalens universitet,Inbyggda system
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- Lindén, Maria, 1965- (author)
- Mälardalens universitet,Inbyggda system
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- Folke, Mia, 1967- (author)
- Mälardalens universitet,Inbyggda system
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- Kristoffersson, Annica, 1980- (author)
- Mälardalens universitet,Inbyggda system
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(creator_code:org_t)
- Institute of Electrical and Electronics Engineers Inc. 2023
- 2023
- English.
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In: Proceedings - IEEE Symposium on Computer-Based Medical Systems. - : Institute of Electrical and Electronics Engineers Inc.. - 9798350312249 ; , s. 923-924
- Related links:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Subject headings
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- Cardiovascular diseases (CVDs) are a leading cause of death worldwide, and hypertension is a major risk factor for acquiring CVDs. Early detection and treatment of hypertension can significantly reduce the risk of developing CVDs and related complications. In this study, a linear SVM machine learning model was used to classify subjects as normal or at different stages of hypertension. The features combined statistical parameters derived from the acceleration plethysmography waveforms and clinical parameters extracted from a publicly available dataset. The model achieved an overall accuracy of 87.50% on the validation dataset and 95.35% on the test dataset. The model's true positive rate and positive predictivity was high in all classes, indicating a high accuracy, and precision. This study represents the first attempt to classify cardiovascular conditions using a combination of acceleration photoplethysmogram (APG) features and clinical parameters The study demonstrates the potential of APG analysis as a valuable tool for early detection of hypertension.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Kardiologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Cardiac and Cardiovascular Systems (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Medicinteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Medical Engineering (hsv//eng)
Keyword
- acceleration photoplethysmography
- cardiovascular
- fiducial points
- hypertension
- PPG
- Acceleration
- Classification (of information)
- Learning systems
- Statistical tests
- Support vector machines
- Cardiovascular disease
- Causes of death
- Clinical parameters
- Machine-learning
- Photoplethysmogram
- Photoplethysmography
Publication and Content Type
- ref (subject category)
- kon (subject category)
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