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Continuous Blood Pressure with Photoplethysmography: Machine Learning for Photoplethysmography Signal Processing
Small, Emma P
Small, Emma P
Abstract
I have performed a comparative analysis of different methods of machine learning and statistical methods of modeling blood pressure from PPG data. I determined that a random forest regression using scikit-learn performed the best for the data we collected. This model was able to predict mean arterial pressure (MAP) with a mean absolute error of 4.654, well within the range of being potentially medically useful.
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2025-05-01
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5/9/2027
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Physics