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13 June 2024 Predicting blood pressure from the change of photoplethysmography features
Qin Chen, Xuezhi Yang, Yawei Chen, Dingliang Wang
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Proceedings Volume 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024); 1318032 (2024) https://doi.org/10.1117/12.3033251
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 2024, Guangzhou, China
Abstract
Blood pressure (BP) is a crucial indicator for assessing cardiovascular health, and effective monitoring contributes to early treatment of cardiovascular diseases. Photoplethysmography (PPG) has shown immense potential in non-invasive BP monitoring. However, existing studies often overlook the impact of feature variations on BP changes. Therefore, this study propose a blood pressure estimation method based on PPG feature changes. Initially, high-quality PPG segments are obtained through signal processing from PPG waveforms, and 68 contributory PPG differential features (DF) for BP changes are derived through differencing. Subsequently, optimal subsets of DFs are identified using correlation analysis and stepwise forward feature selection. Finally, an interpretable model is employed to map DF to BP changes, incorporating calibration values for accurate BP estimation. The proposed method is evaluated on self-collected datasets. The root mean square error (RMSE) for systolic blood pressure (SBP) is 8.39 mmHg, and for diastolic blood pressure (DBP), it is 5.75 mmHg. The corresponding Pearson correlation coefficient (PCC) values are 0.88 and 0.83. Correlation analysis indicates a close relationship between PPG differential features and BP changes. Compared to direct use of PPG features, the RMSE of BP estimation improves by approximately 40%, highlighting the effectiveness of PPG differential features in BP estimation.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Qin Chen, Xuezhi Yang, Yawei Chen, and Dingliang Wang "Predicting blood pressure from the change of photoplethysmography features", Proc. SPIE 13180, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2024), 1318032 (13 June 2024); https://doi.org/10.1117/12.3033251
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KEYWORDS
Blood pressure
Feature selection
Feature extraction
Pulse signals
Photoplethysmography
Calibration
Signal to noise ratio
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