Papers › Blood Pressure Estimation from Photoplethysmogram Using a Spectro-Temporal Deep Neural Network
Blood Pressure Estimation from Photoplethysmogram Using a Spectro-Temporal Deep Neural Network
Gašper Slapničar, Nejc Mlakar, Mitja Luštrek
Blood pressure (BP) is a direct indicator of hypertension, a dangerous and potentially deadly condition. Regular monitoring of BP is thus important, but many people have aversion towards cuff-based devices, and their limitation is that they can only be used at rest. Using just a photoplethysmogram (PPG) to estimate BP is a potential solution investigated in our study. We analyzed the MIMIC III database for high-quality PPG and arterial BP waveforms, resulting in over 700 h of signals after preprocessing, belonging to 510 subjects. We then used the PPG alongside its first and second derivative as inputs into a novel spectro-temporal deep neural network with residual connections. We have shown in a leave-one-subject-out experiment that the network is able to model the dependency between PPG and BP, achieving mean absolute errors of 9.43 for systolic and 6.88 for diastolic BP. Additionally we have shown that personalization of models is important and substantially improves the results, while deriving a good general predictive model is difficult. We have made crucial parts of our study, especially the list of used subjects and our neural network code, publicly available, in an effort to provide a solid baseline and simplify potential comparison between future studies on an explicit MIMIC III subset.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Blood pressure estimation | MIMIC-III | ResNet (raw PPG + PPG’ + PPG”, with personalization) | MAE for DBP [mmHg] | 6.88 | #2 of 4 | Archive leaderboard | report |
| Blood pressure estimation | MIMIC-III | ResNet (raw PPG + PPG’ + PPG”, with personalization) | MAE for SBP [mmHg] | 9.43 | #2 of 4 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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