Paper
Individual-level Public-Private Decoupling for Continuous Blood Pressure Waveform Prediction (IPPD)
ICLR 2027 submission (under review)
TL;DR
Splits PPG representations into statistically decorrelated Public (population) and Private (individual) features; predicts ABP as public waveform + individual residual. Dual-view contrastive learning on the Private branch separates within-person consistency from between-person variation. On VitalDB-360, without target-case calibration or fine-tuning: waveform RMSE 11.65 mmHg, MAE 9.91 mmHg across 30 held-out cases; claims best individual-level performance vs BP baselines.
- Form factor: finger
Results on ChatPPG leaderboards · 1
All leaderboards| Leaderboard | Method | Result | Rank |
|---|---|---|---|
| VitalDB RMSE (mmHg)Cuffless blood pressure estimation | Individual-level Public-Private Decoupling for C | 11.65RMSE (mmHg), lower is better | #1 of 1 |
1 row is credited to this paper. Ranks apply within each leaderboard only, as reported by the source.
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Cite this paper
APA
Individual-level Public-Private Decoupling for Continuous Blood Pressure Waveform Prediction (IPPD). (2026). ICLR 2027 submission. https://openreview.net/forum?id=a8h33qllxT
BibTeX
@misc{ippdpublicprivat2026individuallevel,
title = {{Individual-level Public-Private Decoupling for Continuous Blood Pressure Waveform Prediction (IPPD)}},
year = {2026},
howpublished = {ICLR 2027 submission},
url = {https://openreview.net/forum?id=a8h33qllxT}
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