Physics-Constrained Deep Learning Model for Contactless Blood Pressure Monitoring from Triaxial Bodyseismography

The paper introduces Phy‑BP, a physics‑constrained deep learning framework for contactless blood pressure monitoring using triaxial bodyseismography (BSG). It employs an adaptive quality‑control algorithm to select cardiogenic‑rich BSG segments and embeds a 3‑D wave‑propagation physical model into the neural network to align multi‑axis features, enhancing robustness to real‑world distortions. Experiments on a 162‑hour hospital dataset from 21 subjects demonstrate that Phy‑BP can filter low‑quality measurements and maintain accurate BP estimation even with limited training data.

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