ArterialNet: Reconstructing Arterial Blood Pressure Waveform With Wearable Pulsatile Signals, a Cohort-Aware Approach.

ABSTRACT: Goal: Continuous arterial blood pressure (ABP) waveform is invasive but essential for hemodynamic monitoring. Current non-invasive techniques reconstruct ABP waveforms with pulsatile signals but derived inaccurate systolic and diastolic blood pressure (SBP/DBP) and were sensitive to individual variability. Methods: ArterialNet integrates generalized pulsatile-to-ABP signal translation and personalized feature extraction using hybrid loss functions and regularizations. Results: ArterialNet achieved a root mean square error (RMSE) of 5.41 ± 1.35 mmHg on MIMIC-III, achieving 58% lower standard deviation than existing signal translation techniques. ArterialNet also reconstructed ABP with RMSE of 7.99 ± 1.91 mmHg in remote health scenario. Conclusion: ArterialNet ach

SUBMITTER: Huang S 

PROVIDER: S-EPMC12772991 | biostudies-literature | 2026

REPOSITORIES: biostudies-literature