ArticleArtery research2026
A Dual-Output Physiology-Informed Neural Network Architecture for Continuous Cuffless Blood Pressure Waveform Estimation: A Proof‑of‑Concept.
Article in Artery research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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2 authors.
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Abstract
This pilot study introduces the first subject‑specific, physiology‑informed neural network approach for accurate estimation of the full blood pressure (BP) waveform. The method builds on a nonlinear autoregressive model with exogenous inputs (NARX), implemented through artificial neural networks trained on subject‑specific electrocardiography (ECG) and photoplethysmography (PPG) signals. Three model configurations are evaluated: (1) a reference NARX model trained on 30 min of data, (2) a reduced‑data NARX model trained on 15 min, and (3) a physiology‑informed model (NARX
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