OPLR: Alleviating Normality Bias in PPG-to-ABP Reconstruction via Ordered Prototype Latent Refinement
Abstract
Continuous arterial blood pressure (ABP) waveforms enable high-resolution hemodynamic monitoring but typically require invasive arterial lines. PPG-to-ABP reconstruction offers a noninvasive alternative, yet long-tailed BP distributions induce a systematic failure we term Normality Bias: predictions drift toward the normotensive mean, attenuating hypertensive peaks and elevating hypotensive troughs even when aggregate metrics appear strong. We formalize this bias through a stratified signed-error diagnostic and introduce two model-agnostic metrics: the Normality Bias Index (NBI), which captures monotonic regime-dependent drift, and TailBias, which quantifies bias at the clinically critical extremes. Across architecture families, these diagnostics reveal that normality bias is pervasive. We propose Ordered Prototype Latent Refinement (OPLR), a representation-level remedy that imposes an ordered regime geometry (Low < Normal < High) on the latent space and performs routing-guided prototype–token refinement before decoding. This design targets three coupled failure modes of normality bias: regime absorption (rare-regime segments encoded near the dominant Normal mode), routing monopoly (routing collapsing onto the Normal prototype), and attenuation of extreme waveform amplitudes. Under strict subject-wise, calibration-free evaluation on PulseDB and zero-shot transfer to two additional cohorts, OPLR achieves the lowest NBI and TailBias among all compared models and the lowest RMSE and MAE in every regime, including the aggregate, with gains significant under subject-level paired tests on PulseDB. The diagnostics are robust to binning choices, and the regime-level results are stable under shifts of the reporting boundaries. Matched-backbone ablations isolate the ordered prototype as the component that moves the bias metrics, show that the advantage is not explained by additional inputs alone, and find that data- and loss-level long-tailed remedies on the same backbone reduce it only marginally.
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