Long-Horizon Physiological Analysis via Native Calibration of a Multimodal Waveform Foundation Model

Bedside monitors record PPG and ECG waveforms continuously, but laboratory values such as hemoglobin and potassium are measured only when blood is drawn: hours apart in intensive care, months apart between emergency-department visits. We study long-horizon physiological analysis: estimating from the waveforms how a lab value has changed since the previous draw. Our method, native calibration, uses the patient's own history: each earlier draw provides a measured value and a waveform recorded at the same time. It estimates the current value as an earlier measured value plus the change read from the current and past waveforms, both embedded by a frozen waveform foundation model (FM). We also introduce a new multimodal FM, a transformer pretrained without labels to relate ECG and PPG and to match a patient's PPG across time. We evaluate on two kinds of task: 1) tracking lab changes, namely hemoglobin between emergency visits and potassium within intensive-care stays; and 2) reading values from the current waveform alone, namely first-draw emergency labs, intra-operative haemodynamics and 24 standard PPG benchmark tasks. On held-out patients, native calibration improves the estimated change in both hemoglobin and potassium over strong non-waveform baselines, and part of this gain is specific to the patient: it shrinks when the patient's past waveforms are replaced by those of other patients with the same lab values. Our FM achieves state-of-the-art results on first-draw labs and the standard PPG tasks, ranking first among ten encoders, and is competitive with the best public encoder on intra-operative haemodynamics.