arXiv:2606. 12378v1 Announce Type: cross Abstract: Physiological awareness is important for service, social, and assistive robots that interact with humans in everyday environments.
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The paper introduces Heartian, a physiology‑aware framework that augments Gaussian head avatars with cardiac‑cycle‑dependent albedo modulation, enabling the encoding of remote photoplethysmography (rPPG) signals. By supervising with synchronized contact PPG, the method models the cardiac waveform as a sum of two Gaussians and learns per‑frame spatial residuals via a lightweight MLP. Experiments on 152 stationary recordings from UBFC‑rPPG, PURE, and MMPD show heart‑rate estimation errors as low as 0.29 bpm MAE and 0.38 % MAPE, while preserving reconstruction quality with negligible PSNR loss.
Gaussian head avatars typically model intrinsic facial appearance as temporally static, omitting subtle cardiac-induced skin-color variation. We propose $\unicode{x1F493}$Heartian, a physiology-aware...
EgoHRV is a method that estimates heart rate variability (HRV) and heart rate (HR) from the gaze cameras in egocentric headsets. It uses a 3D backbone and a low–high decomposition module to extract the blood volume pulse signal from gaze video, and aligns frequency‑domain representations of contact‑based and camera‑derived signals through cross‑domain pretraining. The approach achieves state‑of‑the‑art accuracy for HR and HRV estimation and, when integrated into EgoExo4D’s proficiency estimator, improves accuracy by 17.8%.
arXiv:2608. 15831v1 Announce Type: cross Abstract: Remote photoplethysmography (rPPG) enables non-contact heart rate (HR) monitoring from facial videos, but RGB-only methods are vulnerable to illumination changes, motion artifacts, and skin-tone-dependent optical reflectance.
The paper investigates the use of thermal infrared video to non‑invasively monitor cardiorespiratory and sudomotor activity in industrial human‑machine interfaces. It presents a signal‑processing pipeline that tracks facial regions, aggregates thermal signals, and separates slow sudomotor trends from faster heart‑rate and breathing‑rate components. Experiments on 31 driver‑monitoring sessions show that thermal imaging can estimate heart rate, breathing rate, and electrodermal activity with reasonable accuracy, while highlighting challenges such as ROI selection, polarity changes, latency, and subject variability.
arXiv:2609.36607v1 Announce Type: new Abstract: Remote photoplethysmography (rPPG) offers a promising non-contact solution for heart rate monitoring, yet its real-world robustness is fundamentally li...