arXiv:2607. 05230v1 Announce Type: new Abstract: Pre-term infants are susceptible to potentially harmful apnoea-related cessations of breathing due to immature respiratory control.
Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.
Pre-term infants are susceptible to potentially harmful apnoea-related cessations of breathing due to immature respiratory control. However, reliable respiratory monitoring in the neonatal intensive care unit (NICU) remains challenging because motion artefacts, sensor displacement, and skin fragility can compromise contact-based measurements.
Apnoea of prematurity is characterised by recurrent episodes of cessation of breathing and remains difficult to detect reliably using routinely monitored physiological signals in the Neonatal Intensive Care Unit (NICU). Existing bedside monitors rely primarily on respiratory rate and oxygen saturation thresholds, often generating high false-positive alarm rates and missing short or irregular events.
arXiv:2608. 05697v1 Announce Type: cross Abstract: Respiration provides a continuously available window into physiological state and behavior.
arXiv:2607. 06598v1 Announce Type: cross Abstract: Heart rate measurement is one of the key requirements for real-time health monitoring, in particular for health caring of elderly people.
arXiv:2608. 07759v1 Announce Type: cross Abstract: Cardiovascular AI models can classify clean elec- trocardiogram (ECG) signals, but real wearable signals change because of motion, breathing, posture, sensor contact, and true clinical deterioration.
Remote photoplethysmography (rPPG) estimates the blood volume pulse (BVP) signal from facial videos, enabling contact-free health monitoring. Conventional clip-wise approaches, which use video clips as input, require capturing over one hundred frames before inference, thus introducing several seconds of delay and hindering real-time use.