Designing wearable systems for sleep detection and staging is extremely challenging due to
the numerous constraints associated with sensing, usability, accuracy, and regulatory …

Classifying sleep stages in real-time represents considerable potential, for instance in
enabling interactive noise masking in noisy environments when persons are in a state of …

Unobtrusive home sleep monitoring using wrist-worn wearable photoplethysmography
(PPG) could open the way for better sleep disorder screening and health monitoring …

Healthcare is expected to increasingly shift care out of inpatient settings thanks to wearable
monitoring systems. Photoplethysmography (PPG) is an optical technique already integrated …

Background and objective Graph neural networks (GNNs) are widely used for automatic
sleep staging. However, the majority of GNNs are based on spectral approaches, as far as …

This article presents an overview of the advancements that have been made in the use of
photoplethysmography (PPG) for unobtrusive sleep studies. PPG is included in the quickly …

Automatic sleep stage classification is vital for evaluating the quality of sleep.
Conventionally, sleep is monitored using multiple physiological sensors that are …

Sleep is vital to many processes involved in the well-being and health of children; however,
it is estimated that 80% of children with Rett syndrome suffer from sleep disorders. Caregiver …

Photoplethysmography (PPG) is a simple low-cost optics technique that can be used to
detect blood volume changes in the microvascular bed of tissue with each heartbeat. It is …

Sleep disruption is common in pediatric intensive care unit (PICU) patients, but measuring
sleep in this population is challenging. We aimed to evaluate the utility of actigraphy for …