AIMC Topic: Sleep

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Personalized Machine Learning Intervention to Improve Sleep Quality Using Wearable Technology in Healthy Middle-Aged Adults From Mexico City: Protocol for a Pilot Randomized Controlled Trial.

JMIR research protocols
BACKGROUND: In 2019, global sleep surveys reported that 80% of adults want to improve their sleep quality, and in 2021, 45% were reported to be dissatisfied with their sleep. In 2025, among American adults, 37% reported sleep dissatisfaction and 38% ...

Generation of a Free-Living Ground-Truth Validation Dataset for Wearable Measures of Physical Activity, Sedentary Behavior, Sleep, and Heart Rate in Adults (OxWEARS): Protocol for a Cross-Sectional Study.

JMIR research protocols
BACKGROUND: Wearable devices enable continuous measurement of physical activity, sedentary behavior, sleep, and heart rate under free-living conditions. However, most validation studies rely on small, homogeneous samples; are conducted under laborato...

Detection of cortical arousals in sleep using multimodal wearable sensors and machine learning.

Scientific reports
Cortical arousals are brief brain activations that disrupt sleep continuity and contribute to cardiovascular, cognitive, and behavioral impairments. Although polysomnography is the gold standard for arousal detection, its cost and complexity limit us...

Identifying daily-living features related to loneliness: A causal machine learning approach.

PloS one
BACKGROUND: Loneliness is a distressing feeling that influences well-being. Immigrants' experience of acculturation to a new dominant culture places them at risk for maladaptive behaviors and daily rhythms leading to loneliness. Identifying daily-liv...

Smartwatch-Derived Digital Phenotypes Relate to Psychopathology Dimensions in Patients With Psychotic Spectrum Disorders: Longitudinal Observational Study.

JMIR mental health
BACKGROUND: Digital phenotyping refers to the objective measurement of human behavior via devices such as smartphones or watches and constitutes a promising advancement in personalized medicine. Digital phenotypes derived from heart rate, mobility, o...

Oura Ring Behavioral Feedback Intervention for Alcohol Reduction in Young Adults: User Experience Evaluation of a Pilot Randomized Trial.

Journal of medical Internet research
BACKGROUND: Wearable fitness technologies, like the Oura Ring (Oura Health Oy), provide physiological metrics, like sleep and heart rate data, to a growing user base of young adults. However, these technologies and connected mobile apps do not measur...

Can weekend catch-up sleep repay the sleep debt? Balancing short-term relief with long-term risks.

Sleep & breathing = Schlaf & Atmung
BACKGROUND: Sleep insufficiency, driven by modern fast-paced lifestyles, contributes to the accumulation of "sleep debt." Many individuals attempt to compensate through weekend catch-up sleep (WCS). While WCS may temporarily relieve fatigue and enhan...

Automated Classification of Sleep-Wake States and Seizures in Mice.

eNeuro
Sleep-wake states bidirectionally interact with epilepsy and seizures, but the mechanisms are unknown. A barrier to comprehensive characterization and the study of mechanisms has been the difficulty of annotating large chronic recording datasets. To ...

Advancing sleep health equity through deep learning on large-scale nocturnal respiratory signals.

Nature communications
Sleep disorders affect billions globally, yet diagnostic access remains limited by healthcare resource constraints. Here, we develop a deep learning framework that analyzes respiratory signals for remote sleep health monitoring, trained on 15,785 nig...

EEG based classification of sleep cyclic alternating patterns using frequency driven forward ternary encoding.

Sleep & breathing = Schlaf & Atmung
PURPOSE: Cyclic alternating patterns (CAP) of sleep can be observed through electroencephalogram (EEG) signals. Analyzing CAP can provide valuable insights into different abnormalities relating to sleep. CAP comprises of two phases: A and B, characte...