Automated remote sleep monitoring needs uncertainty quantification.

Wearable electroencephalography devices emerge as a cost-effective and ergonomic alternative to gold-standard polysomnography, paving the way for better health monitoring and sleep disorder screening. Machine learning allows to automate sleep stage classification, but trust and reliability issues have hampered its adoption in clinical applications. Estimating uncertainty is a crucial factor in enhancing reliability by identifying regions of heightened and diminished confidence.

Acoustic Stimulation to Improve Slow-Wave Sleep in Alzheimer's Disease: A Multiple Night At-Home Intervention.

Objectives: To investigate the efficacy of closed-loop acoustic stimulation (CLAS) during slow-wave sleep (SWS) to enhance slow-wave activity (SWA) and SWS in patients with Alzheimer's disease (AD) across multiple nights and to explore associations between stimulation, participant characteristics, and individuals' SWS response.

Design: A 2-week, open-label at-home intervention study utilizing the DREEM2 headband to record sleep data and administer CLAS during SWS.

Setting And Participants: Fifteen older patients with AD (6 women, mean age: 76.

Physiological Profiling of Agitation in Dementia: Insights From Wearable Sensor Data.

Background And Objectives: The number of people with dementia is expected to triple to 152 million in 2050, with 90% having accompanying behavioral and psychological symptoms (BPSD). Agitation is among the most critical BPSD and can lead to decreased quality of life for people with dementia and their caregivers. This study aims to explore objective quantification of agitation in people with dementia by analyzing the relationships between physiological and movement data from wearables and observational measures of agitation.

Aggression Severity as a Predictor of Mortality in Dementia.

Objectives: In psychogeriatric units for patients with dementia and behavioral problems, aggression is prevalent. Predictions and timely interventions of aggression are essential to create a safe environment and prevent adverse outcomes. Our study aimed to determine whether aggression severity early during admission to these units could be used as an indicator of adverse outcomes.