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Sleep

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Recognition of activities of daily living in healthy subjects using two ad-hoc classifiers.

Biomedical engineering online
BACKGROUND: Activities of daily living (ADL) are important for quality of life. They are indicators of cognitive health status and their assessment is a measure of independence in everyday living. ADL are difficult to reliably assess using questionna...

Summarizing and visualizing structural changes during the evolution of biomedical ontologies using a Diff Abstraction Network.

Journal of biomedical informatics
Biomedical ontologies are a critical component in biomedical research and practice. As an ontology evolves, its structure and content change in response to additions, deletions and updates. When editing a biomedical ontology, small local updates may ...

Sleep efficiency in community-dwelling persons living with dementia: exploratory analysis using machine learning.

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine
STUDY OBJECTIVES: Sleep disturbances lead to negative health outcomes and caregiver burden, particularly in community settings. This study aimed to investigate a predictive model for sleep efficiency and its associated features in older adults living...

Supervised machine learning on electrocardiography features to classify sleep in noncritically ill children.

Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine
STUDY OBJECTIVES: Despite frequent sleep disruption in the pediatric intensive care unit, bedside sleep monitoring in real time is currently not available. Supervised machine learning applied to electrocardiography data may provide a solution, becaus...

What radio waves tell us about sleep!

Sleep
The ability to assess sleep at home, capture sleep stages, and detect the occurrence of apnea (without on-body sensors) simply by analyzing the radio waves bouncing off people's bodies while they sleep is quite powerful. Such a capability would allow...

MS Pattern Explorer: interactive visual exploration of temporal activity patterns for multiple sclerosis.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: This article describes the design and evaluation of MS Pattern Explorer, a novel visual tool that uses interactive machine learning to analyze fitness wearables' data. Applied to a clinical study of multiple sclerosis (MS) patients, the t...

STConvSleepNet: A Spatiotemporal Convolutional Network for Sleep Posture Detection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Sleep posture, intricately connected to sleep health, has emerged as a crucial focus in sleep medicine. Studies have associated the supine posture with increased frequency and severity of obstructive sleep apnea (OSA), while lateral postures may miti...

Predicting Sleep Quality via Unsupervised Learning of Cardiac Activity.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
While highly important for a person's mood, productivity, and physical performance, perceived sleep quality is challenging to model and, thus, predict with passive means such as physiological and behavioral signals alone. In this paper, we propose a ...

Machine Learning Model Combining Ventilatory, Hypoxic, Arousal Domains Across Sleep Better Predicts Adverse Consequences of Obstructive Sleep Apnea.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Obstructive sleep apnea(OSA) severity is currently assessed clinically using the apnea-hypopnea index (AHI), which is inconsistently associated with short- and long-term outcomes. Ventilatory, hypoxic, and arousal domains are known to exhibit abnorma...

Laying the Foundation: Modern Transformers for Gold-Standard Sleep Analysis and Beyond.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Accurate sleep assessment is critical to the practice of sleep medicine and sleep research. The recent availability of large quantities of publicly available sleep data, alongside recent breakthroughs in AI like transformer architectures, present nov...