AIMC Topic: Sleep
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Beyond accuracy: a framework for evaluating algorithmic bias and performance, applied to automated sleep scoring.
Scientific reports
Jul 1, 2025
Recent advancements in artificial intelligence (AI) have significantly improved sleep-scoring algorithms, bringing their performance close to the theoretical limit of approximately 80%, which aligns with inter-scorer agreement levels. While this sugg...
A novel feature extractor based on constrained cross network for detecting sleep state.
Scientific reports
Jul 1, 2025
With increasing awareness of healthy living and social pressure, more and more people have begun to pay attention to their sleep state. Most existing methods that utilize wrist-worn devices data for detection rely on heuristic algorithms or tradition...
Personalized machine learning models for noninvasive hypoglycemia detection in people with type 1 diabetes using a smartwatch: Insights into feature importance during waking and sleeping times.
PloS one
Jun 25, 2025
Hypoglycemia is a major challenge for people with diabetes. Therefore, glycemic monitoring is an important aspect of diabetes management. However, current methods such as finger pricking and continuous glucose monitoring systems (CGMS) are invasive, ...
A skin-interfaced wireless wearable device and data analytics approach for sleep-stage and disorder detection.
Proceedings of the National Academy of Sciences of the United States of America
Jun 6, 2025
Accurate identification of sleep stages and disorders is crucial for maintaining health, preventing chronic conditions, and improving diagnosis and treatment. Direct respiratory measurements, as key biomarkers, are missing in traditional wrist- or fi...
The two ends of the spectrum: comparing chronic schizophrenia and premorbid latent schizotypy by actigraphy.
BMC psychiatry
May 24, 2025
Motor activity alterations are key symptoms of psychiatric disorders like schizophrenia. Actigraphy, a non-invasive monitoring method, shows promise in early identification. This study characterizes Positive Schizotypy Factor (PSF) and Chronic Schizo...
Data-driven sleep structure deciphering based on cardiorespiratory signals.
Computer methods and programs in biomedicine
Apr 23, 2025
BACKGROUND AND OBJECTIVE: Cardiorespiratory signals provide a novel perspective for understanding sleep structure through the physiological mechanism of cardiopulmonary coupling. This mechanism divides the coupling spectrum into high-frequency (HF) a...
Detecting arousals and sleep from respiratory inductance plethysmography.
Sleep & breathing = Schlaf & Atmung
Apr 11, 2025
PURPOSE: Accurately identifying sleep states (REM, NREM, and Wake) and brief awakenings (arousals) is essential for diagnosing sleep disorders. Polysomnography (PSG) is the gold standard for such assessments but is costly and requires overnight monit...
Neural models for detection and classification of brain states and transitions.
Communications biology
Apr 11, 2025
Exploring natural or pharmacologically induced brain dynamics, such as sleep, wakefulness, or anesthesia, provides rich functional models for studying brain states. These models allow detailed examination of unique spatiotemporal neural activity patt...
CHMMConvScaleNet: a hybrid convolutional neural network and continuous hidden Markov model with multi-scale features for sleep posture detection.
Scientific reports
Apr 10, 2025
Sleep posture, a vital aspect of sleep wellness, has become a crucial focus in sleep medicine. Studies show that supine posture can lead to a higher occurrence of obstructive sleep apnea, while lateral posture might reduce it. For bedridden patients,...
Personalized Health Prediction AI Models Using Transfer Learning and Strategic Overfitting on Wearable Device Data.
Journal of medical systems
Apr 9, 2025
The increasing availability of wearable device data provides an opportunity for developing personalized models for health monitoring and condition prediction. Unlike conventional approaches that rely on pooled data from diverse individuals, our study...
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