Annotated drowsiness detection dataset captured using Raspberry Pi 5. [PDF]
Liawatimena S, Isworo N.
europepmc +1 more source
ABSTRACT Sleep troubles and respiratory and allergic health issues are associated in children, but the timeline of their association is overlooked. This study investigates the associations between sleep patterns at age 1 and respiratory and allergic multi‐trajectories (RespA‐MTG) between ages 1 and 5.5, and the associations between these multi ...
Daniele Saade +10 more
wiley +1 more source
Enhanced smart commuting with artificial intelligence for intelligent health and safety monitoring in school buses. [PDF]
Hossam H +8 more
europepmc +1 more source
Hypoxic Burden in Children With Sleep‐Disordered Breathing: Determinants and Correlates
ABSTRACT Hypoxic burden (HB) is an emerging metric for quantifying intermittent hypoxia associated with sleep apnea, offering potential advantages over traditional measures such as the apnea‐hypopnea index (AHI). This study evaluated the distribution and clinical significance of non‐respiratory event‐specific HB in children and adolescents with ...
Plamen Bokov +2 more
wiley +1 more source
Targeting Expanded CUG and CTG Repeats as a Therapeutic Approach for Myotonic Dystrophy Type 1 (DM1)
DM1 is an RNA gain‐of‐function disease caused by CTG repeat expansion, producing toxic r(CUG)exp RNA that sequesters MBNL1 and impairs splicing. This review covers the field of CUG and CTG ligands identified or rationally designed as DM1 drug candidates, highlighting their molecular design, RNA‐ or DNA‐binding modes, in vitro affinities and ...
Camille Richagneux, Anton Granzhan
wiley +1 more source
Quantitative evaluation of low-frequency oscillations using real-time phase-contrast MRI during drowsiness. [PDF]
Zhu H +6 more
europepmc +1 more source
An Overview of Deep Learning Techniques for Big Data IoT Applications
Reviews deep learning integration with cloud, fog, and edge computing in IoT architectures. Examines model suitability across IoT applications, key challenges, and emerging trends Provides a comparative analysis to guide future deep learning research in IoT environments.
Gagandeep Kaur +2 more
wiley +1 more source
A Multidimensional Benchmark of Public EEG Datasets for Driver State Monitoring in Brain-Computer Interfaces. [PDF]
Ammar S, Triki N, Karray M, Ksantini M.
europepmc +1 more source
A Comprehensive Review of Unobtrusive Biosensing in Intelligent Vehicles: Sensors, Algorithms, and Integration Challenges. [PDF]
Maleki Varnosfaderani S +2 more
europepmc +1 more source
YOLO-FDCL: Improved YOLOv8 for Driver Fatigue Detection in Complex Lighting Conditions. [PDF]
Liu G, Wu K, Lan W, Wu Y.
europepmc +1 more source

