Results 121 to 130 of about 187,501 (315)

Current status and prospects of automatic sleep stages scoring: Review. [PDF]

Biomed Eng Lett, 2023
Gaiduk M, Serrano Alarcón Á, Seepold R, Martínez Madrid N.   +3 more
europepmc   +1 more source

Effects of gender and age on sleep EEG functional connectivity differences in subjects with mild difficulty falling asleep

Frontiers in Psychiatry
IntroductionDifficulty falling asleep place an increasing burden on society. EEG-based sleep staging is fundamental to the diagnosis of sleep disorder, and the selection of features for each sleep stage is a key step in the sleep analysis.
Xiaodong Luo, Bin Zhou, Jilong Shi, Gang Li, Yixia Zhu   +4 more
doaj   +1 more source

HARMLESS Early Warning System for Advanced Materials

Advanced Sustainable Systems, EarlyView.
The HARMLESS Early Warning System tackles Advanced Materials (AdMa) risk governance by providing a framework, organised in two tiers, underpinned with methods/tools to support risk assessors in the pre‐assessment preceding risk assessment. It allows for initial screening to identify AdMa with concerns considering exposure, hazards, sustainability and ...
Julia Prinz, Gregor Nagel, Susan Dekkers, Eugene P. van Someren, Véronique Adam, Veronica Di Battista, Blanca Suarez‐Merino, Wendel Wohlleben, Michael Persson, Anders Baun, Otmar Schmid, Andrea Haase   +11 more
wiley   +1 more source

Activation of Glutamatergic Neurons in the Supramammillary Nucleus Promotes the Recovery of Consciousness under Sevoflurane Anesthesia

Advanced Science, EarlyView.
Selective lesioning of SuM glutamatergic neurons promoted the induction of and delayed emergence from sevoflurane anesthesia and increased sevoflurane sensitivity. Optogenetic stimulation of SuM glutamatergic neurons or the SuM‐MS projection promoted behavioral arousal and cortical activation under steady‐state sevoflurane anesthesia and reduced the ...
Jiayan Li, Yehui Wu, Yihan Wang, Yumin Wu, Rong Hu, Si Long, Wenqi Huang, Liming Nie, Zhongxing Wang   +8 more
wiley   +1 more source

Combining Generative and Discriminative Neural Networks for Sleep Stages Classification [PDF]

arXiv, 2016
Sleep stages pattern provides important clues in diagnosing the presence of sleep disorder. By analyzing sleep stages pattern and extracting its features from EEG, EOG, and EMG signals, we can classify sleep stages. This study presents a novel classification model for predicting sleep stages with a high accuracy.
arxiv  

Differences in intestinal motility during different sleep stages based on long-term bowel sounds. [PDF]

Biomed Eng Online, 2023
Wang G, Chen Y, Liu H, Yu X, Han Y, Wang W, Kang H.   +6 more
europepmc   +1 more source

Periodic Leg Movements (PLM): Their Relationship to Sleep Stages [PDF]

, 1993
T. Pollmächer, Hartmut Schulz
openalex   +1 more source

Bilirubin Targeting WNK1 to Alleviate NLRP3‐Mediated Neuroinflammation

Advanced Science, EarlyView.
At physiological concentrations, bilirubin binds to the kinase domain of WNK1, thereby augmenting its activity and facilitating the phosphorylation of downstream SPAK/OSR1. This phosphorylation inhibits KCC2 activity, leading to elevate intracellular chloride levels in neurons.
Linfei Mao, Jiayu Lu, Quanjun Yang, Zhenqi Liu, Cuiping Wu, Bingbing Ke, Kaiyan Su, Haolin Yuan, Yaqi Cui, Yao Wang, Richard Salvi, Guang Yang, Shankai Yin, Feng Liu, Chunyan Li   +14 more
wiley   +1 more source

From Lab to Life: Self‐Powered Sweat Sensors and Their Future in Personal Health Monitoring

Advanced Science, EarlyView.
This review focuses on recent advances in self‐powered sweat sensors in personal health monitoring, including sweat sensors, energy harvesters, energy management, and their applications. It analyzes the difficulties and challenges in the research field of self‐powered sweat sensors and looks into the future direction of self‐powered sweat sensors from ...
Nan Gao, Guodong Xu, Gang Chang, Yuxiang Wu   +3 more
wiley   +1 more source

Multimodal Sleep Stage and Sleep Apnea Classification Using Vision Transformer: A Multitask Explainable Learning Approach [PDF]

arXiv
Sleep is an essential component of human physiology, contributing significantly to overall health and quality of life. Accurate sleep staging and disorder detection are crucial for assessing sleep quality. Studies in the literature have proposed PSG-based approaches and machine-learning methods utilizing single-modality signals.
arxiv