Results 61 to 70 of about 4,944 (182)
ABSTRACT Children's ambulatory sleep is commonly measured via actigraphy. However, traditional actigraphy measured sleep (e.g., Sadeh algorithm) struggles to predict wake (i.e., specificity, values typically < 70) and cannot predict sleep stages. Long short‐term memory (LSTM) is a machine learning algorithm that may address these deficiencies.
R. Glenn Weaver +18 more
wiley +1 more source
Sleep in Functional Motor Disorders: A Case–Control Polysomnographic Study
ABSTRACT Sleep problems are frequent in functional motor disorders (FMDs). Surprisingly, objective correlates of impaired sleep and its relationship to other comorbidities have been understudied, and no polysomnographic study is available. We aimed to map the polysomnographic parameters in the context of self‐reported sleep and mood symptoms and search
Jiří Nepožitek +10 more
wiley +1 more source
ABSTRACT The ability to stay awake is crucial in life and can be compromised by insufficient sleep and medical conditions. Measuring alertness is important for evaluating driving ability and the Oxford Sleep Resistance (OSLER) test may provide an easy way for assessment.
Riikka Huhta +2 more
wiley +1 more source
Optimising Sleep Stage Detection Using a Minimal Non‐EEG Physiological Signal Set and Deep Learning
ABSTRACT Automatic sleep stage classification is essential for enabling non‐invasive, at‐home monitoring. However, current methods often rely on electroencephalogram (EEG) signals and ad‐hoc development approaches that limit reproducibility. We present a reproducible engineering framework for a deep learning model based on the U‐Net architecture that ...
Ángel Serrano Alarcón +4 more
wiley +1 more source
Human brain imaging with high‐density electroencephalography: Techniques and applications
Abstract figure legend Recent technological advances have elevated high‐density electroencephalography (hdEEG) to the status of a reliable neuroimaging tool. This technique measures scalp potentials with high temporal resolution, which permits the non‐invasive detection and analysis of neural oscillations.
Marco Marino, Dante Mantini
wiley +1 more source
ELECTROOCULOGRAPHY AND PATTERN ERG IN THE DIAGNOSTICS OF BEST’S VITELLIFORM DISTROPHY
Background. The aim of the study was to develop electrooculography in accordance with ISCEV standards and to test its accuracy in the diagnosis of Best’s disease, where the EOG results should be invariably abnormal in all affected members.
Martina Jarc-Vidmar +3 more
doaj
Corn leaf extract (CLE) contains a naturally occurring substance, 6‐methoxybenzoxazolinone (6‐MBOA). Structurally similar to melatonin, 6‐MBOA acts as a weak β‐adrenergic agonist with an affinity for melatonin receptors and stimulating melatonin synthesis.
Katarina M. Doma +4 more
wiley +1 more source
Wearable Near-Eye Tracking Technologies for Health: A Review
With the rapid advancement of computer vision, machine learning, and consumer electronics, eye tracking has emerged as a topic of increasing interest in recent years.
Lisen Zhu +7 more
doaj +1 more source
Early electroretinografic changes in elderly RA patients treated with hydroxychloroquine
Objective: to evaluate the effectiveness of fundoscopy, electrooculography, electroretinogram and visually evoked potentials in early detection of hydroxychloroquine retinal toxicity in RA patients and to evaluate the influence of patients’ age, drug ...
L. Cavagna +6 more
doaj +1 more source
Controlling the industrial robot model with the hybrid BCI based on EOG and eye tracking
The article describes the design process of building a hybrid brain-computer interface based on Electrooculography (EOG) and centre eye tracking.
Kubacki Arkadiusz, Jakubowski Arkadiusz
doaj +1 more source

