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Sleep spindle abnormalities related to Alzheimer's disease: a systematic mini-review
Accumulating evidence supports a bidirectional relationship between sleep disruption and
Alzheimer's disease (AD) pathology. Among various sleep electroencephalography …
Alzheimer's disease (AD) pathology. Among various sleep electroencephalography …
Sleep spindles as an electrographic element: description and automatic detection methods
D Coppieters't Wallant, P Maquet, C Phillips - Neural plasticity, 2016 - Wiley Online Library
Sleep spindle is a peculiar oscillatory brain pattern which has been associated with a
number of sleep (isolation from exteroceptive stimuli, memory consolidation) and individual …
number of sleep (isolation from exteroceptive stimuli, memory consolidation) and individual …
Sleep-spindle detection: crowdsourcing and evaluating performance of experts, non-experts and automated methods
Sleep spindles are discrete, intermittent patterns of brain activity observed in human
electroencephalographic data. Increasingly, these oscillations are of biological and clinical …
electroencephalographic data. Increasingly, these oscillations are of biological and clinical …
Sleep oscillation-specific associations with Alzheimer's disease CSF biomarkers: novel roles for sleep spindles and tau
Background Based on associations between sleep spindles, cognition, and sleep-
dependent memory processing, here we evaluated potential relationships between levels of …
dependent memory processing, here we evaluated potential relationships between levels of …
A deep learning approach for real-time detection of sleep spindles
Objective. Sleep spindles have been implicated in memory consolidation and synaptic
plasticity during NREM sleep. Detection accuracy and latency in automatic spindle detection …
plasticity during NREM sleep. Detection accuracy and latency in automatic spindle detection …
Detection of K-complexes and sleep spindles (DETOKS) using sparse optimization
Background This paper addresses the problem of detecting sleep spindles and K-
complexes in human sleep EEG. Sleep spindles and K-complexes aid in classifying stage 2 …
complexes in human sleep EEG. Sleep spindles and K-complexes aid in classifying stage 2 …
Stage-independent, single lead EEG sleep spindle detection using the continuous wavelet transform and local weighted smoothing
Sleep spindles are critical in characterizing sleep and have been associated with cognitive
function and pathophysiological assessment. Typically, their detection relies on the …
function and pathophysiological assessment. Typically, their detection relies on the …
DOSED: A deep learning approach to detect multiple sleep micro-events in EEG signal
Background Electroencephalography (EEG) monitors brain activity during sleep and is used
to identify sleep disorders. In sleep medicine, clinicians interpret raw EEG signals in so …
to identify sleep disorders. In sleep medicine, clinicians interpret raw EEG signals in so …
The case for using digital EEG analysis in clinical sleep medicine
M Younes - Sleep Science and Practice, 2017 - Springer
Abstract Evaluation of sleep in clinical polysomnograms continues to rely almost exclusively
on visual scoring that implements rules proposed by Rechtschaffen and Kales nearly 50 …
on visual scoring that implements rules proposed by Rechtschaffen and Kales nearly 50 …
A deep learning architecture to detect events in EEG signals during sleep
Electroencephalography (EEG) during sleep is used by clinicians to evaluate various
neurological disorders. In sleep medicine, it is relevant to detect macro-events (≥ 10s) such …
neurological disorders. In sleep medicine, it is relevant to detect macro-events (≥ 10s) such …