A review of automated sleep stage scoring based on physiological signals for the new millennia
Abstract Background and Objective Sleep is an important part of our life. That importance is
highlighted by the multitude of health problems which result from sleep disorders. Detecting …
highlighted by the multitude of health problems which result from sleep disorders. Detecting …
Automatic diagnosis of sleep apnea from biomedical signals using artificial intelligence techniques: Methods, challenges, and future works
P Moridian, A Shoeibi, M Khodatars… - … : Data Mining and …, 2022 - Wiley Online Library
Apnea is a sleep disorder that stops or reduces airflow for a short time during sleep. Sleep
apnea may last for a few seconds and happen for many while sleeping. This reduction in …
apnea may last for a few seconds and happen for many while sleeping. This reduction in …
A deep transfer learning approach for wearable sleep stage classification with photoplethysmography
Unobtrusive home sleep monitoring using wrist-worn wearable photoplethysmography
(PPG) could open the way for better sleep disorder screening and health monitoring …
(PPG) could open the way for better sleep disorder screening and health monitoring …
Sleep stage classification with ECG and respiratory effort
Automatic sleep stage classification with cardiorespiratory signals has attracted increasing
attention. In contrast to the traditional manual scoring based on polysomnography, these …
attention. In contrast to the traditional manual scoring based on polysomnography, these …
[HTML][HTML] Studying the effect of long COVID-19 infection on sleep quality using wearable health devices: observational study
Background Patients with COVID-19 have increased sleep disturbances and decreased
sleep quality during and after the infection. The current published literature focuses mainly …
sleep quality during and after the infection. The current published literature focuses mainly …
Validation of photoplethysmography-based sleep staging compared with polysomnography in healthy middle-aged adults
P Fonseca, T Weysen, MS Goelema, EIS Møst… - Sleep, 2017 - academic.oup.com
Abstract Study Objectives: To compare the accuracy of automatic sleep staging based on
heart rate variability measured from photoplethysmography (PPG) combined with body …
heart rate variability measured from photoplethysmography (PPG) combined with body …
Sleep staging based on signals acquired through bed sensor
JM Kortelainen, MO Mendez… - IEEE Transactions …, 2010 - ieeexplore.ieee.org
We describe a system for the evaluation of the sleep macrostructure on the basis of Emfit
sensor foils placed into bed mattress and of advanced signal processing. The signals on …
sensor foils placed into bed mattress and of advanced signal processing. The signals on …
Adaptive heartbeat modeling for beat-to-beat heart rate measurement in ballistocardiograms
J Paalasmaa, H Toivonen… - IEEE journal of biomedical …, 2014 - ieeexplore.ieee.org
We present a method for measuring beat-to-beat heart rate from ballistocardiograms
acquired with force sensors. First, a model for the heartbeat shape is adaptively inferred from …
acquired with force sensors. First, a model for the heartbeat shape is adaptively inferred from …
An evaluation of cardiorespiratory and movement features with respect to sleep-stage classification
T Willemen, D Van Deun, V Verhaert… - IEEE journal of …, 2013 - ieeexplore.ieee.org
Polysomnography (PSG) is considered the gold standard to assess sleep accurately, but it
can be expensive, time-consuming, and uncomfortable, specifically in long-term sleep …
can be expensive, time-consuming, and uncomfortable, specifically in long-term sleep …
Sleep/wake measurement using a non‐contact biomotion sensor
P De Chazal, N Fox, E O'HARE… - Journal of sleep …, 2011 - Wiley Online Library
We studied a novel non‐contact biomotion sensor, which has been developed for identifying
sleep/wake patterns in adult humans. The biomotion sensor uses ultra low‐power reflected …
sleep/wake patterns in adult humans. The biomotion sensor uses ultra low‐power reflected …