A systematic review of sensing technologies for wearable sleep staging

SA Imtiaz - Sensors, 2021 - mdpi.com
Designing wearable systems for sleep detection and staging is extremely challenging due to
the numerous constraints associated with sensing, usability, accuracy, and regulatory …

The 2023 wearable photoplethysmography roadmap

PH Charlton, J Allen, R Bailón, S Baker… - Physiological …, 2023 - iopscience.iop.org
Photoplethysmography is a key sensing technology which is used in wearable devices such
as smartwatches and fitness trackers. Currently, photoplethysmography sensors are used to …

Sleep stage classification from heart-rate variability using long short-term memory neural networks

M Radha, P Fonseca, A Moreau, M Ross, A Cerny… - Scientific reports, 2019 - nature.com
Automated sleep stage classification using heart rate variability (HRV) may provide an
ergonomic and low-cost alternative to gold standard polysomnography, creating possibilities …

Automated detection of sleep stages using deep learning techniques: A systematic review of the last decade (2010–2020)

HW Loh, CP Ooi, J Vicnesh, SL Oh, O Faust… - Applied Sciences, 2020 - mdpi.com
Sleep is vital for one's general well-being, but it is often neglected, which has led to an
increase in sleep disorders worldwide. Indicators of sleep disorders, such as sleep …

At-home wireless monitoring of acute hemodynamic disturbances to detect sleep apnea and sleep stages via a soft sternal patch

N Zavanelli, H Kim, J Kim, R Herbert, M Mahmood… - Science …, 2021 - science.org
Obstructive sleep apnea (OSA) affects more than 900 million adults globally and can create
serious health complications when untreated; however, 80% of cases remain undiagnosed …

Deep learning enables sleep staging from photoplethysmogram for patients with suspected sleep apnea

H Korkalainen, J Aakko, B Duce, S Kainulainen… - Sleep, 2020 - academic.oup.com
Abstract Study Objectives Accurate identification of sleep stages is essential in the diagnosis
of sleep disorders (eg obstructive sleep apnea [OSA]) but relies on labor-intensive …

Review of ECG detection and classification based on deep learning: Coherent taxonomy, motivation, open challenges and recommendations

SW Chen, SL Wang, XZ Qi, SM Samuri… - … Signal Processing and …, 2022 - Elsevier
An electrocardiogram (ECG) is one of the most promising approaches used for the detection
and classification of cardiovascular diseases (CVDs) in recent years. This work reviewed …

Deep learning for automated sleep staging using instantaneous heart rate

N Sridhar, A Shoeb, P Stephens, A Kharbouch… - NPJ digital …, 2020 - nature.com
Clinical sleep evaluations currently require multimodal data collection and manual review by
human experts, making them expensive and unsuitable for longer term studies. Sleep …

Methodologies and wearable devices to monitor biophysical parameters related to sleep dysfunctions: an overview

R De Fazio, V Mattei, B Al-Naami, M De Vittorio… - Micromachines, 2022 - mdpi.com
Sleep is crucial for human health from metabolic, mental, emotional, and social points of
view; obtaining good sleep in terms of quality and duration is fundamental for maintaining a …

Automatic sleep staging using heart rate variability, body movements, and recurrent neural networks in a sleep disordered population

P Fonseca, MM van Gilst, M Radha, M Ross, A Moreau… - Sleep, 2020 - academic.oup.com
Abstract Study Objectives To validate a previously developed sleep staging algorithm using
heart rate variability (HRV) and body movements in an independent broad cohort of …