[HTML][HTML] 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 …

Automatic sleep stage classification: From classical machine learning methods to deep learning

RN Sekkal, F Bereksi-Reguig… - … Signal Processing and …, 2022 - Elsevier
Background and objectives The classification of sleep stages is a preliminary exam that
contributes to the diagnosis of possible sleep disorders. However, it is a tedious and time …

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 …

[HTML][HTML] Relationship between major depression symptom severity and sleep collected using a wristband wearable device: multicenter longitudinal observational …

Y Zhang, AA Folarin, S Sun, N Cummins… - JMIR mHealth and …, 2021 - mhealth.jmir.org
Background Sleep problems tend to vary according to the course of the disorder in
individuals with mental health problems. Research in mental health has associated sleep …

A novel pedal musculoskeletal response based on differential spatio-temporal LSTM for human activity recognition

H Wu, Z Zhang, X Li, K Shang, Y Han, Z Geng… - Knowledge-Based …, 2023 - Elsevier
Human activity recognition (HAR) with wearable devices has shown superior usability in
everyday life tracking and healthcare monitoring in recent years. To solve the existing …

[HTML][HTML] Sleep classification using Consumer Sleep Technologies and AI: A review of the current landscape

S Djanian, A Bruun, TD Nielsen - Sleep Medicine, 2022 - Elsevier
Classifying sleep stages in real-time represents considerable potential, for instance in
enabling interactive noise masking in noisy environments when persons are in a state of …

Transferable self-supervised instance learning for sleep recognition

A Zhao, Y Wang, J Li - IEEE Transactions on Multimedia, 2022 - ieeexplore.ieee.org
Although the importance of sleep is increasingly recognized, the lack of general and
transferable algorithms hinders scalable sleep assessment in healthy persons and those …

[HTML][HTML] Lower limb kinematics trajectory prediction using long short-term memory neural networks

A Zaroug, DTH Lai, K Mudie, R Begg - Frontiers in Bioengineering …, 2020 - frontiersin.org
This study determined whether the kinematics of lower limb trajectories during walking could
be extrapolated using long short-term memory (LSTM) neural networks. It was hypothesised …

Non-invasive techniques for monitoring different aspects of sleep: A comprehensive review

Z Hussain, QZ Sheng, WE Zhang, J Ortiz… - ACM Transactions on …, 2022 - dl.acm.org
Quality sleep is very important for a healthy life. Nowadays, many people around the world
are not getting enough sleep, which has negative impacts on their lifestyles. Studies are …

[HTML][HTML] An automated wavelet-based sleep scoring model using EEG, EMG, and EOG signals with more than 8000 subjects

M Sharma, A Yadav, J Tiwari, M Karabatak… - International Journal of …, 2022 - mdpi.com
Human life necessitates high-quality sleep. However, humans suffer from a lower quality of
life because of sleep disorders. The identification of sleep stages is necessary to predict the …