[HTML][HTML] Wireless EEG: A survey of systems and studies

G Niso, E Romero, JT Moreau, A Araujo, LR Krol - NeuroImage, 2023 - Elsevier
The popular brain monitoring method of electroencephalography (EEG) has seen a surge in
commercial attention in recent years, focusing mostly on hardware miniaturization. This has …

[HTML][HTML] The future of sleep health: a data-driven revolution in sleep science and medicine

I Perez-Pozuelo, B Zhai, J Palotti, R Mall… - NPJ digital …, 2020 - nature.com
In recent years, there has been a significant expansion in the development and use of multi-
modal sensors and technologies to monitor physical activity, sleep and circadian rhythms …

Sleeptransformer: Automatic sleep staging with interpretability and uncertainty quantification

H Phan, K Mikkelsen, OY Chén, P Koch… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Background: Black-box skepticism is one of the main hindrances impeding deep-learning-
based automatic sleep scoring from being used in clinical environments. Methods: Towards …

SeqSleepNet: end-to-end hierarchical recurrent neural network for sequence-to-sequence automatic sleep staging

H Phan, F Andreotti, N Cooray… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Automatic sleep staging has been often treated as a simple classification problem that aims
at determining the label of individual target polysomnography epochs one at a time. In this …

XSleepNet: Multi-view sequential model for automatic sleep staging

H Phan, OY Chén, MC Tran, P Koch… - … on Pattern Analysis …, 2021 - ieeexplore.ieee.org
Automating sleep staging is vital to scale up sleep assessment and diagnosis to serve
millions experiencing sleep deprivation and disorders and enable longitudinal sleep …

[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 …

[HTML][HTML] Automatic sleep staging of EEG signals: recent development, challenges, and future directions

H Phan, K Mikkelsen - Physiological Measurement, 2022 - iopscience.iop.org
Modern deep learning holds a great potential to transform clinical studies of human sleep.
Teaching a machine to carry out routine tasks would be a tremendous reduction in workload …

Design of hydrogel-based wearable EEG electrodes for medical applications

JC Hsieh, Y Li, H Wang, M Perz, Q Tang… - Journal of Materials …, 2022 - pubs.rsc.org
The electroencephalogram (EEG) is considered to be a promising method for studying brain
disorders. Because of its non-invasive nature, subjects take a lower risk compared to some …

Towards more accurate automatic sleep staging via deep transfer learning

H Phan, OY Chén, P Koch, Z Lu… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Background: Despite recent significant progress in the development of automatic sleep
staging methods, building a good model still remains a big challenge for sleep studies with a …

Agreement between actigraphic and polysomnographic measures of sleep in adults with and without chronic conditions: a systematic review and meta-analysis

S Conley, A Knies, J Batten, G Ash, B Miner… - Sleep medicine …, 2019 - Elsevier
Wrist actigraphy (ACT) may overestimate sleep and underestimate wake, and the agreement
may be lower in people with chronic conditions who often have poor sleep and low activity …