Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

wav2sleep: A Unified Multi-Modal Approach to Sleep Stage Classification from Physiological Signals

Carter JF. and TARASSENKO L., (2025), Machine Learning for Health (ML4H) 2024

Remote vital sign monitoring in admission avoidance hospital at home

FARMER A. et al, (2024), Journal of the American Medical Directors Association

SleepVST: Sleep Staging from Near-Infrared Video Signals using Pre-Trained Transformers

Carter JF. et al, (2024), Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 12479 - 12489

wav2sleep: A Unified Multi-Modal Approach to Sleep Stage Classification from Physiological Signals

Carter JF. and Tarassenko L., (2024), Proceedings of Machine Learning Research, 259, 186 - 202

Deep Learning-Enabled Sleep Staging From Vital Signs and Activity Measured Using a Near-Infrared Video Camera

Carter J. et al, (2023), IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2023-June, 5940 - 5949

Longitudinal Monitoring of Progressive Supranuclear Palsy using Body-Worn Movement Sensors.

Sotirakis C. et al, (2022), Movement disorders : official journal of the Movement Disorder Society, 37, 2263 - 2271

Load More