1 citations · 1 across the 5 of their papers we have counts for
5 papers
Learning Human Health and Diseases from 24-hour Wrist Movement
Yong Wang, Dylan McGagh, Katya Broomberg +21
Much of human health and function unfolds beyond the clinic, through the movements of everyday life. Wrist-worn accelerometers capture these movements continuously, yet their rich…
Next-Token Prediction Learns Generalisable Representations of Sleep Physiology
Jonathan F. Carter, Lionel Tarassenko
Foundation models offer a promising route to compress multi-modal physiological signals into compact representations of human health, with broad applications across sleep medicine,…
wav2sleep: A Unified Multi-Modal Approach to Sleep Stage Classification from Physiological Signals
Jonathan F. Carter, Lionel Tarassenko
Accurate classification of sleep stages from less obtrusive sensor measurements such as the electrocardiogram (ECG) or photoplethysmogram (PPG) could enable important applications…
SleepVST: Sleep Staging from Near-Infrared Video Signals using Pre-Trained Transformers
Jonathan F. Carter, João Jorge, Oliver Gibson +1
Advances in camera-based physiological monitoring have enabled the robust, non-contact measurement of respiration and the cardiac pulse, which are known to be indicative of the sle…
Deep Learning-Enabled Sleep Staging From Vital Signs and Activity Measured Using a Near-Infrared Video Camera
Jonathan Carter, João Jorge, Bindia Venugopal +2
Conventional sleep monitoring is time-consuming, expensive and uncomfortable, requiring a large number of contact sensors to be attached to the patient. Video data is commonly reco…