129 citations · 260 across the 7 of their papers we have counts for
7 papers
UDAMA: Unsupervised Domain Adaptation through Multi-discriminator Adversarial Training with Noisy Labels Improves Cardio-fitness Prediction
Yu Wu, Dimitris Spathis, Hong Jia +5
Deep learning models have shown great promise in various healthcare monitoring applications. However, most healthcare datasets with high-quality (gold-standard) labels are small-sc…
Turning Silver into Gold: Domain Adaptation with Noisy Labels for Wearable Cardio-Respiratory Fitness Prediction
Yu Wu, Dimitris Spathis, Hong Jia +5
Deep learning models have shown great promise in various healthcare applications. However, most models are developed and validated on small-scale datasets, as collecting high-quali…
Longitudinal cardio-respiratory fitness prediction through wearables in free-living environments
Dimitris Spathis, Ignacio Perez-Pozuelo, Tomas I. Gonzales +4
Cardiorespiratory fitness is an established predictor of metabolic disease and mortality. Fitness is directly measured as maximal oxygen consumption (VO), or indirectly as…
SelfHAR: Improving Human Activity Recognition through Self-training with Unlabeled Data
Chi Ian Tang, Ignacio Perez-Pozuelo, Dimitris Spathis +3
Machine learning and deep learning have shown great promise in mobile sensing applications, including Human Activity Recognition. However, the performance of such models in real-wo…
Self-supervised transfer learning of physiological representations from free-living wearable data
Dimitris Spathis, Ignacio Perez-Pozuelo, Soren Brage +2
Wearable devices such as smartwatches are becoming increasingly popular tools for objectively monitoring physical activity in free-living conditions. To date, research has primaril…
Learning Generalizable Physiological Representations from Large-scale Wearable Data
Dimitris Spathis, Ignacio Perez-Pozuelo, Soren Brage +2
To date, research on sensor-equipped mobile devices has primarily focused on the purely supervised task of human activity recognition (walking, running, etc), demonstrating limited…
Exploring Contrastive Learning in Human Activity Recognition for Healthcare
Chi Ian Tang, Ignacio Perez-Pozuelo, Dimitris Spathis +1
Human Activity Recognition (HAR) constitutes one of the most important tasks for wearable and mobile sensing given its implications in human well-being and health monitoring. Motiv…