Ying Wang's Research Lab
Biomedical Signals and Systems Research Group, University of Twente
Bringing Innovation to Life
Ying Wang's Research Lab
Our lab develops Physiology-Centred Scientific AI for understanding human physiology in daily life. We view physiological signals not as isolated measurements, but as observable manifestations of underlying physiological regulation systems that continuously adapt to internal and external perturbations.
Our research spans three interconnected layers. First, we investigate multimodal physiological signal interactions to understand how physiological information emerges across sensing modalities. Second, we combine forward physiological modelling and backward signal analysis to interpret the physiological meaning of digital biomarkers. Third, we develop computational physiological inference approaches, including hybrid AI methodologies, to infer hidden physiological regulation from observable signals.
By integrating multimodal sensing, physiological modelling, and artificial intelligence, we aim to bridge physiological signals and systems, enabling more interpretable, trustworthy, and personalised digital health technologies for disease prevention, health monitoring, and clinical decision support.
Research Framework & Relevant Key Publications
Layer 1. Multimodal Physiological Signal Interaction
How physiological signals interact and co-vary across modalities.
Layer 2. External-Internal: Bidirectional Signal–Mechanism Interpretation
Layer 3. Computational Physiological Inference: Physiology-centred Hybrid AI
Current Research Projects
Our on-going research projects are listed below.
EU HealthyW8 Project
EU Horizon Stay Healthy 2022 RIA project for obesity prevention in daily life. We lead the task of developing daily monitoring algorithms for energy expenditure and stress that causes abnormal eating behaviour. For more information about the HealthyW8 project, please visit: https://www.healthyw8.eu/.
IMPROVE Project
Dutch ZonMw Open Competition 2021 project for the elderly’s intrinsic capacity. We lead the task of investigating intrinsic capacity digital markers extracted from multimodal physiological signals during activities of the elderly's daily living.
EU SMARTTEST Project
EU MSCA Doctoral Networks 2024 Project for resilient remote healthcare using intelligent sensing and communication technologies. We lead the tasks of developing contactless vital sign monitoring algorithms for children with heart diseases and elderly after surgery, respectively.
Load Project
Dutch NWA project for osteoarthritis daily management. We lead the task of developing daily wellbeing monitoring algorithms of people with osteoarthritis. For more information about the Load project, please visit: https://www.load-project.nl/.
Stress-in-Action Project
Dutch Gravitation Programme 2021 project for advancing the science of stress by moving the lab to daily life. We lead the task of developing daily monitoring algorithms of stress using multimodal active and passive sensing data. For more information about the Stress-in-Action project, please visit: https://stress-in-action.nl/.
EarlyBird Project
Early bird monitoring system for diabetic heart problems. We develop a data-powered dynamic model to capture abnormal changes that indicate potential heart problems among people with a long-term history of diabetes.
Meet the Team
Our laboratory comprises a multidisciplinary group of professionals with extensive knowledge and experience in the fields Electrical Engineering, Data Science, Physiology, and Medicine. Our primary objective is to monitor human health during daily living activities. We utilize our collective expertise to increase the explainability of AI technologies in healthcare applications.
