Y. Wang PhD (Ying)

Universitair docent

Over mij

My research is interdisciplinary, which applies and develops multi-modal model-based signal processing, sensing and physiological system modeling techniques in the healthcare field. My main research interest is about remote continuous monitoring of individual’s physiological signs (such as, heart activty) and body movement in the daily life for personalized disease prevention and management, especially enthusiastic in using my expertise to tackle challenges about the daily monitoring of physiological (brain and body) responses to dynamic physical activities for different healthcare purposes, such as, helping people stay in healthy and tracking patients' disease symptom for disease management. 

My past and on-going research projects are listed below:

  • EU Horizon Stay Healthy 2022 RIA project to develop daily monitoring algorithms for energy expenditure and stress causing abnormal eating behaviour for obesity prevention in daily life.
  • Dutch Gravitation Programme 2021 project to develop daily monitoring algorithms of people's stress level using multimodal active and passive sensing data.
  • Dutch ZonMw Open Competition 2021 project to investigate intrinsic capacity digital markers extracted from multimodal physiological signals during activities of daily living of the elderly. 
  • Dutch NWA project to develop daily monitoring algorithms for people’s physical and mental condition for osteoarthritis.
  • Early detection of heart disease in people with diabets using multimodal model-based signal processing and dynamic model technologies.
  • Recovery monitoring of hip-fracture patients using wearable movement sensors (Up&Go project).
  • Early detection of clinical adverse events in postoperative patients using remote monitoring techniques (MoViSign and MoViSupport projects).
  • Track elderly people's resilience using digital hand grip strength (Reshape project).
  • Daily monitoring of gait disorder symptoms (freezing of gait) in people with Parkinson's disease (BrainWave project).
  • Daily monitoring of seizures in people with epilepsy (BrainWave project).

I have daily supervised 8 PhD candidates, over 50 master/bachelor students in the filed of biomedical engineering, technical medicine, electrical engineering, embedded system, neuroscience, etc.

I am the committee member of Dutch Electrical Engineering council (EE-NL) which creates the visibility of EE in the Netherlands, discusses topics which involve, require or affect Electrical Engineering research and education on the national level, coordinates initiatives undertaken by the Dutch technical-university faculties of Electrical Engineering in the areas of research, education and valorization, and strengthens the Dutch Electrical Engineering community.

I am the committee member of educational quality committee for Electrical Engineering program at UT to control and give suggestions to improve the education quality for new-generation electrical engineer training.

I am the committee member of UT-EEMCS ethical committee where we review the ethical protocol of research projects involving human participants to ensure that the research projects agree with local and international ethical guidelines.

For more information, please check my LinkedIn.


Engineering & Materials Science
Medicine & Life Sciences
Status Epilepticus
Agriculture & Biology
Parkinson Disease


My research is to develop and use the techniques of wearable sensing, signal analysis,  and dynamic system modelling to solve practical clinical and technical problems during daily remote vital-sign and movement monitoring. Interesting applications include but not limited to the monitoring of individual's mental health, lifestyle, individuals with cardiovascular disease, diabetes, obesity, Parkinson's disease, and epilepsy. 


van Dartel, D. , Wang, Y., Hegeman, J. H., Vermeer, M. , Vollenbroek-Hutten, M. M. R., & on behalf of the Up&Go after a hip fracture group (2023). Patterns of physical activity over time in older patients rehabilitating after hip fracture surgery: a preliminary observational study. BMC Geriatrics, 23(1), Article 373. https://doi.org/10.1186/s12877-023-04054-2
van Rossum, M. C. (2023). Remote vital signs monitoring for early detection of deterioration after surgery. [PhD Thesis - Research UT, graduation UT, University of Twente]. University of Twente. https://doi.org/10.3990/1.9789036556224
van Rossum, M. C., da Silva, P. M. A. , Wang, Y., Kouwenhoven, E. A. , & Hermens, H. J. (2023). Missing data imputation techniques for wireless continuous vital signs monitoring. Journal of clinical monitoring and computing, 37(5), 1387-1400. https://doi.org/10.1007/s10877-023-00975-w
Thoonen, M. , Veltink, P. H. , Halfwerk, F. R. , van Delden, R. , & Wang, Y. (2022). A Movement-Artefact-Free Heart-Rate Prediction System. Paper presented at 49th Computing in Cardiology Conference, CinC 2022, Tampere, Finland. https://doi.org/10.22489/CinC.2022.190

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Universiteit Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Horst - Zuidhorst (gebouwnr. 28)
De Horst 2
7522LW  Enschede

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Universiteit Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Horst - Zuidhorst
Postbus 217
7500 AE Enschede

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