Y. Wang PhD (Ying)

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 responses to dynamic physical activities.

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

Early detection of heart disease in people with diabets using multimodal model-based signal processing and dynamic model techniques.
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 take the daily supervisor role of four PhD candidates . I have supervised around 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

# Electroencephalography

Medicine & Life Sciences

# Electroencephalography
# Freezing
# Gait
# Status Epilepticus

Agriculture & Biology

# Accelerometers
# Parkinson Disease
# Surgery

Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), Biomedical Signals and Systems (BSS)

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 life style, individuals with cardiovascular disease, diabetes, obesity, Parkinson's disease, and epilepsy.

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

Reintjes, M. P. T. , Wang, Y. , van Delden, R. , Klaassen, R., Lynch, W. , Veltink, P. H. , Grandjean, J. G. , & Halfwerk, F. R. (2022). Objectief in kaart brengen van patiëntmobilisatie na hartchirurgie met behulp van accelerometers: Op weg naar patiënt-specifieke strategieën. Abstract from Wetenschapsdag Medisch Spectrum Twente 2022, Enschede, Netherlands.

Reintjes, M. P. T. , Wang, Y. , van Delden, R. , Klaassen, R., Lynch, W. , Veltink, P. H. , Grandjean, J. G. , & Halfwerk, F. R. (2022). Objectief in kaart brengen van patiëntmobilisatie na hartchirurgie met behulp van accelerometers: Op weg naar patiënt-specifieke strategieën. Poster session presented at Congres Cardiovasculaire Preventie en Hartrevalidatie 2022 , Ede, Netherlands.

Cockx, H. M. , Nonnekes, J., Bloem, B. , van Wezel, R. J. A., Cameron, I. , & Wang, Y. (2021). Dealing with the heterogeneous presentations of freezing of gait: How reliable are the freezing index and heart rate for freezing detection?. Manuscript submitted for publication. https://doi.org/10.21203/rs.3.rs-735366/v1

Bruin, B. D., Singh, K. , Wang, Y., Huisken, J., Pineda de Gyvez, J., & Corporaal, H. (2021). Multi-level Optimization of an Ultra-Low Power BrainWave System for Non-Convulsive Seizure Detection. IEEE Transactions on Biomedical Circuits and Systems, 15(5), 1107-1121. https://doi.org/10.1109/TBCAS.2021.3120965

Wang, Y., Wanrooij, M. M. V., Emaus, R., Nonneke, J., Cohen, M. X., Cockx, H. , Janssen, S., Helmich, R. C. , & Wezel, R. V. (2021). Relationship between eye movements and freezing of gait during turning in individuals with Parkinson’s disease. MedRxiv. https://doi.org/10.1101/2021.09.06.21263180

Wang, Y., Zibrandtsen, I. C., Lazeron, R. H. C., van Dijk, J. P., Long, X., Aarts, R. M., Wang, L., & Arends, J. B. A. M. (2021). Pitfalls in EEG Analysis in Patients With Nonconvulsive Status Epilepticus: A Preliminary Study. Clinical EEG and Neuroscience. https://doi.org/10.1177/15500594211050492

Wang, Y., Long, X., van Dijk, J. P., Aarts, R. M., Wang, L., & Arends, J. B. A. M. (2020). False alarms reduction in non-convulsive status epilepticus detection via continuous EEG analysis. Physiological measurement, 41, [055009]. https://doi.org/10.1088/1361-6579/ab8cb3

Wang, Y., Beuving, F. , Nonnekes, J., Cohen, M. X., Long, X., Aarts, R. M. , & van Wezel, R. (2020). Freezing of gait detection in Parkinson's disease via multimodal analysis of EEG and accelerometer signals. In 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2020): Enabling Innovative Technologies for Global Healthcare (pp. 847-850). [9175288] (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2020). IEEE. https://doi.org/10.1109/EMBC44109.2020.9175288

Wang, Y., Long, X., Dijk, H. V., Aarts, R., & Arends, J. (2019). Adaptive EEG Channel Selection for Nonconvulsive Seizure Analysis. In 2018 IEEE 23rd International Conference on Digital Signal Processing, DSP 2018 [8631844] IEEE. https://doi.org/10.1109/ICDSP.2018.8631844

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