RESEARCHER

Yun-Hsuan Chen
Research Assistant Professor

chenyunxuan@westlake.edu.cn  

  • 2016 Ph.D University of Leuven

    Belgium

  • 2011 M.S. ENS Cachan

    France

  • 2008 B.S. National Tsing Hua University

    China

Biography

Yun-Hsuan Chen got her bachelor's degree in the Department of Materials Science and Engineering of National Tsing Hua University, Hsinchu, Taiwan, China. She got an Erasmus Mundus scholarship to pursue her joint master's degree in molecular nano- and bio-photonics for telecommunications and biotechnologies (Monabiphot) program in ENS Cachan, Paris, France, in collaboration with Complutense University of Madrid, Spain, and Delft University of Technology, the Netherlands. She received her Ph.D. in Electrical Engineering from imec, University of Leuven, Belgium in 2016. Then, she completed a postdoctoral fellowship in the Center of Excellence in Biomedical Research on Advanced Integrated-on-chips Neurotechnologies (CenBRAIN Neurotech) in 2021. Presently, Dr. Chen is a Research Assistant Professor in CenBRAIN Neurotech, leading research activities related to multimodal neuroimaging techniques for brain disorders.

Research Interests and Project 

Yun-Hsuan Chen characterized the electrochemical and mechanical properties of various electrodes (multiple designs and materials) for wearable devices. She has experience in validating the designed electrodes by analyzing the recorded ECG signals on human subjects and EEG signals on patients with epilepsy. Her research interest in CenBRAIN Neurotech is applying multimodal EEG-fNIRS neuroimaging devices to diagnose, early detect, and predict brain diseases. The collected signals indicate the changes in neural activity and hemodynamic conditions. The EEG-fNIRS signals of stroke patients prior, during, and after the medical treatments are investigated. The real-time recorded brain signals combined with other physiological signals, electronic health records, and machine learning models can achieve a stroke risk prediction. In addition, the multimodal EEG-fNIRS imaging technique is applied to patients with epilepsy and addiction.

Representative Publications

[1] Y.-H. Chen, and M. Sawan, "Trends and Challenges of Wearable Multimodal Technologies for Stroke Risk Prediction," Sensors, vol. 21, no. 2, 2021, Art no. 460, doi: 10.3390/s21020460 

[2] Y.-H. Chen, C. Fang, E. Z. Chen, L. Huang, and M. Sawan, "Correlation of Sleepiness Scale with Hemoglobin Concentration Variation: Experimental fNIRS Validation," IEEE PhotonIcs & Electromagnetics Research Symposium, Hangzhou, China, 2021. 

[3] Y.-H. Chen et al., "Soft, Comfortable Polymer Dry Electrodes for High Quality ECG and EEG Recording," Sensors, Article vol. 14, no. 12, pp. 23758-23780, Dec 2014, doi: 10.3390/s141223758. 

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