T. Nassi (Thijs)

PhD Candidate

About Me

I am a Technical Physician, specialized in algorithmic physiological signal analysis. I aspire to improve healthcare by bridging worlds between conventional medicine and engineering. Using software engineering I assess medical datasets to model and predict pathological patterns in respiration, neurological output and sleep related signals. After a successful collaboration between the University of Twente and Harvard Medical School during my master thesis project, the Massachusetts General Hospital and the Cardiovascular and Respiratory Physiology (CRPH) faculty of Science Technology of the University of Twente appointed me a position as a PhD candidate. I am currently researching novel prediction features to identify respiratory pathologies from non-invasive signals. 


Engineering & Materials Science
Deep Learning
Deep Neural Networks
Neural Networks
Medicine & Life Sciences
Action Potentials
Neuromuscular Diseases


Nassi, T. E., Ganglberger, W., Sun, H., Bucklin, A. A., Biswal, S. , Van Putten, M., Thomas, R., & Westover, B. (2022). Automated Scoring of Respiratory Events in Sleep with a Single Effort Belt and Deep Neural Networks. IEEE transactions on biomedical engineering, 69(6), 2094-2104. [9656654]. https://doi.org/10.1109/TBME.2021.3136753
Sleutjes, B. T. H. M., Ruisch, J. , Nassi, T. E. , Buitenweg, J. R., Van Schelven, L. J., Van Den Berg, L. H., Franssen, H., & Stephan Goedee, H. (2021). Impact of stimulus duration on motor unit thresholds and alternation in compound muscle action potential scans. Clinical neurophysiology, 132(2), 323-331. https://doi.org/10.1016/j.clinph.2020.10.026

UT Research Information System

Contact Details

Visiting Address

University of Twente
Drienerlolaan 5
7522 NB Enschede
The Netherlands

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Mailing Address

University of Twente
P.O. Box 217
7500 AE Enschede
The Netherlands