Centre for Biomedical Engineering

Centre for Biomedical Engineering at Tallinn University of Technology is one structural unit of Department of Health Technologies. The Centre is engaged in teaching on  master and doctoral levels.

The mission of Centre for Biomedical Engineering is to act as a leading institution within the interdisciplinary field of Biomedical Engineering in Estonia, to be a partner in the world, which carries out high level research and high-quality teaching at various levels.

The activities and competence of the Centre:

• Research and development of medical apparatus and instruments, and their optimal and effective use;
• Systems and instruments for personalized treatments aiming to improve life quality and well-being;
• Development of technologies for the artifical systems expanding and strengthening inherent human capacities.

Team of the Centre for Biomedical Engineering values:

• Performance
• Development
• Professional Commitment
• Consistency
• Cooperation
• Ethics

Research:

• Centre of Excellence in Information Technology (EXCITE)
• More info in the EXCITE magazine
• Biofluid optics
• Publications (ETIS)

Head of the research group:  Professor IVO FRIDOLIN
Members: Jürgen Arund, Jana Holmar, Merike Luman, Kristjan Pilt, Risto Tanner, Nils Fredrik Arne Uhlin, Moonika Viigimäe,  Kai Lauri, Sigrid Kalle, Deniss Karai
Doctoral Students: Ardo Allik, Andrus Paats

Topics and Competences
Keywords: sensors, algorithms, sensor fusion, biofluid optics, uremic toxins, dialysis, on-line monitoring, spectrophotometry, spectrofluorimetry, signal processing, smart workwear, physical activity monitoring, energy consumption, fatigue monitoring, automatic speech recognition, speech-to-text applications

The main research field of the SensorTechBME team is to develop flexible and novel sensor technologies and algorithms in biomedical engineering applications:

• To estimate dialysis adequacy and quality securing end stage renal disease (ESRD) patients’ care quality. The research is exploring spectrophotometrical and spectrofluorimetrical characteristics-signatures of the biofluids and performing various signal processing and analysis on those signals.
• To develop beyond the state-of-the-art applications incorporated into a smart wearable multi-sensor fusion system for generating valuable data about the workers’ location, locomotion, physical activity, energy consumption and physiological status;
• For speech-to-text usage in healthcare and industry.

Professor Fridolin is a member of the international European Uremic Toxin Work Group (EUTox WG).

Main results

• A novel on-line multicomponent miniaturized optical sensor for monitoring removal of uremic toxins in the spent dialysate during hemodialysis was designed and validated in the European multicenter clinical study.
• A new method and device were developed for real-time physical fatigue estimation based on physiological signals and parameters.

Selected projects:

• IUT19-2, "Biooptical and bioelectrical signals in Biomedical Engineering" (2014−2019)
• TAR16013  (TK148) "Estonian Centre of Excellence in ICT Research" (EXCITE, 2016−2023)
• 767572 "On-line Dialysis Sensor Phase2 (OLDIAS2)" (2017−2019)
• "Tark  töörõivas/Smart workwear Ragnarok 2.0"

Selected publications:

• Paats, A.; Alumäe, T.; Meister, E.; Fridolin, I. (2018). Retrospective analysis of clinical performance of an Estonian speech recognition system radiology: effects of different acoustic and language models. Journal of Digital Imaging, J Digit Imaging (2018) 31: 615.
• Paats, J.; Adoberg, A.; Arund, J.; Dhondt, A.; Fernström, A.; Fridolin, I.; Glorieux, G.; Leis, L.; Luman, M.; Gonzalez-Parra, E.; Perez-Gomez, V. M.; Pilt, K.; Sanchez-Ospina, D.; Segelmark, Mårten; U., Fredrik; A. Ortiz, A. (2020). Serum Levels and Removal by Haemodialysis and Haemodiafiltration of Tryptophan-Derived Uremic Toxins in ESKD Patients. International Journal of Molecular Sciences, 21 (4), #1522.10.3390/ijms21041522.
• Allik, Ardo; Pilt, Kristjan; Karai, Deniss; Fridolin, Ivo; Leier, Mairo; Jervan, Gert (2019). Optimization of Physical Activity Recognition for Real-Time Wearable Systems: Effect of Window Length, Sampling Frequency and Number of Features. Applied Sciences, 9 (22).10.3390/app9224833.
• Lauri, K.; Arund, J.; Holmar, J.; Tanner, R.; Kalle, S.; Luman, M.; Fridolin, I. (2020). Removal of Urea, beta-2-Microglobulin, and Indoxyl Sulfate Assessed by Absorbance and Fluorescence in the Spent Dialysate During Hemodialysis. Asaio Journal, 66 (6), 695−705.10.1097/MAT.0000000000001058.