Sensor technologies in biomedical engineering (SensorTechBME) research group

Head of the research group
Keyword
algorithms
sensor fusion
biofluid optics
uremic toxins
dialysis
on-line monitoring
spectrophotometry
spectrofluorimetry
smart work wear
physical activity monitoring
energy consumption
fatigue monitoring
automatic speech recognition
speech-to-text applications
Overview
The main research field of the SensorTechBMEteam is to develop flexible and novel sensor technologies and algorithms in biomedical engineering applications:‚ To estimate dialysis adequacy and qualitysecuring end stage renal disease (ESRD) patients’ care quality. The research is exploring spectrophotometrical and spectrofluorimetrical characteristics-signatures of thebiofluids and performing various signalprocessing and analysis on those signals.‚ To develop beyond the state-of-the-art applications incorporated into a smart wearablemulti-sensor fusion system for generatingvaluable data about the workers’ location,locomotion, physical activity, energy consumption and physiological status;‚ For speech-to-text usage in healthcareand industry.‚ The well-being score is an innovativemethod and tool integrating quantitativephysiological and subjective psychological indicators for assessing environmentsthat are not only safe and convenient, but also interesting or pleasant or vice versa todefine environments that are unsafe, stressful, overstimulating, or unattractive. Oneapplication area of the tool is to bridge thegap between urban planners and urban residents utilizing a well-being score mapping.
Important results
‚ A new a novel on-line multicomponentminiaturized optical sensor for monitoring removal of uremic toxins in the spentdialysate during hemodialysis was designedand validated in an European multicenterclinical study;‚ A new method and device were developed forreal-time physical fatigue estimation basedon physiological signals and parameters.
Pilt, K.; Karai, D.; Bachmann, M.; Gavriljuk, M.; Fridolin, I. (2023). Influence of Acute Mental Stress on the Forehead Photoplethysmographic Signal Waveform. In: 19th Nordic-Baltic Conference on Biomedical Engineering and Medical Physics. (181−188). Springer. (IFMBE Proceedings; 89). DOI: 10.1007/978-3-031-37132-5_23
Leis, L.; Adoberg, A.; Paats, J.; Holmar, J.; Arund, J.; Karai, D.; Luman, M.; Pilt, K.; Taklaja, P.; Tanner, R.; Fridolin, I. (2023). Hemodialysis Optical Monitoring Toward Greener Technology: A Potential for Water Saving Dialysis Treatment. In: 19th Nordic-Baltic Conference on Biomedical Engineering and Medical Physics. (162−171). Springer. (IFMBE Proceedings; 89). DOI: 10.1007/978-3-031-37132-5_21
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