BioMediTech Research Groups

Sensor Technology and Biomeasurements

Group Leader: Assistant Professor Antti Vehkaoja

antti.vehkaoja(at)tut.fi

About Us

Sensor Technology and Biomeasurements Group (STB) concentrates on the research and development of embedded measurement technology for physiological monitoring and related signal processing and data analysis methods. In addition, we study electronic nose techniques for clinical applications. Emeritus Professor Jukka Lekkala continues his research as a member of our research group.

Research interests and expertise

Our primary research interests include:

  • Wearable physiological monitoring systems
  • Signal processing methods for vitals estimation
  • Assessment of vascular condition
  • Ion mobility spectrometry for tissue classification

Collaboration offer and requests

We wish to offer our knowledge in embedded systems, measurement methods and data analysis to both, industrial and academic collaborators. For further discussions, please contact: antti.vehkaoja(at)tut.fi, mobile: +358 40 7393181

Major Publications

  1. Peltokangas M, Verho J, Mattila VM, Romsi P, Vehkaoja A, Lekkala J, Oksala N. Areas under peripheral pulse waves: a potential marker of atherosclerotic changes. Physiological Measurement, 2017.
  2. Jeyhani V, Vuorinen T, Mäntysalo M, Vehkaoja A. Comparison on simple algorithms for estimating respiration rate from electrical impedance pneumography signals in wearable devices. Health and Technology, 7(1): 21–31, 2017.
  3. Harju J, Vehkaoja A, Lindroos V, Kumpulainen P, Liuhanen S, Yli-Hankala A, Oksala N. Determination of saturation, heart rate, and respiratory rate at forearm using a Nellcor forehead SpO2-saturation sensor. Journal of Clinical Monitoring and Computing. 2017
  4. Peltokangas M, Vehkaoja A, Verho J, Huotari M, Roning J, Lekkala J. Monitoring arterial pulse waves with synchronous body sensor network. Biomedical and Health Informatics, IEEE Journal of, 18(6):1781–1787, 2014.
  5. Vehkaoja A, Rajala S, Kumpulainen P, Lekkala J. Correlation approach for the detection of the heartbeat intervals using force sensors placed under the bed posts. Journal of medical engineering & technology, 37(5):327–333, 2013.
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