Thomas Hellstén

Senior Lecturer in Physiotherapy

Phone number:040 773 31 54

Thomas Hellstén, Master of Physiotherapy, PhD,
Senior Lecturer in Physiotherapy

Hellstén's main interest is in musculoskeletal physiotherapy, digitalisation in health care and rehabilitation and health promotion. He is a member in an interdisciplinary research group at Arcada between technology and health care, Computer Vision based Real-Time Motion Analysis in Health and Well-Being. Hellstén is currently a visiting researcher at the University of Helsinki.

" I believe that successful innovation and research is a result from multi professional co-operation."

PUBLICATIONS
Hellstén, T., Arokoski, J., Karlsson, J., Ristolainen, L., & Kettunen, J. (2025). Reliability and validity of computer vision‐based markerless human pose estimation for measuring hip and knee range of motion. Healthcare Technology Letters, 12(1), e70002.

Hellstén, T. (2025). Digital Practice in Physiotherapy : Remote physiotherapy in Finland and the development of a computer vision-based markerless human pose estimation application. [Doctoral Thesis, University of Helsinki]. Helsingin yliopisto. http://hdl.handle.net/10138/602204 .

Hellstén, T., Arokoski, J., Sjögren, T., Jäppinen, A. M., & Kettunen, J. (2023). Remote physiotherapy in Finland—suitability, usability and factors affecting its use. European Journal of Physiotherapy, 25(6), 378-387.

Hellstén, T., Arokoski, J., Sjögren, T., Jäppinen, A. M., & Kettunen, J. (2022). The current state of remote physiotherapy in Finland: cross-sectional web-based questionnaire study. JMIR rehabilitation and assistive technologies, 9(2), e35569.

Hellsten, T., Karlsson, J., Shamsuzzaman, M., & Pulkkis, G. 2021. The Potential of Computer Vision-Based Marker-Less Human Motion Analysis for Rehabilitation. Rehabilitation Process and Outcome, 10, doi: 11795727211022330.

Hellstén, T., Karlsson, J., & Pulkkis, G. 2021. Computer Vision-based Marker-less Real Time Motion Analysis for Rehabilitation–An Interdisciplinary Research Project. Arcada Working Papers. ISBN 978-952-7365-10-6

Ring, J., Hellstén, T. and Kettunen, J., 2020. Walking speed in older physically active adults – one-year follow-up study. Arcada Working Papers 1/2020, ISSN 2342-3064, ISBN 978-952-7365-03-8

Pulkkis, G., Tana, J., Hellstén, T. and Karlsson, J., 2019. Recent developments in computer vision based real-time monitoring in health and well-being. Arcada Working Papers 3/2019, ISSN 2342-3064, ISBN 978-952-7365-02-1

Ring, J., Hellstén, T. and Kettunen, J., 2019. Evaluating factors associated with the fear of falling in older adults using The Falls Efficacy Scale International (FES-I). Arcada Working Papers 1/2019, ISSN 2342-3064, ISBN 978-952-5260-96-0

Bengs D, Jeglinsky I, Surakka J, Hellstén T, Ring J, Kettunen J. 2017. Reliability of Measuring Lower-Limb Muscle EMG Activity Ratio in Activities of Daily Living With Electrodes Embedded in the Clothing. J Sport Rehabil. 2017 Apr 19:1-12. doi: 10.1123/jsr.2017-0019

Tana J., Forss M., Hellstén T. 2017. The use of wearables in healthcare – challenges and opportunities. Arcada Working Papers 6/2017, ISSN 2342-3064, ISBN 978-952-5260-83-0

GoogleScholar: https://scholar.google.com/citation…

LinkedInhttps://www.linkedin.com/in/thomas-…