Thomas Hellstén

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/citations?us…

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