Artificial Intelligence in Sport and Health

We use existing AI tools and develop new AI-driven methods to solve problems related to sports performance, medical imaging, and human movement.
AI_sport_health_lab

Table of contents

Research group type
Research group
Core fields of research
Physical activity, health and wellbeing
Research areas
Neuromuscular function and adaptation
Faculty
Faculty of Sport and Health Sciences

Research group description

In the AI group within the Faculty of Sport and Health Sciences, we focus on the use of existing AI tools or the development of new AI-driven methods to solve problems related to sports performance, medical imaging, and human movement. 

Across the group we have broad expertise in sport and exercise science (e.g. exercise physiology, biomechanics), as well as in AI and computer science. We work mainly with Python, but also with other languages such as Matlab.

Beyond our faculty, we collaborate with other faculties at JYU and other universities in Finland (e.g Tampere, University of Eastern Finland, Metropolia) and abroad. We also work closely with the Finnish Institute of High Performance Sport (KIHU), hospital NOVA, and various companies. In addition, we play a central role in JYU's Digital Citizen Science Centre

Our group are always open to new opportunities. If you are interested in working together, please contact group leader Prof. Neil Cronin.

Publications

Publication
2024
Available through Open Access
Triennial Conference of the European Society for the Cognitive Sciences of Music.
Danso, Andrew
Kekäläinen, Tiia
Koehler, Friederike
Knittle, Keegan
Nijhuis, Patti
Burunat, Iballa
Neto, Pedro
Mavrolampados, Anastasios
Randall, William M.
Ansani, Alessandro
Rantalainen, Timo
Alluri, Vinoo
Hartmann, Martin
Schaefer, Rebecca S.
Rousi, Rebekah
Agres, Kat
MacRitchie, Jennifer
Toiviainen, Petri
Saarikallio, Suvi
Chastin, Sebastien
Luck, Geoff

Research group