Research group - Sports Injury Prevention


The multiple benefits of sport participation on health are well documented. However, sports injuries are common and they are recognized as a serious public health burden, especially when considering the possible long-term consequences. 

The goals of our research activities are to identify injury risk factors, to improve our understanding of the mechanisms leading to sports injuries, and to provide prevention recommendations to the participants. Research projects on sports injuries have been carried out in different contexts, such as youth sport, semi-professional football or the army. We have specifically developed an expertise in running-related injuries and the possible role of footwear used in that context. 

Our research relies on both epidemiological and biomechanical approaches. We actively collaborate with the RUNSAFE group (DK) through scientific meetings and publications.

Research projects

  • Assessment of a pressure-sensitive insole device to analyse the running technique during regular training sessions.
  • Does running shoe drop influence injury risk? An epidemiological and biomechanical study.
  • Impact of shoe type on running-related injury: A randomised controlled trial comparing conventional running footwear with and without anti-pronation system.
  • Moderate to severe injuries in football: a one-year prospective study of twenty-four female and male amateur teams.
  • Relationship between training load and injury incidence in competitive young athletes.
laurent malisoux


76, rue d’Eich
L-1460 Luxembourg
Tel. : +352 26 970 231

Featured Publications

Associations between device-measured physical activity and glycemic control and variability indices under free-living condition.

  • Deep Digital Phenotyping Research Unit
  • Physical Activity, Sport and Health
October 14, 2021
2021 Oct. Diabetes Technol Ther. Online ahead of print.
  • El Fatouhi D
  • Heritier H
  • Allemann C
  • Malisoux L
  • Laouali N
  • Riveline JP
  • Salathe M
  • Fagherazzi G.

Towards precision cardiometabolic prevention: results from a machine learning, semi-supervised clustering approach in the nationwide population-based ORISCAV-LUX 2 study.

  • Deep Digital Phenotyping Research Unit
  • Platform Bioinformatics
  • Public Health Expertise
  • Public Health Research
  • Physical Activity, Sport and Health
  • NutriHealth
  • PHR Custom Group 3
August 06, 2021
2021 Aug. Sci Rep.11(1):16056.
  • Fagherazzi G
  • Zhang L
  • Aguayo G
  • Pastore J
  • Goetzinger C
  • Fischer A
  • Malisoux L
  • Samouda H
  • Bohn T
  • Ruiz-Castell M
  • Huiart L.
See all publications