This study proposes a novel comprehensive personalized computational framework that allows the evaluation and optimization of scoliosis-specific exercises for modulating spinal growth.


  • Lead school School of Health Professions
  • Institute Physiotherapy
  • Research unit Spinal Movement Biomechanics
  • Funding organisation SNSF
  • Duration (planned) 01.10.2023 - 30.09.2027
  • Project management Prof. Dr. Stefan Schmid
  • Head of project Prof. Dr. Stefan Schmid
  • Keywords Musculoskeletal modeling, Finite element modeling, Optical motion capture, Spinal loading, Personalized models, Spinal deformity, Scoliosis-specific exercises, Spinal growth modeling, Vertebral growth quantification


Adolescent idiopathic scoliosis (AIS) is a complex 3D spinal condition where vertebral growth is affected by biomechanical forces. Surgical fusion is needed for severe cases, which results in a stiffer spine and is associated with various complications. To avoid this, early intervention using non-invasive methods like scoliosis-specific exercises (SSEs) is vital. However, current SSE protocols lack biomechanical basis and largely rely on the subjective experience of clinicians. While a variety of protocols have been proposed, they lack the type of loading required to adequately modulate spinal bone growth. The objectives of this study are therefore to develop a personalized numerical modeling framework to 1) determine vertebral endplate stresses in AIS patients during daily activities and currently practiced SSEs; 2) quantify and model spinal growth in those patients; 3) evaluate the potential of two novel high impact corrective SSEs on spinal stresses and growth.

Course of action

Motion capture-driven musculoskeletal models will be combined with finite element simulations to quantify vertebral endplate stresses in 25 patients with progressive AIS for daily activities and currently practiced SSEs. Endplate stresses in these patients will be correlated with growth-related changes in vertebral morphology at 24 months follow-up, which will be measured using high field MRI and the overall change of 3D spinal curvature using biplanar EOS radiographs. Combining the calculated endplate stresses with the measured growth will allow us to develop, calibrate and validate personalized numerical models to accurately simulate spinal growth in those patients. This personalized computational framework will be used to simulate the effect of two novel high impact corrective SSEs (treadmill running and vertical jumping with spine in corrected position) on curve progression.

This project contributes to the following SDGs

  • 3: Good health and well-being