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Updated: Mar 23, 2026

3D Kinematic Gait Analysis for Preclinical Studies in Rodents
Published on: August 3, 2019
Quantifying spinal gait kinematics using an enhanced optical motion capture approach in adolescent idiopathic
Stefan Schmid1, Daniel Studer2, Carol-Claudius Hasler2
1ETH Zurich, Institute for Biomechanics, Zurich, Switzerland; Bern University of Applied Sciences, Health Division, Bern, Switzerland.
Background And Purpose:
The pathogenesis of adolescent idiopathic scoliosis (AIS) remains poorly understood. Previous research has indicated possible relationships between kinematics of the spine, pelvis and lower extremities during gait and the progression of AIS, but adequate evidence on spinal kinematics is lacking. The aim of this study was to provide a detailed assessment of spinal gait kinematics in AIS patients compared to asymptomatic controls.
Methods:
Fourteen AIS patients and 15 asymptomatic controls were included. Through introducing a previously validated enhanced trunk marker set, sagittal and frontal spinal curvature angles as well as general trunk kinematics were measured during gait using a 12-camera Vicon motion capture system. Group comparisons were conducted using T-tests and relationships between kinematic parameters and severity of scoliosis (Cobb angle) were investigated using regression analyses.
Results:
The sagittal thoracic curvature angle in AIS patients showed on average 10.7° (4.2°, 17.3°) less kyphosis but 4.9° (2.3°, 7.6°) more range of motion (Cobb angle-dependent (R(2)=0.503)). In the frontal plane, thoracic and thoracolumbar/lumbar curvature angles indicated average lateral deviations in AIS patients. General trunk kinematics and spatio-temporal gait parameters, however, did not show any clinically relevant differences between the groups.
Conclusions:
This demonstrates that the dynamic functionality of the scoliotic spine can be assessed using advanced non-invasive optical approaches and that these should become standard in clinical gait analysis. Furthermore, curvature angle data might be used to drive sophisticated computer simulation models in order to gain an insight into the dynamic loading behavior of the scoliotic spine during gait.
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