The 6th Congress of Exercise and Sport Sciences

Visual Feedback Gait Retraining to Reduce Lower Extremity Loading During Running in Obese Children

Oren Tirosh
School of Health Sciences, Swinburne University of Technology, Melbourne, Australia

Repeated bouts of dynamic activity comprising high foot-ground reaction forces and loading rates can be beneficial to bone health. However, this may be compromised in the obese population, which has shown to have significant peak ground reaction forces during comfortable and fast walking. Tibial stress fractures are associated with increased lower extremity loading at initial foot-ground contact that can be measured using inertial sensors. The aim of the present study was to determine the effect of visual feedback on reducing lower extremity loading in obese children in running. Sixteen children without known gait pathology, aged 8.8 ± 1.3 years, were randomly assigned to either a control or a feedback group. Participants were asked to attend nine treadmill running sessions with two sessions per week, with the last session (retention) as a 1-month follow-up. In each running session the inertial sensor attached to the right anteromedial aspect of the distal tibia captured the acceleration along the tibia at each foot-strike. From the 2nd to the 8th session the feedback group received real-time visual feedback of the tibia acceleration displayed on a monitor in front of the treadmill. Participants were instructed to “run softer”, make their footfalls quieter, and to keep the acceleration peaks below the line. Significant session X group interaction was found (p0.05), indicating a significant 18% reduction in PPA in the feedback group compared to a plateau no change in the control group. This was maintained one month post-training, with significantly lower acceleration in the feedback group at the 9th session. Wearable inertial sensors can be useful for real-time feedback gait retraining to reduce tibia impact loading during running in children.

Oren Tirosh
Oren Tirosh
Swinburne University of Technology
Oren interest involve the understanding of human movement in sport and medical applications and to develop tools for clinicians and coaches to simplify data capture, analysis and interpretation. Oren uses variety of available systems but also interested in developing affordable measuring and interpretation tools using sensors and web based repository applications. Examples of Oren’s work include the development of textile sensor sock to measure plantar pressure, motion sensors with biofeedback application to reduce stress fracture, and tele-assessment platform to measure balance and functional performance.








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