Biofeedback Gait Retraining under Real-World Running Conditions
Date
2023-08
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Abstract
Gait retraining has been used as an intervention to mitigate the risk of injuries among distance runners. Lab-based gait retraining has demonstrated promising results in changing biomechanical parameters associated with injuries. However, there was limited evidence that supports the transfer of training effect to conditions that resemble real-world running. The main objective of this thesis was to optimize the training protocol for training under real-world conditions and five studies were conducted to address three specific aims: 1) identify the limitations of conventional training protocols, 2) assess habitual gait adaptations in real-world running, and 3) establish the technical specifications for gait assessment using wearables. Regarding the first specific aim, two studies were conducted to examine the transfer of training effect to untrained conditions, including overground and slopes. Results of both studies suggested incomplete transfer, hence, gait retraining along overground running routes with slopes was recommended. For the second specific aim, our third study examined the natural biomechanical adaptations along slopes. Differences in speed and cadence were observed between various slope conditions from real-world training data. As these changes could potentially affect training, an adaptive feedback model was recommended. Tibial acceleration can be measured using wearables and is a common outcome measure for gait retraining. The fourth and fifth studies addressed the third specific aim and presented the technical considerations required for accurate and reliable tibial acceleration measurements under conditions that resemble real-world running. Based on the findings, it was recommended to use wearables with an accelerometer operating range wider than ±16-g and to measure a minimum of 100 consecutive strides during each condition. Finally, a gait retraining protocol for training under real-world conditions was proposed based on the findings of the five studies and was evaluated. The evaluation study has demonstrated the feasibility of using adaptive feedback in real-world training using wearables. Reduction of tibial acceleration was observed after the training in various slope conditions. Overall, the findings of this thesis provided insights for further optimization of the gait retraining protocol and future development of feedback systems suitable for use under real-world conditions.
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Biomechanics
Citation
Chan, Z. Y. S. (2023). Biofeedback gait retraining under real-world running conditions (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.