Charles, Danielle T. (2024) Accelerometer-based gait analysis for the quantitative assessment of running performance for potential application outside the laboratory. PhD thesis, University of Leeds.
Abstract
Running gait analysis is often achieved using motion capture (MC), however this is largely confined to laboratories with costly and space-intensive equipment. This study investigates measuring radial acceleration against time on a runner’s leg, using a sensitive wearable accelerometer as a simpler alternative. Stride Frequency (SF) and Spectral Purity (SP) were identified as key parameters extracted using Fast Fourier Transformation (FFT) of accelerometery data as potential quantitative indicators of running gait quality. To assess these parameters as measures of gait quality and whether they are related to performance, Running Economy (RE) benefits from wearing the Nike® Vaporfly ZoomX Next% (VFN%) versus the Saucony® ProGrid Jazz 12 (JAZ) running shoes were determined using a Cardiopulmonary Exercise Test (CPET) of 25 participants running at a fixed speed of 12 km/h on a treadmill over various inclines from 0-5%. The RE benefits of the VFN% were confirmed to be 4.4% at 0% incline and shown to exponentially decline to a predicted minimum benefit of 2.3% by 16% incline and above. The FFT of the corresponding accelerometer movement waves revealed that runners always have a lower SF and generally a better SP when wearing the VFN% running shoes. As incline increased the difference between the lower SF in the VFN% vs the JAZ parallels the declining RE benefit of wearing VFN% over the JAZ whilst running at a fixed speed. This novel analysis emphasises the potential of accelerometry as a tool for understanding gait quality and predicting performance outside the laboratory. Further testing and optimisation are required to make this type of gait analysis affordable and accessible for all athletes.
Metadata
Supervisors: | Askew, Graham and Brown, Andy |
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Keywords: | Biomechanics; cardiopulmonary exercise testing; running economy; accelerometry |
Awarding institution: | University of Leeds |
Academic Units: | The University of Leeds > Faculty of Biological Sciences (Leeds) > School of Biology (Leeds) |
Academic unit: | School of Biomedical Sciences |
Depositing User: | Miss Danielle T. Charles |
Date Deposited: | 14 Aug 2024 13:04 |
Last Modified: | 14 Aug 2024 13:04 |
Open Archives Initiative ID (OAI ID): | oai:etheses.whiterose.ac.uk:35340 |
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