Improving the validity, Accessibility and Applicability of Low-Cost Gait Assessment

Abstract

This thesis presents a comprehensive examination of advancements in gait analysis technologies, specifically focusing on their applications in running. The research primarily investigates the integration and optimisation of low-cost wearable technologies and the Internet-of-Things (IoT) to facilitate running gait assessments within athletes’ habitual environments. This exploration includes the development and validation of a foot-mounted Inertial Measurement Unit (IMU), designed to capture precise gait data directly from the athlete’s foot, providing insights into running dynamics that influence performance, injury prevention, and footwear choices.
In collaboration with the industry partner ‘Mymo Ltd.’ his thesis aims to refine these wearable devices, enhancing their capability to deliver real-time feedback and detailed gait analytics outside conventional lab settings. This adaptation seeks to democratise high- resolution gait analysis, making it accessible in non-clinical/non-bespoke settings, which is essential for continuous performance monitoring and tailored training regimens in sports.
Furthermore, the thesis explores the extension of these technologies into alternative gait analysis methods, such as computer vision. This multi-modal approach aims to overcome some inherent limitations of IMU-only assessments, such as the lack of environmental context and the challenge of analysing gait events in dynamic running scenarios. Computer vision, integrated with IMU data, can offer a richer understanding of gait dynamics by providing visual context go a given assessment.
Additionally, while the primary focus remains on running applications, the thesis also touches upon the potential extensions of these technologies into clinical settings. This includes a preliminary examination of how the same technologies could assist in the assessment of walking gait, which can have implications in assessing those with e.g., neurological disorders. Although this application is secondary, it highlights the versatile potential of the developed technologies to contribute broadly across different fields of health and sports sciences.
By demonstrating how connected, low-cost, and adaptable technologies can revolutionise the approach to gait analysis, the thesis advocates for a shift in how gait assessments are conducted, suggesting a move towards more personalised, accessible, and real- time analyses that could significantly impact athletic training and sports medicine, as well as clinical practice.

Date of Award	25 Jul 2024
Original language	English
Awarding Institution	Northumbria University
Supervisor	Alan Godfrey (Supervisor), Sam Stuart (Supervisor) & Rosie Morris (Supervisor)