Young, Fraser, Mason, Rachel, Wall, Conor, Morris, Rosie, Stuart, Sam and Godfrey, Alan (2022) Examination of a Foot Mounted IMU-based Methodology for Running Gait Assessment. Frontiers in Sports and Active Living, 4. p. 956889. ISSN 2624-9367
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Abstract
Gait assessment is essential to understand injury prevention mechanisms during running where high impact-forces can lead to a range of injuries in the lower extremities. Informing running style to increase efficiency and/or selection of the correct running equipment such as shoe type can minimize risk of injury through e.g., matching a runner’s gait to a particular set of cushioning technologies found in modern shoes (neutral/support cushioning). Informing training or selection of the correct equipment requires understanding of a runner’s biomechanics such as determining foot orientation when it strikes the ground. Previous work involved a low-cost approach with a foot mounted inertial measurement unit (IMU) and associated zero-crossing (ZC) based methodology to objectively understand a runner’s biomechanics (in any setting) to inform shoe selection. Here, an investigation of the previously presented ZC-based methodology is presented only to determine general validity for running gait assessment in a range of running abilities from novice (8km/h) to experienced (16km/h+). In comparison to Vicon 3D motion tracking data, the presented approach can extract pronation, foot strike location and ground contact time with good (ICC(2,1) > 0.750) to excellent (ICC(2,1) > 0.900) agreement between 8-12km/h runs. However, at higher speeds (14km/h+) the ZC-based approach begins to deteriorate in performance, suggesting other features and approaches may be more suitable for faster running and sprinting tasks.
Item Type: | Article |
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Additional Information: | Funding information: The work was supported by Northumbria University and the European Regional Development Fund (ERDF) Intensive Industrial Innovation Programme (IIIP) and it was delivered through Northumbria University (grant number: 25R17P01847). |
Uncontrolled Keywords: | algorithm, gait, IMU3, running, wearables, zero-crossing |
Subjects: | C600 Sports Science |
Department: | Faculties > Engineering and Environment > Computer and Information Sciences Faculties > Health and Life Sciences > Sport, Exercise and Rehabilitation |
Depositing User: | John Coen |
Date Deposited: | 17 Aug 2022 11:49 |
Last Modified: | 14 Sep 2022 14:15 |
URI: | https://nrl.northumbria.ac.uk/id/eprint/49885 |
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