Just find it: The Mymo approach to recommend running shoes

Young, Fraser, Coulby, Graham, Watson, Ian, Downs, Craig, Stuart, Sam and Godfrey, Alan (2020) Just find it: The Mymo approach to recommend running shoes. IEEE Access, 8. pp. 109791-109800. ISSN 2169-3536

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Official URL: https://doi.org/10.1109/ACCESS.2020.3002075


Wearing inappropriate running shoes may lead to unnecessary injury through continued strain upon the lower extremities; potentially damaging a runner’s performance. Many technologies have been developed for accurate shoe recommendation, which centre on running gait analysis. However, these often require supervised use in the laboratory/shop or exhibit too high a cost for personal use. This work addresses the need for a deployable, inexpensive product with the ability to accurately assess running shoe-type recommendation. This was achieved through quantitative analysis of the running gait from 203 individuals through use of a tri-axial accelerometer and tri-axial gyroscope-based wearable (Mymo). In combination with a custom neural network to provide the shoe-type classifications running within the cloud, we experience an accuracy of 94.6 in classifying the correct type of shoe across unseen test data.

Item Type: Article
Uncontrolled Keywords: Deep learning, gait analysis, foot pronation, IMU, running shoes
Subjects: C600 Sports Science
G400 Computer Science
G600 Software Engineering
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Faculties > Health and Life Sciences > Sport, Exercise and Rehabilitation
Depositing User: Elena Carlaw
Date Deposited: 11 Jun 2020 09:06
Last Modified: 31 Jul 2021 13:31
URI: http://nrl.northumbria.ac.uk/id/eprint/43417

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