Abstract
The presence of pes cavus, a high-arched foot, is a potential reason for some neuromuscular problems. Active research efforts are being made to devise portable systems for monitoring and early detection of foot deviations. In line with that, we have developed instrumented insoles that incorporate force and inertial sensors and used them to capture data from sixty-four subjects; among them, there were forty-four subjects with normal feet arches and twenty subjects exhibiting pes cavus. We applied a 1D convolutional neural network to extract features and classify data. The trained model allowed for a recognition rate of more than 96%. The presented use case could inspire further research on using smart footwear for pes cavus screening and progression monitoring.
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Acknowledgments
This project was supported in parts by the Key Project 2017GZ0304 of the Science and Technology Department of Sichuan province and the Key Program of Joint Funds of the National Natural Science Foundation of China, grant U1505251.
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Mei, Z., Ivanov, K., Lubich, L., Wang, L. (2019). Recognition of Pes Cavus Foot Using Smart Insole: A Pilot Study. In: Yu, H., Liu, J., Liu, L., Ju, Z., Liu, Y., Zhou, D. (eds) Intelligent Robotics and Applications. ICIRA 2019. Lecture Notes in Computer Science(), vol 11742. Springer, Cham. https://doi.org/10.1007/978-3-030-27535-8_58
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DOI: https://doi.org/10.1007/978-3-030-27535-8_58
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