Abstract
In order to realize gait assessment and robot-assisted control in lower extremity rehabilitation scenarios, prevention and diagnosis of lower extremity diseases, a sensitivity-enhanced array fiber optic sensing insole for plantar pressure monitoring was designed by taking advantage of the characteristics of fiber optic sensor, such as lightness, anti-electromagnetic interference, strong multiplexing capability, and sensitivity to stress and strain. The gait parameters were effectively analyzed by collecting the plantar pressure data under natural walking. A gait recognition method based on plantar pressure at different walking speeds was proposed to solve the problems of the complexity and poor accuracy of gait recognition. The support vector machine was used to classify four gait periods: the initial double-limb support phase, the single-limb stance phase, the second double-limb support phase and the swing phase. The overall gait phase recognition rate of the classifier was 90.37\(\%\). The experiment verifies the validity of the fiber optic pressure insole to measure gait parameters and the accuracy of gait recognition.
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Acknowledgements
This project is supported by National Natural Science Foundation of China (Grant 52075398), Application Foundation Frontier Project of Wuhan Science and Technology Program (Grant 2020020601012220), and Research Project of Wuhan University of Technology Chongqing Research Institute (Grant YF2021-17).
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Peng, N., Meng, W., Liu, Q., Xie, S. (2022). Gait Analysis and Phase Recognition Based on Array Fiber Optic Sensing Insole. In: Liu, H., et al. Intelligent Robotics and Applications. ICIRA 2022. Lecture Notes in Computer Science(), vol 13457. Springer, Cham. https://doi.org/10.1007/978-3-031-13835-5_4
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