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Vol. 259, Issue 5, October 2022, pp. 61-68




Detection of Motion Restriction with Smart Insoles

1, * Tomoko Funayama, 2 Yasutaka Uchida and 3 Yoshiaki Kogure

1 Faculty of Medical Sciences, Teikyo University of Science, Uenohara-shi, Ymanashi, 409-0193, Japan
2 Faculty of Life & Environmental Sciences, Teikyo University of Science, Adachi-ku, Tokyo, 120-0045, Japan
3 Professor Emeritus, Teikyo university of Science, Adachi-ku, 120-0045, Japan
1 Tel.: + 81554634411, fax: + 81554636944

E-mail: funayama@ntu.ac.jp


Received: 9 September 2022 /Accepted: 11 October 2022 /Published: 31 October 2022



Abstract: In this study, a wireless smart insole was used to measure walking with joint motion restriction. This smart insole outputs data for four parts—toe, heel, inside, and outside—and the color of these parts changes according to the degree of weighting. Motion restrictions involving the ankle joint were performed to assess changes in the physical condition. Normal walking without motion restriction was also assessed. Raw data from the smart insole were graphed and visually predicted. Subsequently, we used support vector machines and K-means methods to detect the classifications. Analysis of the data with and without ankle joint restrictions showed a trend toward higher classification accuracy for those with restrictions. The peak value of each waveform during the gait cycle, rate of decrease in the value after each peak, and data inside the insole were identified as potential detection possibilities. The use of smart insoles may facilitate the determination of changes in physical conditions. This will lead to an assessment of the physical condition based on objective data.


Keywords: Smart insole, Physical condition assessment, Wearable devices, Walking monitoring, Wireless data.


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