Sensors & Transducers Journal (ISSN: 2306-8515, e-ISSN 1726-5479) |
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Vol. 18, Special Issue, January 2013, pp. 47-58
Selected papers from the 3rd International Conference on
Sensor Device Technologies and Applications (SENSORDEVICES' 2012)
and The 6th International Conference on Sensor Technologies
and Applications (SENSORCOMM' 2012),
19 - 24 August 2012, Rome, Italy
Implementation of a Shoe-Embedded Human Interface and
Collaborative Supplementation of Service Requirements on
Smartphone SystemKaname Takaochi, Kazuhiro Watanabe, Kazumasa TakamiInformation System Technology Department Graduate School of Engineering, Soka University, 1-236 Tangi-Cho Hachioji-Shi, Tokyo, 192-8577, Japan Tel.: +81-426-91-4118, +81-426-91-9312 E-mail: e10m5222@soka.ac.jp, kazuhiro@soka.ac.jp, k_takami@soka.ac.jp
Received: 12 November 2012 /Accepted: 14 December 2012 /Published: 22 January 2013 |
Abstract: Although a handsfree man-machine interface is useful when the user’s hands are not free, existing handsfree input devices are not the type of device that are normally worn by people. We have focused on a shoe as an input device because people normally wear it when they go out, and proposed a shoe-embedded interface. The input device is a sensor shoe. Weight sensors have been attached at three positions on a sole: the first metatarsal, the fifth metatarsal, and the calcaneal tuberosity. These positions have been selected based on the characteristics of the human foot skeleton. Two types of foot operation have been used: tap and push. By combining these operations, 10 commands have been defined. To make it possible to use web applications with a limited number of commands, we have proposed a method of supplementing the user’s service requirements using collaborative filtering. The sensor shoe houses an insole with hetero-core optical fiber sensor elements attached to it. These elements are sensitive to weight. We have built an experimental system that runs on a smartphone and provides the shoe-embedded interface, and conducted experiments with three test subjects to evaluate the system. The average rate of successful command identification was 89 %. We have also evaluated this service requirements supplementation method theoretically, and confirmed that the proposed service recommendation function can be applied to smartphone systems.
Keywords: Shoe-embedded interface, Heterocore optical fiber sensor, Handsfree interface, Service requirements supplementation, Collaborative filtering
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