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dc.contributor.authorWang, Shie-Yuanen_US
dc.contributor.authorJenp, En-Yuen_US
dc.contributor.authorHsu, Ya-Jenen_US
dc.date.accessioned2020-10-05T02:02:22Z-
dc.date.available2020-10-05T02:02:22Z-
dc.date.issued2019-01-01en_US
dc.identifier.isbn978-1-7281-2999-0en_US
dc.identifier.issn1530-1346en_US
dc.identifier.urihttp://hdl.handle.net/11536/155531-
dc.description.abstractChanges in the human body weight may be caused by diseases, overeating, lack of exercise, or other health problems. In this paper, we built a prototype of a pair of weighing shoes to enable people to constantly monitor their weight changes so that they can detect and treat their health problems earlier. We placed several thin and flexible pressure sensors under the shoes and used machine learning techniques to learn the relationship between their values and the actual weight of the human body being measured. The trained model then was used to predict the weight of a human body. In our experiments, we varied the number of used pressure sensors to study its impact on the prediction error. We found that the prediction error of the trained model could be controlled within 5.8% when 8 or more pressure sensors were used for the current prototype.en_US
dc.language.isoen_USen_US
dc.titleBuilding A Prototype of a Pair of Weighing Shoes Based on Machine Learning Techniquesen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2019 IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATIONS (ISCC)en_US
dc.citation.spage557en_US
dc.citation.epage562en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000568621700095en_US
dc.citation.woscount0en_US
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