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dc.contributor.author이정호-
dc.contributor.author신범주-
dc.contributor.author이석-
dc.contributor.author박진우-
dc.contributor.author김재헌-
dc.contributor.author김철기-
dc.contributor.author이택진-
dc.date.accessioned2015-12-03T01:14:41Z-
dc.date.available2015-12-03T01:14:41Z-
dc.date.issued201406-
dc.identifier.other42229-
dc.identifier.urihttp://pubs.kist.re.kr/handle/201004/47803-
dc.description.abstractThis paper presents a motion recognition based step length estimation algorithm using smartphone. Motion of a user is identified based on the hybrid model of Decision Tree (DT), Artificial Neural Network (ANN) and Support Vector Machine (SVM). The parameters of linear combination based step length model are adapted based on the result motion recognition. In order to verify the proposed algorithm, we performed experiments on 5 subjects and showed accuracy of step length estimation as RMSE.-
dc.publisherIEEE ISCE 2014-
dc.subjectStep Length-
dc.subjectSmartphone-
dc.subjectMotion-
dc.subjectnavigation-
dc.subjecthealthcare-
dc.titleMotion based Adaptive Step Length Estimation using Smartphone-
dc.typeConference Paper-
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