Walking phase recognition for people with lower limb disability

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dc.contributor.authorLee, Sang Wanko
dc.contributor.authorYi, Taeyoubko
dc.contributor.authorHan, Jeong-Suko
dc.contributor.authorJang, Hyoyoungko
dc.contributor.authorKim, Heon-Huiko
dc.contributor.authorJung, Jin-Wooko
dc.contributor.authorBien, Zeungnamko
dc.date.accessioned2018-07-24T02:34:09Z-
dc.date.available2018-07-24T02:34:09Z-
dc.date.created2018-07-12-
dc.date.issued2007-06-
dc.identifier.citation2007 IEEE 10th International Conference on Rehabilitation Robotics, ICORR'07, pp.60 - 67-
dc.identifier.urihttp://hdl.handle.net/10203/244256-
dc.description.abstractThis paper presents a total solution on EMG signal-based walking phase recognition for people with lower limb disability. Various environmental factors such as sensed location, walking speed, and ground inclination are taken into consideration in all the phases of signal sensing, feature extraction, feature selection, and classification. Based on analysis on fourteen well-known feature extraction methods in varying environmental situation, this paper proposes a methodology for selecting a good feature set, and then demonstrates effectiveness of the proposed approach with the classification results. © 2007 IEEE.-
dc.languageEnglish-
dc.publisherIEEE-
dc.titleWalking phase recognition for people with lower limb disability-
dc.typeConference-
dc.type.rimsCONF-
dc.citation.beginningpage60-
dc.citation.endingpage67-
dc.citation.publicationname2007 IEEE 10th International Conference on Rehabilitation Robotics, ICORR'07-
dc.identifier.conferencecountryNE-
dc.identifier.conferencelocationNoordwijk-
dc.identifier.doi10.1109/ICORR.2007.4428407-
dc.contributor.localauthorLee, Sang Wan-
dc.contributor.nonIdAuthorYi, Taeyoub-
dc.contributor.nonIdAuthorHan, Jeong-Su-
dc.contributor.nonIdAuthorJang, Hyoyoung-
dc.contributor.nonIdAuthorKim, Heon-Hui-
dc.contributor.nonIdAuthorJung, Jin-Woo-
dc.contributor.nonIdAuthorBien, Zeungnam-
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