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Intention detection using physical sensors and electromyogram for a single leg knee exoskeletonoa mark
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dc.contributor.authorMoon, Dae Hoon-
dc.contributor.authorKim, Donghan-
dc.contributor.authorHong, Young Dae-
dc.date.issued2019-10-02-
dc.identifier.issn1424-8220-
dc.identifier.urihttps://aurora.ajou.ac.kr/handle/2018.oak/30967-
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85073432626&origin=inward-
dc.description.abstractIn this paper, we present a knee exoskeleton. Due to the complicated structure of the knee, an exoskeleton can limit the wearer’s movement (e.g., when completely sitting down). To prevent this, the proposed exoskeleton is designed to move the ankle part prismatically, so the movement of the wearer is not limited. In addition, the developed exoskeleton could be worn on only one leg, but in this case, it is difficult to detect the intention because the relative relationship information of the two legs is unknown. For this purpose, the length between the knee center of rotation and the ankle (LBKA) was measured and used for intention detection. Using a physical sensor—an encoder and an LBKA sensor, the success rate of intention detection was 82.1%. By additionally using an electromyogram (EMG) sensor, the success rate of intention detection was increased to 92%, and the intention detection was also 27.1 ms faster on average.-
dc.description.sponsorshipAcknowledgments: This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. 2019R1C1C1002049). This work was supported by the Technology Innovation Program (No. 10080348, Robust Command Generation of Movement Intention using Epidemal Multi Sensor system for Exoskeleton Robot) funded By the Ministry of Trade, Industry & Energy (MOTIE, Korea).-
dc.language.isoeng-
dc.publisherMDPI AG-
dc.subject.meshComplicated structures-
dc.subject.meshElectromyo grams-
dc.subject.meshElectromyogram-
dc.subject.meshIntention detection-
dc.subject.meshPhysical sensors-
dc.subject.meshSelf alignment-
dc.subject.meshSensor fusion-
dc.subject.meshSitting down-
dc.subject.meshAlgorithms-
dc.subject.meshElectromyography-
dc.subject.meshEntropy-
dc.subject.meshExoskeleton Device-
dc.subject.meshHumans-
dc.subject.meshKnee-
dc.subject.meshLeg-
dc.subject.meshMovement-
dc.subject.meshNeural Networks, Computer-
dc.subject.meshProbability-
dc.subject.meshRange of Motion, Articular-
dc.subject.meshWalking-
dc.titleIntention detection using physical sensors and electromyogram for a single leg knee exoskeleton-
dc.typeArticle-
dc.citation.number20-
dc.citation.titleSensors (Switzerland)-
dc.citation.volume19-
dc.identifier.bibliographicCitationSensors (Switzerland), Vol.19 No.20-
dc.identifier.doi2-s2.0-85073432626-
dc.identifier.pmid31615048-
dc.identifier.scopusid2-s2.0-85073432626-
dc.identifier.urlhttps://www.mdpi.com/1424-8220/19/20/4447/pdf-
dc.subject.keywordElectromyogram (EMG)-
dc.subject.keywordIntention detection-
dc.subject.keywordKnee exoskeleton-
dc.subject.keywordLBKA sensor-
dc.subject.keywordNeural network-
dc.subject.keywordSelf-alignment-
dc.subject.keywordSensor fusion-
dc.type.otherArticle-
dc.description.isoatrue-
dc.subject.subareaAnalytical Chemistry-
dc.subject.subareaBiochemistry-
dc.subject.subareaAtomic and Molecular Physics, and Optics-
dc.subject.subareaInstrumentation-
dc.subject.subareaElectrical and Electronic Engineering-
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