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애니바디 모델링 시스템을 활용한 지형 특화 수정 보행 지수 개발

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dc.contributor.author김윤서-
dc.contributor.author하성민-
dc.contributor.author노준규-
dc.contributor.author황순웅-
dc.contributor.author김완수-
dc.date.accessioned2025-09-08T06:00:28Z-
dc.date.available2025-09-08T06:00:28Z-
dc.date.issued2025-08-
dc.identifier.issn1976-5622-
dc.identifier.issn2233-4335-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/126280-
dc.description.abstractGait is intricately linked to human health, with key gait indexes showing strong correlations. To overcome limitations of flat-surface-focused evaluations, we propose a Modified Gait Index (MGI) that adapts to diverse terrains such as ramps and stairs. Gait data were collected from 15 healthy adults using motion capture, IMU (Inertial Measurement Unit), EMG (Electromyography), and force plates. For each terrain, principal component analysis (PCA) identified key contributing features based on loading vectors and contribution scores. MGI formulas were derived by combining these features with clinically relevant variables, including stance/swing ratio and joint flexion angles. Participants were divided into training and test groups based on PCA similarity, and generalization was evaluated using interquartile range-based normal thresholds. Across all terrains, the test group’s average GI values remained within the training-defined normal range: 1.05 - 2.82 for ramp ascent, 0.71 - 4.02 for ramp descent, 1.68 - 2.86 for stair ascent, 1.15 - 3.99 for stair descent. Although some test values approached quartile boundaries, no outliers were observed. These results demonstrate the MGI’s terrain-adaptive consistency and generalizability, supporting its application in exoskeleton control strategies for users with subclinical gait deviations or muscular overload.-
dc.format.extent6-
dc.language한국어-
dc.language.isoKOR-
dc.publisher제어·로봇·시스템학회-
dc.title애니바디 모델링 시스템을 활용한 지형 특화 수정 보행 지수 개발-
dc.title.alternativeDevelopment of a Terrain-specific Modified Gait Index Using the AnyBody Modeling System-
dc.typeArticle-
dc.publisher.location대한민국-
dc.identifier.doi10.5302/J.ICROS.2025.25.0116-
dc.identifier.scopusid2-s2.0-105013767799-
dc.identifier.bibliographicCitation제어.로봇.시스템학회 논문지, v.31, no.8, pp 900 - 905-
dc.citation.title제어.로봇.시스템학회 논문지-
dc.citation.volume31-
dc.citation.number8-
dc.citation.startPage900-
dc.citation.endPage905-
dc.type.docTypeY-
dc.identifier.kciidART003230557-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.description.journalRegisteredClasskci-
dc.subject.keywordAuthoranybody modeling system-
dc.subject.keywordAuthorexoskeleton-
dc.subject.keywordAuthorgait analysis-
dc.subject.keywordAuthorgait index-
dc.subject.keywordAuthormusculoskeletal modeling-
dc.subject.keywordAuthor.-
dc.identifier.urlhttps://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE12300123&language=ko_KR&hasTopBanner=true-
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ERICA 공학대학 (DEPARTMENT OF ROBOT ENGINEERING)
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