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dc.contributor.authorChen, Sheng-Changen_US
dc.contributor.authorHsieh, Hong-Jungen_US
dc.contributor.authorLu, Tung-Wuen_US
dc.contributor.authorTseng, Ching-Huanen_US
dc.date.accessioned2014-12-08T15:11:46Z-
dc.date.available2014-12-08T15:11:46Z-
dc.date.issued2011-04-01en_US
dc.identifier.issn0966-6362en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.gaitpost.2011.03.004en_US
dc.identifier.urihttp://hdl.handle.net/11536/9021-
dc.description.abstractAn optimization-based, non-invasive, radiation-free method was developed for estimating subject-specific body segment inertial properties (BSIPs) using a motion capture system and two forceplates. The method works with accurate descriptions of the geometry of the body segments, subject-specific center of pressure (COP) and kinematic data captured during stationary standing, and an optimization procedure. Twelve healthy subjects performed stationary standing in different postures, level walking and squatting while kinematic and forceplate data were measured. The performance of the current method was compared to three commonly used predictive methods in terms of the errors of the calculated ground reaction force, COP and joint moments using the corresponding predicted BSIPs. The current method was found to be capable of producing estimates of subject-specific BSIPs that predicted accurately the important variables in human motion analysis during static and dynamic activities. With the differences in the BSIPs from the current method, the mean COP errors were less than 5 mm during stationary standing postures, while those from the existing comparative methods ranged from 11 to 25 mm. During dynamic activities, the existing methods gave COP errors three times as large as the proposed method, with up to 2.5 times RMSE in joint moments during walking. Being non-invasive and using standard motion laboratory equipment, the current method will be useful for routine clinical gait analysis and relevant clinical applications, particularly in patient populations that are not targeted by the existing predictive methods. (C) 2011 Elsevier B.V. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectMotion analysisen_US
dc.subjectOptimizationen_US
dc.subjectInertial parametersen_US
dc.subjectAnthropometryen_US
dc.titleA method for estimating subject-specific body segment inertial parameters in human movement analysisen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.gaitpost.2011.03.004en_US
dc.identifier.journalGAIT & POSTUREen_US
dc.citation.volume33en_US
dc.citation.issue4en_US
dc.citation.spage695en_US
dc.citation.epage700en_US
dc.contributor.department機械工程學系zh_TW
dc.contributor.departmentDepartment of Mechanical Engineeringen_US
dc.identifier.wosnumberWOS:000291139600032-
dc.citation.woscount15-
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