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dc.contributor.authorBrooks, Douglas Antwonneen_US
dc.contributor.authorHoward, Ayanna M.en_US
dc.date.accessioned2011-03-28T17:47:36Z
dc.date.available2011-03-28T17:47:36Z
dc.date.issued2010-09
dc.identifier.citationD. Brooks, A. Howard, “A Computational Method for Physical Rehabilitation Assessment,” IEEE International Conference on Biomedical Robotics and Biomechatronics, Tokyo, Japan, Sept. 2010, 442-447.en_US
dc.identifier.isbn978-1-4244-7708-1
dc.identifier.issn2155-1774
dc.identifier.urihttp://hdl.handle.net/1853/38301
dc.description©2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.en_US
dc.descriptionPresented at the 3rd IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), 26-29 September 2010, Tokyo, Japan.en_US
dc.descriptionDOI: 10.1109/BIOROB.2010.5626047en_US
dc.description.abstractThe objective of this research effort is to advance the process of quantifying physical rehabilitation techniques by developing and validating the core technologies needed to integrate therapy instruction with human-robot interaction in order to improve upper-arm rehabilitation. The method presented uses computer vision techniques such as Motion History Imaging (MHI), edge detection, and Random Sample Consensus (RANSAC) to quantify movements through robot observation. The results are compared with ground truth data retrieved via the Trimble 5606 Robotic Total Station for the purpose of assessing the efficiency of this approach.en_US
dc.language.isoen_USen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.subjectComputer vision techniquesen_US
dc.subjectEdge detectionen_US
dc.subjectHuman-robot interactionen_US
dc.subjectMotion history imagingen_US
dc.subjectPhysical rehabilitation assessmenten_US
dc.subjectRandom sample consensusen_US
dc.subjectUpper-arm rehabilitationen_US
dc.titleA computational method for physical rehabilitation assessmenten_US
dc.typeProceedingsen_US
dc.contributor.corporatenameGeorgia Institute of Technology. Human-Automation Systems Laben_US
dc.contributor.corporatenameGeorgia Institute of Technology. School of Electrical and Computer Engineeringen_US
dc.contributor.corporatenameGeorgia Institute of Technology. Center for Robotics and Intelligent Machinesen_US
dc.publisher.originalInstitute of Electrical and Electronics Engineersen_US
dc.identifier.doi10.1109/BIOROB.2010.5626047


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