A computational method for physical rehabilitation assessment

Show simple item record

dc.contributor.author Brooks, Douglas Antwonne en_US
dc.contributor.author Howard, Ayanna M. en_US
dc.date.accessioned 2011-03-28T17:47:36Z
dc.date.available 2011-03-28T17:47:36Z
dc.date.issued 2010-09
dc.identifier.citation D. 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.isbn 978-1-4244-7708-1
dc.identifier.issn 2155-1774
dc.identifier.uri http://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.description Presented at the 3rd IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), 26-29 September 2010, Tokyo, Japan. en_US
dc.description DOI: 10.1109/BIOROB.2010.5626047 en_US
dc.description.abstract The 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.iso en_US en_US
dc.publisher Georgia Institute of Technology en_US
dc.subject Computer vision techniques en_US
dc.subject Edge detection en_US
dc.subject Human-robot interaction en_US
dc.subject Motion history imaging en_US
dc.subject Physical rehabilitation assessment en_US
dc.subject Random sample consensus en_US
dc.subject Upper-arm rehabilitation en_US
dc.title A computational method for physical rehabilitation assessment en_US
dc.type Proceedings en_US
dc.contributor.corporatename Georgia Institute of Technology. Human-Automation Systems Lab en_US
dc.contributor.corporatename Georgia Institute of Technology. School of Electrical and Computer Engineering en_US
dc.contributor.corporatename Georgia Institute of Technology. Center for Robotics and Intelligent Machines en_US
dc.publisher.original Institute of Electrical and Electronics Engineers en_US
dc.identifier.doi 10.1109/BIOROB.2010.5626047


Files in this item

Files Size Format View
IEEE_2010_BioRob_001.pdf 593.9Kb PDF View/ Open

This item appears in the following Collection(s)

Show simple item record