Title:
A computational method for physical rehabilitation assessment
A computational method for physical rehabilitation assessment
dc.contributor.author | Brooks, Douglas Antwonne | en_US |
dc.contributor.author | Howard, Ayanna M. | 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.date.accessioned | 2011-03-28T17:47:36Z | |
dc.date.available | 2011-03-28T17:47:36Z | |
dc.date.issued | 2010-09 | |
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.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.doi | 10.1109/BIOROB.2010.5626047 | |
dc.identifier.isbn | 978-1-4244-7708-1 | |
dc.identifier.issn | 2155-1774 | |
dc.identifier.uri | http://hdl.handle.net/1853/38301 | |
dc.language.iso | en_US | en_US |
dc.publisher | Georgia Institute of Technology | en_US |
dc.publisher.original | Institute of Electrical and Electronics Engineers | 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 | Text | |
dc.type.genre | Proceedings | |
dspace.entity.type | Publication | |
local.contributor.author | Howard, Ayanna M. | |
local.contributor.corporatename | School of Civil and Environmental Engineering | |
local.contributor.corporatename | Institute for Robotics and Intelligent Machines (IRIM) | |
relation.isAuthorOfPublication | 6d77e175-105c-4b0b-9548-31f20e60e20a | |
relation.isOrgUnitOfPublication | 88639fad-d3ae-4867-9e7a-7c9e6d2ecc7c | |
relation.isOrgUnitOfPublication | 66259949-abfd-45c2-9dcc-5a6f2c013bcf |
Files
Original bundle
1 - 1 of 1
- Name:
- IEEE_2010_BioRob_001.pdf
- Size:
- 593.92 KB
- Format:
- Adobe Portable Document Format
- Description: