BioKin: an ambulatory platform for gait kinematic and feature assessment Ekanayake, Samitha W., Morris, Andrew J., Forrester, Mike and Pathirana, Pubudu N. 2015, BioKin: an ambulatory platform for gait kinematic and feature assessment, Healthcare technology letters, vol. 2, no. 1, pp. 40-45, doi: 10.1049/htl.2014.0094. Attached Files Name Description MIMEType Size Downloads Title BioKin: an ambulatory platform for gait kinematic and feature assessment Author(s) Ekanayake, Samitha W. Morris, Andrew J. Forrester, Mike Pathirana, Pubudu N. orcid.org/0000-0001-8014-7798 Journal name Healthcare technology letters Volume number 2 Issue number 1 Start page 40 End page 45 Total pages 6 Publisher Institution of Engineering and Technology Place of publication Stevenage, Eng. Publication date 2015-02 ISSN 2053-3713 Keyword(s) BioKin system ambulatory platform correlation coefficient data collection feature assessment gait analysis gait kinematic image motion analysis instrumented treadmill kinematics limb orientation estimation algorithm low-cost wearable wireless motion capture sensor medical image processing motion analysis platform motion estimation motion measurement patient rehabilitation root-mean-square error storage engine visualisation platform wireless sensor networks Summary A platform to move gait analysis, which is normally restricted to a clinical environment in a well-equipped gait laboratory, into an ambulatory system, potentially in non-clinical settings is introduced. This novel system can provide functional measurements to guide therapeutic interventions for people requiring rehabilitation with limited access to such gait laboratories. BioKin system consists of three layers: a low-cost wearable wireless motion capture sensor, data collection and storage engine, and the motion analysis and visualisation platform. Moreover, a novel limb orientation estimation algorithm is implemented in the motion analysis platform. The performance of the orientation estimation algorithm is validated against the orientation results from a commercial optical motion analysis system and an instrumented treadmill. The study results demonstrate a root-mean-square error less than 4° and a correlation coefficient more than 0.95 when compared with the industry standard system. These results indicate that the proposed motion analysis platform is a potential addition to existing gait laboratories in order to facilitate gait analysis in remote locations. Language eng DOI 10.1049/htl.2014.0094 Field of Research 090305 Rehabilitation Engineering Socio Economic Objective 970109 Expanding Knowledge in Engineering HERDC Research category C1 Refereed article in a scholarly journal ERA Research output type C Journal article Copyright notice ©2015, IET Persistent URL http://hdl.handle.net/10536/DRO/DU:30080749 Document type: Journal Article Collections: Faculty of Health School of Medicine Faculty of Science, Engineering and Built Environment School of Engineering Related Links Link Description Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Fri, 15 Jan 2016, 15:02:31 EST Fri, 15 Jan 2016, 15:03:03 EST Sat, 16 Jan 2016, 04:01:12 EST Sat, 16 Jan 2016, 05:10:48 EST Thu, 23 Jun 2016, 08:59:49 EST Thu, 23 Jun 2016, 09:00:48 EST Sat, 24 Feb 2018, 01:32:16 EST Filtered Full Citation counts:   Cited 15 times in TR Web of Science Cited 22 times in Scopus Search Google Scholar Access Statistics: 396 Abstract Views, 2 File Downloads  -  Detailed Statistics Created: Fri, 15 Jan 2016, 15:03:03 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.