Representation of human gait trajectory through temporospatial image modelling.

Marker-based 2D temporospatial image modelling is a common strategy in characterizing human gait where Channel filtering, Threshold imaging, and Line feel algorithm are normally used in foreground segmentation targeting human lower limbs of a particular image frame. This paper presents Temporospatia...

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Main Authors:	Akhtaruzzaman, Md., Shafie, Amir Akramin, Khan, Md. Raisuddin
Format:	Article
Language:	English English
Published:	Asian Research Publishing Network 2016
Subjects:	TA Engineering (General). Civil engineering (General) TA349 Mechanics of engineering. Applied mechanics
Online Access:	http://irep.iium.edu.my/56437/ http://irep.iium.edu.my/56437/ http://irep.iium.edu.my/56437/1/56437_REPRESENTATION%20OF%20HUMAN%20GAIT.pdf http://irep.iium.edu.my/56437/2/56437_REPRESENTATION%20OF%20HUMAN%20GAIT_SCOPUS.pdf

id	iium-56437
recordtype	eprints
spelling	iium-564372017-04-12T03:23:37Z http://irep.iium.edu.my/56437/ Representation of human gait trajectory through temporospatial image modelling. Akhtaruzzaman, Md. Shafie, Amir Akramin Khan, Md. Raisuddin TA Engineering (General). Civil engineering (General) TA349 Mechanics of engineering. Applied mechanics Marker-based 2D temporospatial image modelling is a common strategy in characterizing human gait where Channel filtering, Threshold imaging, and Line feel algorithm are normally used in foreground segmentation targeting human lower limbs of a particular image frame. This paper presents Temporospatial Image Modelling approach in presenting segmented objects with spatiotemporal view by reflecting various poses of lower limbs for forward walking. Lower limbs joint movement characteristics and angle variations are also presented in this paper where pre-assigned marker-points are modelled in tracking the motion trajectories. Results show various patterns of motion trajectories and angle variations for Hip, Knee, Ankle, Heel, and Toe of lower limbs through observing the variations of times, locations, and spatiotemporal representations. The results also characterize that the Swing and Stance phases of a gait cycle are about 40% and 60% of a gait cycle respectively. © 2006-2016 Asian Research Publishing Network (ARPN). Asian Research Publishing Network 2016 Article PeerReviewed application/pdf en http://irep.iium.edu.my/56437/1/56437_REPRESENTATION%20OF%20HUMAN%20GAIT.pdf application/pdf en http://irep.iium.edu.my/56437/2/56437_REPRESENTATION%20OF%20HUMAN%20GAIT_SCOPUS.pdf Akhtaruzzaman, Md. and Shafie, Amir Akramin and Khan, Md. Raisuddin (2016) Representation of human gait trajectory through temporospatial image modelling. ARPN Journal of Engineering and Applied Sciences Open Access, 11 (6). pp. 4105-4110. ISSN 1819-6608 http://www.arpnjournals.org/jeas/research_papers/rp_2016/jeas_0316_3929.pdf
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	TA Engineering (General). Civil engineering (General) TA349 Mechanics of engineering. Applied mechanics
spellingShingle	TA Engineering (General). Civil engineering (General) TA349 Mechanics of engineering. Applied mechanics Akhtaruzzaman, Md. Shafie, Amir Akramin Khan, Md. Raisuddin Representation of human gait trajectory through temporospatial image modelling.
description	Marker-based 2D temporospatial image modelling is a common strategy in characterizing human gait where Channel filtering, Threshold imaging, and Line feel algorithm are normally used in foreground segmentation targeting human lower limbs of a particular image frame. This paper presents Temporospatial Image Modelling approach in presenting segmented objects with spatiotemporal view by reflecting various poses of lower limbs for forward walking. Lower limbs joint movement characteristics and angle variations are also presented in this paper where pre-assigned marker-points are modelled in tracking the motion trajectories. Results show various patterns of motion trajectories and angle variations for Hip, Knee, Ankle, Heel, and Toe of lower limbs through observing the variations of times, locations, and spatiotemporal representations. The results also characterize that the Swing and Stance phases of a gait cycle are about 40% and 60% of a gait cycle respectively. © 2006-2016 Asian Research Publishing Network (ARPN).
format	Article
author	Akhtaruzzaman, Md. Shafie, Amir Akramin Khan, Md. Raisuddin
author_facet	Akhtaruzzaman, Md. Shafie, Amir Akramin Khan, Md. Raisuddin
author_sort	Akhtaruzzaman, Md.
title	Representation of human gait trajectory through temporospatial image modelling.
title_short	Representation of human gait trajectory through temporospatial image modelling.
title_full	Representation of human gait trajectory through temporospatial image modelling.
title_fullStr	Representation of human gait trajectory through temporospatial image modelling.
title_full_unstemmed	Representation of human gait trajectory through temporospatial image modelling.
title_sort	representation of human gait trajectory through temporospatial image modelling.
publisher	Asian Research Publishing Network
publishDate	2016
url	http://irep.iium.edu.my/56437/ http://irep.iium.edu.my/56437/ http://irep.iium.edu.my/56437/1/56437_REPRESENTATION%20OF%20HUMAN%20GAIT.pdf http://irep.iium.edu.my/56437/2/56437_REPRESENTATION%20OF%20HUMAN%20GAIT_SCOPUS.pdf
first_indexed	2023-09-18T21:19:37Z
last_indexed	2023-09-18T21:19:37Z
_version_	1777411794235555840

Representation of human gait trajectory through temporospatial image modelling.

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