職員瀏覽: A new fractal-based kinetic index to characterize gait deficits with application in stroke survivor functional mobility assessment

A new fractal-based kinetic index to characterize gait deficits with application in stroke survivor functional mobility assessment

This paper proposes a new Kinetic Index (K.I.) to characterize the gait deficits in stroke survivors. The index is derived from the fractal properties of surface electromyography (sEMG) signals. The objectives of proposing this K.I. are (i) to find the correlation between sEMG fractal properties wit...

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Main Authors:	Tan, Ming Gui, Ho, Jee Hou, Goh, Hui Ting, Ng, Hoon Kiat, Abdul Latif, Lydia, Mazlan, Mazlina
格式:	Article
出版:	Elsevier 2019
主題:	R Medicine
在線閱讀:	http://eprints.um.edu.my/23297/ https://doi.org/10.1016/j.bspc.2018.09.014
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spelling	my.um.eprints.232972021-05-25T03:19:24Z http://eprints.um.edu.my/23297/ A new fractal-based kinetic index to characterize gait deficits with application in stroke survivor functional mobility assessment Tan, Ming Gui Ho, Jee Hou Goh, Hui Ting Ng, Hoon Kiat Abdul Latif, Lydia Mazlan, Mazlina R Medicine This paper proposes a new Kinetic Index (K.I.) to characterize the gait deficits in stroke survivors. The index is derived from the fractal properties of surface electromyography (sEMG) signals. The objectives of proposing this K.I. are (i) to find the correlation between sEMG fractal properties with TUG test; (ii) to classify stroke survivors into different homogeneous subgroups based on K.I., and (iii) to compare the classification results based on published methods. To achieve these objectives, 30 stroke survivors with different levels of gait impairments were recruited to perform TUG. sEMG signals from Tibialis Anterior (TA) and Gastrocnemius Lateral (GL) were acquired in a 5-meter walk test. Sliding window Higuchi fractal dimension algorithm was applied to sEMG of these TA and GL muscles to determine the fractal properties. Hierarchical cluster analysis was used to classify stroke survivors into different subgroups with (i) conventional multiple category of gait parameters (Approach 1), and (ii) single input by using the proposed K.I. value (Approach 2). Besides that, classification based on stroke survivors TUG score was also applied. Results showed that K.I. has strong correlation with the TUG score. A higher value in K.I. associates with higher TUG score. This suggests K.I. could quantify gait deficits and detect risk of fall in this population. The classification results from the Approach 1 were similar to previous published studies. The gait parameters from Approach 2 showed similar gait patterns to Approach 1. Meanwhile, gait results from classification based on TUG score yielded heterogeneous subgroups. These results suggested that K.I. was able to assess gait severity among stroke survivors and was more efficient (it requires a single input parameter only) to classify stroke survivors into homogeneous subgroups. © 2018 Elsevier Ltd Elsevier 2019 Article PeerReviewed Tan, Ming Gui and Ho, Jee Hou and Goh, Hui Ting and Ng, Hoon Kiat and Abdul Latif, Lydia and Mazlan, Mazlina (2019) A new fractal-based kinetic index to characterize gait deficits with application in stroke survivor functional mobility assessment. Biomedical Signal Processing and Control, 52. pp. 403-413. ISSN 1746-8094 https://doi.org/10.1016/j.bspc.2018.09.014 doi:10.1016/j.bspc.2018.09.014
institution	Universiti Malaya
building	UM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaya
content_source	UM Research Repository
url_provider	http://eprints.um.edu.my/
topic	R Medicine
spellingShingle	R Medicine Tan, Ming Gui Ho, Jee Hou Goh, Hui Ting Ng, Hoon Kiat Abdul Latif, Lydia Mazlan, Mazlina A new fractal-based kinetic index to characterize gait deficits with application in stroke survivor functional mobility assessment
description	This paper proposes a new Kinetic Index (K.I.) to characterize the gait deficits in stroke survivors. The index is derived from the fractal properties of surface electromyography (sEMG) signals. The objectives of proposing this K.I. are (i) to find the correlation between sEMG fractal properties with TUG test; (ii) to classify stroke survivors into different homogeneous subgroups based on K.I., and (iii) to compare the classification results based on published methods. To achieve these objectives, 30 stroke survivors with different levels of gait impairments were recruited to perform TUG. sEMG signals from Tibialis Anterior (TA) and Gastrocnemius Lateral (GL) were acquired in a 5-meter walk test. Sliding window Higuchi fractal dimension algorithm was applied to sEMG of these TA and GL muscles to determine the fractal properties. Hierarchical cluster analysis was used to classify stroke survivors into different subgroups with (i) conventional multiple category of gait parameters (Approach 1), and (ii) single input by using the proposed K.I. value (Approach 2). Besides that, classification based on stroke survivors TUG score was also applied. Results showed that K.I. has strong correlation with the TUG score. A higher value in K.I. associates with higher TUG score. This suggests K.I. could quantify gait deficits and detect risk of fall in this population. The classification results from the Approach 1 were similar to previous published studies. The gait parameters from Approach 2 showed similar gait patterns to Approach 1. Meanwhile, gait results from classification based on TUG score yielded heterogeneous subgroups. These results suggested that K.I. was able to assess gait severity among stroke survivors and was more efficient (it requires a single input parameter only) to classify stroke survivors into homogeneous subgroups. © 2018 Elsevier Ltd
format	Article
author	Tan, Ming Gui Ho, Jee Hou Goh, Hui Ting Ng, Hoon Kiat Abdul Latif, Lydia Mazlan, Mazlina
author_facet	Tan, Ming Gui Ho, Jee Hou Goh, Hui Ting Ng, Hoon Kiat Abdul Latif, Lydia Mazlan, Mazlina
author_sort	Tan, Ming Gui
title	A new fractal-based kinetic index to characterize gait deficits with application in stroke survivor functional mobility assessment
title_short	A new fractal-based kinetic index to characterize gait deficits with application in stroke survivor functional mobility assessment
title_full	A new fractal-based kinetic index to characterize gait deficits with application in stroke survivor functional mobility assessment
title_fullStr	A new fractal-based kinetic index to characterize gait deficits with application in stroke survivor functional mobility assessment
title_full_unstemmed	A new fractal-based kinetic index to characterize gait deficits with application in stroke survivor functional mobility assessment
title_sort	new fractal-based kinetic index to characterize gait deficits with application in stroke survivor functional mobility assessment
publisher	Elsevier
publishDate	2019
url	http://eprints.um.edu.my/23297/ https://doi.org/10.1016/j.bspc.2018.09.014
_version_	1702170272030785536
score	13.251813

A new fractal-based kinetic index to characterize gait deficits with application in stroke survivor functional mobility assessment

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