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Classification of gait parameters in stroke with peripheral neuropathy (PN) by using k-Nearest Neighbors (kNN) algorithm / N. Anang ...[et al.]

—This paper presents the gait pattern classification between 3 groups which are control, stroke only and stroke with Peripheral Neuropathy (SPN) using k-Nearest Neighbors (kNN) algorithm. Control group has been used as a reference or baseline in order to see the difference in the gait pattern. T...

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Main Authors: Anang, N., Jailani, R., Mustafah, N., Manaf, H.
Format: Article
Language:English
Published: UiTM Press 2018
Subjects:
Algorithms
Online Access:https://ir.uitm.edu.my/id/eprint/63109/1/63109.pdf
https://ir.uitm.edu.my/id/eprint/63109/
https://jeesr.uitm.edu.my/v1/
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spelling my.uitm.ir.631092022-06-29T05:55:53Z https://ir.uitm.edu.my/id/eprint/63109/ Classification of gait parameters in stroke with peripheral neuropathy (PN) by using k-Nearest Neighbors (kNN) algorithm / N. Anang ...[et al.] Anang, N. Jailani, R. Mustafah, N. Manaf, H. Algorithms —This paper presents the gait pattern classification between 3 groups which are control, stroke only and stroke with Peripheral Neuropathy (SPN) using k-Nearest Neighbors (kNN) algorithm. Control group has been used as a reference or baseline in order to see the difference in the gait pattern. The model able to classify patients into their respective group based on the gait parameters collected. Furthermore, the findings also will help them to monitor patient’s performances in rehabilitation program from time to time. 29 subjects has been recruited (9 SPN, 10 stroke subjects and 10 control subjects) with range of age between 40 to 65 years old. Additionally, all subjects must be able to walk freely without any cane or mechanical aid during walking. Vicon® Nexus Plug-in-Gait has been used to compute the kinematic gait parameters. From the results, it is found that there are 9 significant differences in kinematic angles and spatio-temporal data. The classification model developed has been successfully discriminate three different groups with 83.33% accuracy. UiTM Press 2018-12 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/63109/1/63109.pdf Classification of gait parameters in stroke with peripheral neuropathy (PN) by using k-Nearest Neighbors (kNN) algorithm / N. Anang ...[et al.]. (2018) Journal of Electrical and Electronic Systems Research (JEESR), 13: 3. pp. 19-24. ISSN 1985-5389 https://jeesr.uitm.edu.my/v1/
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Algorithms
spellingShingle Algorithms
Anang, N.
Jailani, R.
Mustafah, N.
Manaf, H.
Classification of gait parameters in stroke with peripheral neuropathy (PN) by using k-Nearest Neighbors (kNN) algorithm / N. Anang ...[et al.]
description —This paper presents the gait pattern classification between 3 groups which are control, stroke only and stroke with Peripheral Neuropathy (SPN) using k-Nearest Neighbors (kNN) algorithm. Control group has been used as a reference or baseline in order to see the difference in the gait pattern. The model able to classify patients into their respective group based on the gait parameters collected. Furthermore, the findings also will help them to monitor patient’s performances in rehabilitation program from time to time. 29 subjects has been recruited (9 SPN, 10 stroke subjects and 10 control subjects) with range of age between 40 to 65 years old. Additionally, all subjects must be able to walk freely without any cane or mechanical aid during walking. Vicon® Nexus Plug-in-Gait has been used to compute the kinematic gait parameters. From the results, it is found that there are 9 significant differences in kinematic angles and spatio-temporal data. The classification model developed has been successfully discriminate three different groups with 83.33% accuracy.
format Article
author Anang, N.
Jailani, R.
Mustafah, N.
Manaf, H.
author_facet Anang, N.
Jailani, R.
Mustafah, N.
Manaf, H.
author_sort Anang, N.
title Classification of gait parameters in stroke with peripheral neuropathy (PN) by using k-Nearest Neighbors (kNN) algorithm / N. Anang ...[et al.]
title_short Classification of gait parameters in stroke with peripheral neuropathy (PN) by using k-Nearest Neighbors (kNN) algorithm / N. Anang ...[et al.]
title_full Classification of gait parameters in stroke with peripheral neuropathy (PN) by using k-Nearest Neighbors (kNN) algorithm / N. Anang ...[et al.]
title_fullStr Classification of gait parameters in stroke with peripheral neuropathy (PN) by using k-Nearest Neighbors (kNN) algorithm / N. Anang ...[et al.]
title_full_unstemmed Classification of gait parameters in stroke with peripheral neuropathy (PN) by using k-Nearest Neighbors (kNN) algorithm / N. Anang ...[et al.]
title_sort classification of gait parameters in stroke with peripheral neuropathy (pn) by using k-nearest neighbors (knn) algorithm / n. anang ...[et al.]
publisher UiTM Press
publishDate 2018
url https://ir.uitm.edu.my/id/eprint/63109/1/63109.pdf
https://ir.uitm.edu.my/id/eprint/63109/
https://jeesr.uitm.edu.my/v1/
_version_ 1738514003675578368
score 13.211869

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