Classification of walking gait features using markerless-based approach in ASD children / Nur Khalidah Zakaria, Nooritawati Md Tahir and R. Jailani

Zakaria, Nur Khalidah and Md Tahir, Nooritawati and Jailani, R. (2019) Classification of walking gait features using markerless-based approach in ASD children / Nur Khalidah Zakaria, Nooritawati Md Tahir and R. Jailani. Journal of Electrical and Electronic Systems Research (JEESR), 15. pp. 28-34. ISSN 1985-5389

Abstract

This paper discussed the gait classification of autism children versus normal group. The study involved children from 30 typically development and 21 autism children with aged range between 6 to 13 years old. In this study, gait data from both groups were captured using markerless approach namely Kinect sensor. Three types of gait features are extracted namely direct joint feature, reference joint feature and center of mass feature. Additionally, all the features are classified using three different types of classifiers. Further, the effectiveness of the features for classification of walking gait pattern for ASD children is evaluated. Based on the results obtained, artificial neural network (ANN) outperformed the other two classifiers and results showed that the direct joint feature contributed to perfect classification followed by reference joint feature and center of mass feature.

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Item Type: Article
Creators:
Creators
Email / ID Num.
Zakaria, Nur Khalidah
UNSPECIFIED
Md Tahir, Nooritawati
UNSPECIFIED
Jailani, R.
UNSPECIFIED
Subjects: T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Electronics
T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Electronics > Apparatus and materials > Detectors. Sensors. Sensor networks
Divisions: Universiti Teknologi MARA, Shah Alam > Faculty of Electrical Engineering
Journal or Publication Title: Journal of Electrical and Electronic Systems Research (JEESR)
UiTM Journal Collections: UiTM Journal > Journal of Electrical and Electronic Systems Research (JEESR)
ISSN: 1985-5389
Volume: 15
Page Range: pp. 28-34
Keywords: ASD, gait classification, gait features
Date: December 2019
URI: https://ir.uitm.edu.my/id/eprint/48850
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