Abstract: This study proposed a new method in gait acquisition and analysis for autistic children based on the markerless technique versus the gold standard marker-based technique. Here, the gait acquisition stage is conducted using a depth camera with a customizable skeleton tracking function that is the Microsoft Kinect sensor for recording the walking gait trials of the 23 children with autism spectrum disorder (ASD) and 30 typically healthy developing (TD) children. Next, the Kinect depth sensor outputs information is translated into kinematic gait features. Further, analysis and evaluation are done specifically the kinematic angles of the hip, knee, and ankle in analyzing and visualizing the pattern of the plots versus the kinematic plots acquired from the marker-based that is the Vicon motion system gait technique. In addition, these kinematic angles are also validated using the statistical method namely the Analysis of Variance (ANOVA). Results showed that the ρ-values are insignificant for all angles upon computing both the intra-group and inter-group normalization. Hence, these findings have proven that the proposed markerless-based gait technique is indeed apt to be used as a new alternative markerless method for gait analysis of ASD children.

Nur Khalidah Zakaria, Nooritawati Md Tahir and Rozita Jailani, “A Markerless-based Gait Analysis and Visualization Approach for ASD Children” International Journal of Advanced Computer Science and Applications(IJACSA), 12(5), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120553

@article{Zakaria2021,
title = {A Markerless-based Gait Analysis and Visualization Approach for ASD Children},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120553},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120553},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {5},
author = {Nur Khalidah Zakaria and Nooritawati Md Tahir and Rozita Jailani}
}