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arXiv · 2012.08662

Automated system to measure Tandem Gait to assess executive functions in children

Mohammad Zaki Zadeh·Ashwin Ramesh Babu·Ashish Jaiswal·Maria Kyrarini·Morris Bell·Fillia Makedon
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Abstract

As mobile technologies have become ubiquitous in recent years, computer-based cognitive tests have become more popular and efficient. In this work, we focus on assessing motor function in children by analyzing their gait movements. Although there has been a lot of research on designing automated assessment systems for gait analysis, most of these efforts use obtrusive wearable sensors for measuring body movements. We have devised a computer vision-based assessment system that only requires a camera which makes it easier to employ in school or home environments. A dataset has been created with 27 children performing the test. Furthermore in order to improve the accuracy of the system, a deep learning based model was pre-trained on NTU-RGB+D 120 dataset and then it was fine-tuned on our gait dataset. The results highlight the efficacy of proposed work for automating the assessment of children's performances by achieving 76.61% classification accuracy.

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Mohammad Zaki Zadeh, Ashwin Ramesh Babu, Ashish Jaiswal, Maria Kyrarini, Morris Bell, Fillia Makedon. 2020-12-15. Automated system to measure Tandem Gait to assess executive functions in children. https://doi.org/10.1145/3453892.3453999

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