التفاصيل البيبلوغرافية
| العنوان: |
Automated system to measure Tandem Gait to assess executive functions in children |
| المؤلفون: |
Zadeh, Mohammad Zaki, Babu, Ashwin Ramesh, Jaiswal, Ashish, Kyrarini, Maria, Bell, Morris, Makedon, Fillia |
| سنة النشر: |
2020 |
| المجموعة: |
Computer Science |
| مصطلحات موضوعية: |
Computer Science - Computer Vision and Pattern Recognition |
| الوصف: |
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. |
| نوع الوثيقة: |
Working Paper |
| DOI: |
10.1145/3453892.3453999 |
| URL الوصول: |
http://arxiv.org/abs/2012.08662 |
| رقم الانضمام: |
edsarx.2012.08662 |
| قاعدة البيانات: |
arXiv |