论文标题
自动化系统来测量串联步态以评估儿童的执行功能
Automated system to measure Tandem Gait to assess executive functions in children
论文作者
论文摘要
随着近年来移动技术已经变得无处不在，基于计算机的认知测试变得越来越流行和高效。在这项工作中，我们专注于通过分析儿童的步态运动来评估运动功能。尽管在设计自动化评估系统进行步态分析方面已经进行了大量研究，但这些努力中的大多数都使用令人难以置信的可穿戴传感器来测量身体运动。我们设计了一个基于计算机视觉的评估系统，该系统仅需要一个相机，该相机更容易在学校或家庭环境中使用。已经创建了一个数据集，其中27个孩子正在进行测试。此外，为了提高系统的准确性，在NTU-RGB+D 120数据集上预先训练了基于深度学习的模型，然后在我们的步态数据集中进行了微调。结果突出了提议的工作在通过达到76.61％的分类准确性来自动化儿童表现评估的功效。
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.
