基于人工智能的移动应用程序,通过绘画感知儿童情绪。

Artificial Intelligence-Based Mobile Application for Sensing Children Emotion Through Drawings.

机构信息

Division of Information and Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar.

AI Center for Precision Health, Weill Cornell Medicine-Qatar, Doha, Qatar.

出版信息

Stud Health Technol Inform. 2022 Jun 29;295:118-121. doi: 10.3233/SHTI220675.

Abstract

Children go through varied emotions such as happiness, sadness, and fear. At times, it may be difficult for children to express their emotions. Detecting and understanding the unexpressed emotions of children is very important to address their needs and prevent mental health issues. In this paper, we develop an artificial intelligence (AI) based Emotion Sensing Recognition App (ESRA) to help parents and teachers understand the emotions of children by analyzing their drawings. We collected 102 drawings from a local school in Doha and 521 drawings from Google and Instagram. Four different experiments were conducted using a combination of the two datasets. The deep learning model was trained using the Fastai library in Python. The model classifies the drawings into positive or negative emotions. The model accuracy ranged from 55% to 79% in the four experiments. This study showed that ESRA has the potential in identifying the emotions of children. However, the underlying algorithm needs to be trained and evaluated using more drawings to improve its current accuracy and to be able to identify more specific emotions.

摘要

儿童会经历各种情绪,如快乐、悲伤和恐惧。有时,儿童可能难以表达自己的情绪。因此,发现和理解儿童未表达的情绪对于满足他们的需求和预防心理健康问题非常重要。在本文中,我们开发了一种基于人工智能(AI)的情感感知识别应用程序(ESRA),通过分析儿童的绘画来帮助父母和教师了解他们的情绪。我们从多哈的一所当地学校收集了 102 幅画,从谷歌和 Instagram 收集了 521 幅画。使用这两个数据集的组合进行了四项不同的实验。该深度学习模型使用 Python 中的 Fastai 库进行训练。该模型将绘画分类为积极或消极情绪。在四项实验中,模型的准确率在 55%到 79%之间。这项研究表明,ESRA 有潜力识别儿童的情绪。但是,需要使用更多的绘画来训练和评估底层算法,以提高其当前的准确性,并能够识别更具体的情绪。

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