SAFETYLIT WEEKLY UPDATE

We compile citations and summaries of about 400 new articles every week.
RSS Feed

HELP: Tutorials | FAQ
CONTACT US: Contact info

Search Results

Journal Article

Citation

Ali N, Abd-Alrazaq A, Shah Z, Alajlani M, Alam T, Househ M. Stud. Health Technol. Inform. 2022; 295: 118-121.

Copyright

(Copyright © 2022, IOS Press)

DOI

10.3233/SHTI220675

PMID

35773821

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.


Language: en

Keywords

Children; Artificial Intelligence; Emotion Sensing; Mobile Application

NEW SEARCH


All SafetyLit records are available for automatic download to Zotero & Mendeley
Print