感官-ASD:一个社会情感培养和技能增强系统,用于自闭症谱系障碍
Haya Abu-Nowar1, Adeeb Sait1, Tawfik Al-Hadhrami1
1Computer Science Department, School of Science and Technology, Nottingham Trent University, Nottingham, United Kingdom.
PeerJ. Computer science
|March 4, 2024
概括
这项研究介绍了SENSES-ASD,一种使用CNN的深度学习系统,以帮助自闭症成年人识别情绪. 该系统旨在改善自闭症谱系障碍 (ASD) 患者的社交互动和沟通技巧.
科学领域:
- 人工智能的人工智能
- 神经科学是一个神经科学.
- 心理学 心理学 心理学
背景情况:
- 自闭症谱系障碍 (ASD) 在社会情感理解方面提出了挑战.
- 越来越多地探索技术干预措施来支持患有自闭症的人.
- 面部情绪识别是改善社交互动的关键领域.
研究的目的:
- 引入社会情感培养和技能提升系统 (SENSES-ASD).
- 利用深度学习来提高ASD患者的面部情绪识别能力.
- 开发一个对高功能自闭症成年人的需求敏感的用户界面.
主要方法:
- 利用深度学习,特别是卷积神经网络 (CNN).
- 使用在FER-2013数据集上训练的Xception CNN模型.
- 开发了一种能够从各种媒体输入中分类七种主要情绪状态的系统.
主要成果:
- 在培训数据集上达到71%的峰值准确度.
- 在验证数据集上达到66%的准确性.
- 证明成功地对主要情绪状态进行分类和预测.
结论:
- 该SENSES-ASD系统为ASD干预提供了一种创新的技术方法.
- 该系统的新之处在于其量身定制的深度学习方法和灵敏的用户界面.
- 这项工作为在高功能自闭症成年人中使用人工智能进行情绪识别提供了新的视角.
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