基于远程边缘的智能自闭症谱系障碍学习系统 医疗保健诊所和医疗物联网
Mazin Abed Mohammed1, Saleh Alyahya2, Abdulrahman Abbas Mukhlif1
1College of Computer Science and Information Technology, University of Anbar, Anbar 31001, Iraq.
Sensors (Basel, Switzerland)
|December 17, 2024
概括
本研究介绍了一个使用智能手表和人工智能的智能系统,以改善自闭症谱系障碍 (ASD) 儿童的学习. 该系统提高了学习成绩和准确性,同时减少了教育应用程序的处理时间.
科学领域:
- 人工智能的人工智能
- 医疗保健技术 技术 医疗保健 技术
- 特殊教育 特殊教育
背景情况:
- 自闭症谱系障碍 (ASD) 影响儿童的学习,需要优化教育技术.
- 现有的方法往往缺乏针对自闭症儿童的个性化,可访问的学习环境.
- 远程医疗和物联网集成为改善ASD教育提供了潜力.
研究的目的:
- 为自闭症儿童开发智能学习系统,使用远程边缘医疗保健和医疗物联网 (IoMT).
- 为患有自闭症儿童提供面向儿童的综合在线教育和医疗保健环境.
- 为ASD优化学习应用程序,重点关注服务质量 (QoS) 和处理约束.
主要方法:
- 该研究提出了智能手表自闭症谱数据学习方案 (SM-ASDS).
- SM-ASDS使用分区卸载和深度学习模型 (DCNN,ALSTM) 来在各种设备上进行数据训练.
- 应用程序运行在智能手表,移动设备和边缘节点上,考虑精度和处理时间等优化约束.
主要成果:
- 在SM-ASDS计划中,学习成绩提高了30%.
- 与基线方法相比,准确度提高了98%.
- 总处理时间减少了33%.
结论:
- 开发的基于智能手表的系统有效地促进了自闭症患者的教育培训.
- 集成到系统中的人工智能技术显著改善了ASD的学习成果.
- 该系统为自闭症儿童提供了一种有前途的在线教育和医疗保健方法.
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