对ADHD的多模式方法与儿童的ASD共存检测
Jungpil Shin1, Sota Konnai2, Md Maniruzzaman3
1School of Computer Science and Engineering, The University of Aizu, Aizuwakamatsu, Fukushima, 965-8580, Japan. jpshin@u-aizu.ac.jp.
Scientific reports
|July 2, 2025
概括
这项研究开发了一种使用手写和大脑活动来识别注意力缺陷/多动障碍 (ADHD) 和自闭症谱系障碍 (ASD) 的儿童的新多式方法,达到96.4%的准确率.
科学领域:
- 神经科学是一个神经科学.
- 发展心理学 发展心理学
- 生物医学工程 生物医学工程
背景情况:
- 在儿童中诊断同时出现的注意力缺陷/多动症障碍 (ADHD) 和自闭症谱系障碍 (ASD) 存在重大挑战,原因是症状重叠.
- 现有的诊断方法往往缺乏客观性,并可能受到主观评估的影响.
研究的目的:
- 开发和验证一种新的多式联络方法来识别与ASD共存的ADHD儿童.
- 将手写动态和大脑活动的数据融合在一起,以提高诊断准确度.
主要方法:
- 开发了一种多模式方法,整合了笔板数据 (写字动态) 和功能近红外光谱 (fNIRs) 数据 (大脑活动).
- 患有多动症和自闭症的儿童,与典型发育 (TD) 的儿童一起,在追踪和预测条件下执行手写任务 (齐格扎克线和周期线).
- 来自数据源和条件的特征被融合在一起,并使用了带有支向量机 (SVM) 分类器的顺序前向浮动选择 (SFFS) 算法进行评估.
主要成果:
- 拟议的多式联网方法在周期线 (PL) 任务中实现了96.4%的分类准确度.
- 与现有的诊断研究相比,这种准确性代表了超过2%的改进.
- 该方法在区分患有ADHD和同时存在的ASD儿童与TD儿童方面显示出显著的潜力.
结论:
- 开发的多式联络方法提供了一个有希望的客观工具,用于诊断儿童的ADHD与ASD共存.
- 这种方法可以帮助临床医生提供更准确和及时的诊断.
- 这项研究为患有ADHD和ASD的儿童的神经发育特征提供了新的见解.
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