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利用视频游戏检测 ADHD 儿童的注意力水平,并使用单通道脑机接口耳机测量大脑活动。

Detecting Attention Levels in ADHD Children with a Video Game and the Measurement of Brain Activity with a Single-Channel BCI Headset.

机构信息

Department of Experimental Psychology, Faculty of Psychology, Universidad de Sevilla, 41018 Seville, Spain.

Department of Experimental Psychology, Faculty of Psychology and Educational Sciences, University of Ghent, 9000 Ghent, Belgium.

出版信息

Sensors (Basel). 2021 May 6;21(9):3221. doi: 10.3390/s21093221.

Abstract

Attentional biomarkers in attention deficit hyperactivity disorder are difficult to detect using only behavioural testing. We explored whether attention measured by a low-cost EEG system might be helpful to detect a possible disorder at its earliest stages. The GokEvolution application was designed to train attention and to provide a measure to identify attentional problems in children early on. Attention changes registered with NeuroSky MindWave in combination with the CARAS-R psychological test were used to characterise the attentional profiles of 52 non-ADHD and 23 ADHD children aged 7 to 12 years old. The analyses revealed that the GokEvolution was valuable in measuring attention through its use of EEG-BCI technology. The ADHD group showed lower levels of attention and more variability in brain attentional responses when compared to the control group. The application was able to map the low attention profiles of the ADHD group when compared to the control group and could distinguish between participants who completed the task and those who did not. Therefore, this system could potentially be used in clinical settings as a screening tool for early detection of attentional traits in order to prevent their development.

摘要

仅通过行为测试很难发现注意缺陷多动障碍(ADHD)的注意力生物标志物。我们探讨了通过低成本 EEG 系统测量注意力是否有助于在最早阶段检测到可能的障碍。GokEvolution 应用程序旨在训练注意力,并提供一种在早期识别儿童注意力问题的方法。使用 NeuroSky MindWave 记录的注意力变化和 CARAS-R 心理测试结合,用于描述 52 名非 ADHD 和 23 名 ADHD 年龄在 7 至 12 岁的儿童的注意力特征。分析表明,GokEvolution 通过使用 EEG-BCI 技术来衡量注意力是有价值的。与对照组相比,ADHD 组的注意力水平较低,大脑注意力反应的变异性更大。该应用程序能够将 ADHD 组的注意力低下特征与对照组进行映射,并能够区分完成任务的参与者和未完成任务的参与者。因此,该系统有可能在临床环境中用作早期检测注意力特征的筛查工具,以防止其发展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f244/8124980/f52552116067/sensors-21-03221-g001.jpg

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