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Received:December 31, 2020 Revised:January 29, 2021
Received:December 31, 2020 Revised:January 29, 2021
中文摘要: 青少年注意力不集中的现象在生活中十分普遍, 而现有的青少年注意力检测和训练系统功能单一. 因此, 本文研发了一个基于脑电信号的青少年注意力检测和训练系统. 针对注意力检测分类少、准确率低的问题, 本文将注意力分为5类, 并提出基于随机森林模型的注意力检测方法以改进检测的准确率, 达76.17%; 针对注意力效果不佳的问题, 本文基于闭环脑电生物反馈感知技术, 首次根据持续型注意力、选择型注意力和集中型注意力, 分别设计3个面向青少年的严肃游戏训练模式, 并提出4个评估指标进行实验, 排除游戏熟悉程度对受试者影响的同时, 结合自身对照法验证了注意力训练的有效性.
中文关键词: 注意力检测 注意力训练 随机森林模型 闭环脑电生物反馈技术 严肃游戏
Abstract:The phenomenon of impaired concentration is common among adolescents, but the existing systems for attention detection and training are equipped with simplistic functions. This study develops an attention detection and training system based on EEG signals for adolescents. In light of few classifications and low accuracy in attention detection, we divide attention into five categories and propose an attention detection method based on the random forest model for higher detection accuracy which arrives at 76.17%. With regard to the deficiencies in unsatisfied effect of attention training, we design three serious game training modes for adolescents in terms of sustained attention, selective attention, and focus attention for the first time using the EEG-based closed-loop biofeedback technology. Meanwhile, to verify the effectiveness of the attention training mode, we define four indicators to conduct experiments with the self-control method while excluding the influence of familiarity with the game on subjects.
keywords: attention detection attention training random forest model EEG-based closed-loop biofeedback technology serious game
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基金项目:国家自然科学基金面上项目(62076103); 广州市重点领域研发计划(202007030005); 广东省自然科学基金面上项目(2019A1515011375)
引用文本:
王冰冰,许泽举,罗通,潘家辉.基于脑电信号的青少年注意力检测和训练系统.计算机系统应用,2021,30(10):76-85
WANG Bing-Bing,XU Ze-Ju,LUO Tong,PAN Jia-Hui.Attention Detection and Training System for Adolescents Based on EEG Signals.COMPUTER SYSTEMS APPLICATIONS,2021,30(10):76-85
王冰冰,许泽举,罗通,潘家辉.基于脑电信号的青少年注意力检测和训练系统.计算机系统应用,2021,30(10):76-85
WANG Bing-Bing,XU Ze-Ju,LUO Tong,PAN Jia-Hui.Attention Detection and Training System for Adolescents Based on EEG Signals.COMPUTER SYSTEMS APPLICATIONS,2021,30(10):76-85