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AttentivU:基于 EEG 的闭环生物反馈系统,用于实时监测和提升个性化学习中的参与度。

AttentivU: An EEG-Based Closed-Loop Biofeedback System for Real-Time Monitoring and Improvement of Engagement for Personalized Learning.

机构信息

MIT Media Lab, 75 Amherst St, E14-548, Cambridge, MA 02139, USA.

出版信息

Sensors (Basel). 2019 Nov 27;19(23):5200. doi: 10.3390/s19235200.

DOI:10.3390/s19235200
PMID:31783646
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6929136/
Abstract

Information about a person's engagement and attention might be a valuable asset in many settings including work situations, driving, and learning environments. To this end, we propose the first prototype of a device called AttentivU-a system that uses a wearable system which consists of two main components. Component 1 is represented by an EEG headband used to measure the engagement of a person in real-time. Component 2 is a scarf, which provides subtle, haptic feedback (vibrations) in real-time when the drop in engagement is detected. We tested AttentivU in two separate studies with 48 adults. The participants were engaged in a learning scenario of either watching three video lectures on different subjects or participating in a set of three face-to-face lectures with a professor. There were three conditions administrated during both studies: (1) biofeedback, meaning the scarf (component 2 of the system) was vibrating each time the EEG headband detected a drop in engagement; (2) random feedback, where the vibrations did not correlate or depend on the engagement level detected by the system, and (3) no feedback, when no vibrations were administered. The results show that the biofeedback condition redirected the engagement of the participants to the task at hand and improved their performance on comprehension tests.

摘要

关于一个人的参与度和注意力的信息可能是许多场景中的宝贵资产,包括工作环境、驾驶和学习环境。为此,我们提出了一种名为 AttentivU 的设备的第一个原型,该系统使用一个由两个主要组件组成的可穿戴系统。组件 1 由一个 EEG 头带表示,用于实时测量一个人的参与度。组件 2 是一条围巾,当检测到参与度下降时,它会实时提供微妙的触觉反馈(振动)。我们在两项独立的研究中测试了 AttentivU,共有 48 名成年人参与。参与者在观看三个关于不同主题的视频讲座或与教授进行三组面对面讲座的学习场景中进行了学习。在这两项研究中都进行了三种条件管理:(1)生物反馈,即系统的围巾(组件 2)每次检测到头带检测到参与度下降时都会振动;(2)随机反馈,其中振动与系统检测到的参与度水平不相关或不依赖,以及(3)无反馈,即不进行振动。结果表明,生物反馈条件将参与者的注意力重新引导到手头的任务上,并提高了他们在理解测试中的表现。

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本文引用的文献

1
Brain-computer-interface-based intervention re-normalizes brain functional network topology in children with attention deficit/hyperactivity disorder.基于脑-机接口的干预使注意缺陷多动障碍儿童的大脑功能网络拓扑结构恢复正常。
Transl Psychiatry. 2018 Aug 10;8(1):149. doi: 10.1038/s41398-018-0213-8.
2
Removal of movement artifact from high-density EEG recorded during walking and running.行走和跑步时高密度 EEG 中运动伪迹的去除。
J Neurophysiol. 2010 Jun;103(6):3526-34. doi: 10.1152/jn.00105.2010. Epub 2010 Apr 21.
3
Analysis of the dynamical behaviour of the EEG rhythms during a test of sustained attention.
基于机器学习算法的可穿戴式脑电图神经反馈对自闭症儿童的影响:一项随机、安慰剂对照研究。
Curr Med Sci. 2024 Dec;44(6):1141-1147. doi: 10.1007/s11596-024-2938-3. Epub 2024 Nov 20.
4
Effects of Frontal-Midline Theta Neurofeedback with Different Training Directions on Goal-Directed Attentional Control.不同训练方向的额中线θ波神经反馈对目标导向性注意力控制的影响
Appl Psychophysiol Biofeedback. 2025 Mar;50(1):11-23. doi: 10.1007/s10484-024-09673-y. Epub 2024 Nov 5.
5
Neuroergonomic Attention Assessment in Safety-Critical Tasks: EEG Indices and Subjective Metrics Validation in a Novel Task-Embedded Reaction Time Paradigm.安全关键任务中的神经工效学注意力评估:在新型任务嵌入反应时范式中对脑电图指标和主观指标的验证
Brain Sci. 2024 Oct 7;14(10):1009. doi: 10.3390/brainsci14101009.
6
Enhancing learning experiences: EEG-based passive BCI system adapts learning speed to cognitive load in real-time, with motivation as catalyst.增强学习体验:基于脑电图的被动脑机接口系统以动机为催化剂,实时根据认知负荷调整学习速度。
Front Hum Neurosci. 2024 Oct 7;18:1416683. doi: 10.3389/fnhum.2024.1416683. eCollection 2024.
7
Electroencephalogram-based adaptive closed-loop brain-computer interface in neurorehabilitation: a review.神经康复中基于脑电图的自适应闭环脑机接口:综述
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8
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9
A comprehensive study on the efficacy of a wearable sleep aid device featuring closed-loop real-time acoustic stimulation.一款具有闭环实时声刺激功能的可穿戴睡眠辅助设备的疗效综合研究。
Sci Rep. 2023 Oct 16;13(1):17515. doi: 10.1038/s41598-023-43975-1.
10
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BMC Med. 2023 Sep 29;21(1):372. doi: 10.1186/s12916-023-03076-2.
在持续注意力测试期间脑电图节律的动态行为分析。
Annu Int Conf IEEE Eng Med Biol Soc. 2007;2007:1298-301. doi: 10.1109/IEMBS.2007.4352535.
4
EEG correlates of task engagement and mental workload in vigilance, learning, and memory tasks.警觉、学习和记忆任务中任务参与度和心理负荷的脑电图相关性。
Aviat Space Environ Med. 2007 May;78(5 Suppl):B231-44.
5
Vigilance, alertness, or sustained attention: physiological basis and measurement.警觉、警醒或持续注意力:生理基础与测量
Clin Neurophysiol. 2006 Sep;117(9):1885-901. doi: 10.1016/j.clinph.2006.01.017. Epub 2006 Apr 3.
6
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7
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Biol Psychol. 1996 Feb 5;42(3):249-68. doi: 10.1016/0301-0511(95)05161-9.
8
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Biol Psychol. 1995 May;40(1-2):187-95. doi: 10.1016/0301-0511(95)05116-3.