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AttentivU: An EEG-Based Closed-Loop Biofeedback System for Real-Time Monitoring and Improvement of Engagement for Personalized Learning
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 com...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6929136/ https://www.ncbi.nlm.nih.gov/pubmed/31783646 http://dx.doi.org/10.3390/s19235200 |
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author | Kosmyna, Nataliya Maes, Pattie |
author_facet | Kosmyna, Nataliya Maes, Pattie |
author_sort | Kosmyna, Nataliya |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6929136 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-69291362019-12-26 AttentivU: An EEG-Based Closed-Loop Biofeedback System for Real-Time Monitoring and Improvement of Engagement for Personalized Learning Kosmyna, Nataliya Maes, Pattie Sensors (Basel) Article 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. MDPI 2019-11-27 /pmc/articles/PMC6929136/ /pubmed/31783646 http://dx.doi.org/10.3390/s19235200 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Kosmyna, Nataliya Maes, Pattie AttentivU: An EEG-Based Closed-Loop Biofeedback System for Real-Time Monitoring and Improvement of Engagement for Personalized Learning |
title | AttentivU: An EEG-Based Closed-Loop Biofeedback System for Real-Time Monitoring and Improvement of Engagement for Personalized Learning |
title_full | AttentivU: An EEG-Based Closed-Loop Biofeedback System for Real-Time Monitoring and Improvement of Engagement for Personalized Learning |
title_fullStr | AttentivU: An EEG-Based Closed-Loop Biofeedback System for Real-Time Monitoring and Improvement of Engagement for Personalized Learning |
title_full_unstemmed | AttentivU: An EEG-Based Closed-Loop Biofeedback System for Real-Time Monitoring and Improvement of Engagement for Personalized Learning |
title_short | AttentivU: An EEG-Based Closed-Loop Biofeedback System for Real-Time Monitoring and Improvement of Engagement for Personalized Learning |
title_sort | attentivu: an eeg-based closed-loop biofeedback system for real-time monitoring and improvement of engagement for personalized learning |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6929136/ https://www.ncbi.nlm.nih.gov/pubmed/31783646 http://dx.doi.org/10.3390/s19235200 |
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