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Physiological signal – based Engagement Level Analysis under fuzzy framework

The paper presents real-time affective state detection, in particular, the engagement level detection by using physiological signals under fuzzy framework. In order to develop the fuzzy model, the engagement model is developed by using data collected from controlled design experiment. In measuring...

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Main Authors: Ismail, Elliana, Ghazali, Aimi Shazwani, Sidek, Shahrul Na'im
Format: Article
Language:English
Published: Trans Tech Publications Ltd., Switzerland 2013
Subjects:
T Technology (General)
Online Access:http://irep.iium.edu.my/32214/1/AMM.373-375.1768.pdf
http://irep.iium.edu.my/32214/
http://www.scientific.net/AMM.373-375.1768
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spelling my.iium.irep.322142020-02-14T01:46:03Z http://irep.iium.edu.my/32214/ Physiological signal – based Engagement Level Analysis under fuzzy framework Ismail, Elliana Ghazali, Aimi Shazwani Sidek, Shahrul Na'im T Technology (General) The paper presents real-time affective state detection, in particular, the engagement level detection by using physiological signals under fuzzy framework. In order to develop the fuzzy model, the engagement model is developed by using data collected from controlled design experiment. In measuring the level of engagement, the physiological signals; namely the Electrooculogram (EOG) is recorded using G-tec data acquisition system. In the experiment, the data collected are the average endogenous eye blinks and the average trajectory errors recorded from the trajectory that the subjects have to follow in completing specific tasks. For the tasks, the subjects are asked to track a set of prescribed paths within the allocated times and have to obey different speed constraints. Various shapes of trajectories are given to the subjects in order to study the level of engagement while performing the task. The data then are used to develop the fuzzy model to measure the level of engagement (LOE) of the subjects. Following the experiments, a series of questionnaires are given to the subjects to verify their engagement level when performing the experiments. Preliminary analysis on the data shows a good match between the experimental results and the questionnaire. Trans Tech Publications Ltd., Switzerland 2013 Article PeerReviewed application/pdf en http://irep.iium.edu.my/32214/1/AMM.373-375.1768.pdf Ismail, Elliana and Ghazali, Aimi Shazwani and Sidek, Shahrul Na'im (2013) Physiological signal – based Engagement Level Analysis under fuzzy framework. Applied Mechanics and Materials, 373-35. pp. 1768-1775. ISSN 1660-9336 http://www.scientific.net/AMM.373-375.1768
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
topic T Technology (General)
spellingShingle T Technology (General)
Ismail, Elliana
Ghazali, Aimi Shazwani
Sidek, Shahrul Na'im
Physiological signal – based Engagement Level Analysis under fuzzy framework
description The paper presents real-time affective state detection, in particular, the engagement level detection by using physiological signals under fuzzy framework. In order to develop the fuzzy model, the engagement model is developed by using data collected from controlled design experiment. In measuring the level of engagement, the physiological signals; namely the Electrooculogram (EOG) is recorded using G-tec data acquisition system. In the experiment, the data collected are the average endogenous eye blinks and the average trajectory errors recorded from the trajectory that the subjects have to follow in completing specific tasks. For the tasks, the subjects are asked to track a set of prescribed paths within the allocated times and have to obey different speed constraints. Various shapes of trajectories are given to the subjects in order to study the level of engagement while performing the task. The data then are used to develop the fuzzy model to measure the level of engagement (LOE) of the subjects. Following the experiments, a series of questionnaires are given to the subjects to verify their engagement level when performing the experiments. Preliminary analysis on the data shows a good match between the experimental results and the questionnaire.
format Article
author Ismail, Elliana
Ghazali, Aimi Shazwani
Sidek, Shahrul Na'im
author_facet Ismail, Elliana
Ghazali, Aimi Shazwani
Sidek, Shahrul Na'im
author_sort Ismail, Elliana
title Physiological signal – based Engagement Level Analysis under fuzzy framework
title_short Physiological signal – based Engagement Level Analysis under fuzzy framework
title_full Physiological signal – based Engagement Level Analysis under fuzzy framework
title_fullStr Physiological signal – based Engagement Level Analysis under fuzzy framework
title_full_unstemmed Physiological signal – based Engagement Level Analysis under fuzzy framework
title_sort physiological signal – based engagement level analysis under fuzzy framework
publisher Trans Tech Publications Ltd., Switzerland
publishDate 2013
url http://irep.iium.edu.my/32214/1/AMM.373-375.1768.pdf
http://irep.iium.edu.my/32214/
http://www.scientific.net/AMM.373-375.1768
_version_ 1662753697142145024
score 13.211869

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