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...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Trans Tech Publications Ltd., Switzerland
2013
|
| Subjects: | |
| Online Access: | http://irep.iium.edu.my/32214/ http://irep.iium.edu.my/32214/1/AMM.373-375.1768.pdf |
| _version_ | 1848780520302837760 |
|---|---|
| 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 |
| building | IIUM Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-14T15:34:58Z |
| format | Article |
| id | iium-32214 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T15:34:58Z |
| publishDate | 2013 |
| publisher | Trans Tech Publications Ltd., Switzerland |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-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 |
| spellingShingle | T Technology (General) Ismail, Elliana Ghazali, Aimi Shazwani Sidek, Shahrul Na'im Physiological signal – based Engagement Level Analysis under fuzzy framework |
| title | 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_short | Physiological signal – based Engagement Level Analysis under fuzzy framework |
| title_sort | physiological signal – based engagement level analysis under fuzzy framework |
| topic | T Technology (General) |
| url | http://irep.iium.edu.my/32214/ http://irep.iium.edu.my/32214/ http://irep.iium.edu.my/32214/1/AMM.373-375.1768.pdf |