Multimodal BCI system for user's performance assessment

As technology advances, more learning materials for students are shifted to an online platform. Learning through online platform must be engaging enough for the students to stay focus and continue learning. Thus, it is crucial to evaluate the engagement level of the students. Multimodal Brain Comput...

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Main Author: Nageshwari Rajadharen
Other Authors: Zhong Wende
Format: Final Year Project
Language:English
Published: 2018
Subjects:
Online Access:http://hdl.handle.net/10356/74453
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-744532023-07-07T17:34:23Z Multimodal BCI system for user's performance assessment Nageshwari Rajadharen Zhong Wende School of Electrical and Electronic Engineering A*STAR Institute for Infocomm Research DRNTU::Science As technology advances, more learning materials for students are shifted to an online platform. Learning through online platform must be engaging enough for the students to stay focus and continue learning. Thus, it is crucial to evaluate the engagement level of the students. Multimodal Brain Computer Interface (BCI) system is developed to effectively assess the learning performance of the students. Two different experiments were conducted. For the 1st experiment, electroencephalogram (EEG), gaze positions and photoplethysmogram (PPG) of the students are recorded. For the 2nd experiment, gaze positions and EEG of the students are recorded. Features are extracted from each modality. Data analysis are conducted to analyse the features extracted in depth. Results have revealed that the eye-tracker used is of high accuracy and music does distract the students as their attention level tends to decrease. Not only that, it is also observed that the students showed negative feelings towards the end of the experiment. Using only one modality is not sufficient to assess the engagement level of the students, hence the multimodal system is able to assess visual and mental engagement more accurately. These will aid educators to better assess and understand students’ response towards the learning materials and their performance, enabling more effective intervention and meaningful improvements in learning materials. Bachelor of Engineering 2018-05-18T02:47:43Z 2018-05-18T02:47:43Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/74453 en Nanyang Technological University 57 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Science
spellingShingle DRNTU::Science
Nageshwari Rajadharen
Multimodal BCI system for user's performance assessment
description As technology advances, more learning materials for students are shifted to an online platform. Learning through online platform must be engaging enough for the students to stay focus and continue learning. Thus, it is crucial to evaluate the engagement level of the students. Multimodal Brain Computer Interface (BCI) system is developed to effectively assess the learning performance of the students. Two different experiments were conducted. For the 1st experiment, electroencephalogram (EEG), gaze positions and photoplethysmogram (PPG) of the students are recorded. For the 2nd experiment, gaze positions and EEG of the students are recorded. Features are extracted from each modality. Data analysis are conducted to analyse the features extracted in depth. Results have revealed that the eye-tracker used is of high accuracy and music does distract the students as their attention level tends to decrease. Not only that, it is also observed that the students showed negative feelings towards the end of the experiment. Using only one modality is not sufficient to assess the engagement level of the students, hence the multimodal system is able to assess visual and mental engagement more accurately. These will aid educators to better assess and understand students’ response towards the learning materials and their performance, enabling more effective intervention and meaningful improvements in learning materials.
author2 Zhong Wende
author_facet Zhong Wende
Nageshwari Rajadharen
format Final Year Project
author Nageshwari Rajadharen
author_sort Nageshwari Rajadharen
title Multimodal BCI system for user's performance assessment
title_short Multimodal BCI system for user's performance assessment
title_full Multimodal BCI system for user's performance assessment
title_fullStr Multimodal BCI system for user's performance assessment
title_full_unstemmed Multimodal BCI system for user's performance assessment
title_sort multimodal bci system for user's performance assessment
publishDate 2018
url http://hdl.handle.net/10356/74453
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