Detecting Different Tasks Using EEG-Source-Temporal Features
This study proposes a new type of features extracted from Electroencephalography (EEG) signals to distinguish between different tasks. EEG signals are collected from six children aged between two to six years old during opened and closed eyes tasks. For each time-sample, Time Difference of Arriva...
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Online Access: | http://irep.iium.edu.my/28931/ http://irep.iium.edu.my/28931/ http://irep.iium.edu.my/28931/1/Detecting_Different_Tasks.pdf |
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iium-289312013-02-15T07:27:11Z http://irep.iium.edu.my/28931/ Detecting Different Tasks Using EEG-Source-Temporal Features Shams, Wafa Khazal Abdul Rahman, Abdul Wahab Qidwai, Uvais A. QA75 Electronic computers. Computer science This study proposes a new type of features extracted from Electroencephalography (EEG) signals to distinguish between different tasks. EEG signals are collected from six children aged between two to six years old during opened and closed eyes tasks. For each time-sample, Time Difference of Arrival (TDOA) is applied to EEG time series to compute the source-temporalfeatures that are assigned to x, y and z coordinates. The features are classified using neural network. The results show an accuracy of around 100% for eyes open task and around (83%-95%) for eyes closed tasks for the same subject. This study highlights the use of new types of features (source-temporal features), to characterize the brain functional behavior. 2012 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/28931/1/Detecting_Different_Tasks.pdf Shams, Wafa Khazal and Abdul Rahman, Abdul Wahab and Qidwai, Uvais A. (2012) Detecting Different Tasks Using EEG-Source-Temporal Features. In: Proceedings of Neural Information Processing - 19th International Conference, ICONIP 2012, November 12-15, 2012, Doha, Qata. http://download.springer.com/static/pdf/555/chp%253A10.1007%252F978-3-642-34478-7_47.pdf?auth66=1360482086_76e894c59a6cc78ca77432ba9544a88e&ext=.pdf |
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QA75 Electronic computers. Computer science |
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QA75 Electronic computers. Computer science Shams, Wafa Khazal Abdul Rahman, Abdul Wahab Qidwai, Uvais A. Detecting Different Tasks Using EEG-Source-Temporal Features |
description |
This study proposes a new type of features extracted from Electroencephalography
(EEG) signals to distinguish between different tasks. EEG signals
are collected from six children aged between two to six years old during
opened and closed eyes tasks. For each time-sample, Time Difference of Arrival
(TDOA) is applied to EEG time series to compute the source-temporalfeatures
that are assigned to x, y and z coordinates. The features are classified
using neural network. The results show an accuracy of around 100% for eyes
open task and around (83%-95%) for eyes closed tasks for the same subject.
This study highlights the use of new types of features (source-temporal features),
to characterize the brain functional behavior. |
format |
Conference or Workshop Item |
author |
Shams, Wafa Khazal Abdul Rahman, Abdul Wahab Qidwai, Uvais A. |
author_facet |
Shams, Wafa Khazal Abdul Rahman, Abdul Wahab Qidwai, Uvais A. |
author_sort |
Shams, Wafa Khazal |
title |
Detecting Different Tasks Using EEG-Source-Temporal Features |
title_short |
Detecting Different Tasks Using EEG-Source-Temporal Features |
title_full |
Detecting Different Tasks Using EEG-Source-Temporal Features |
title_fullStr |
Detecting Different Tasks Using EEG-Source-Temporal Features |
title_full_unstemmed |
Detecting Different Tasks Using EEG-Source-Temporal Features |
title_sort |
detecting different tasks using eeg-source-temporal features |
publishDate |
2012 |
url |
http://irep.iium.edu.my/28931/ http://irep.iium.edu.my/28931/ http://irep.iium.edu.my/28931/1/Detecting_Different_Tasks.pdf |
first_indexed |
2023-09-18T20:42:30Z |
last_indexed |
2023-09-18T20:42:30Z |
_version_ |
1777409458243108864 |