Evaluating bad and good EEG segments based on extracted features: towards an automated understanding of infant behavior and attention

Evaluating bad and good EEG segments based on extracted features: towards an automated understanding of infant behavior and attention

The field of brain computer interference has grown rapidly with the purpose of reading a human’s mind, generating a certain output, controlling objects with this output and having an automated understanding of human reactions and responses to the surrounding environment. Electroencephal...

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Bibliographic Details
Main Authors: Sharif, Mhd Saeed, Alsibai, Mohammed Hayyan, Kushnerenko, Elena
Format: Conference or Workshop Item
Language:English
English
Published: IEEE 2018
Subjects:
T Technology (General)
Online Access:http://umpir.ump.edu.my/id/eprint/20199/
http://umpir.ump.edu.my/id/eprint/20199/
http://umpir.ump.edu.my/id/eprint/20199/1/Evaluating%20Bad%20and%20Good%20EEG%20Segments%20Based%20on%20Extracted%20Features.pdf
http://umpir.ump.edu.my/id/eprint/20199/2/Evaluating%20Bad%20and%20Good%20EEG%20Segments%20Based%20on%20Extracted%20Features.pdf
id ump-20199
recordtype eprints
spelling ump-201992018-07-27T04:27:37Z http://umpir.ump.edu.my/id/eprint/20199/ Evaluating bad and good EEG segments based on extracted features: towards an automated understanding of infant behavior and attention Sharif, Mhd Saeed Alsibai, Mohammed Hayyan Kushnerenko, Elena T Technology (General) The field of brain computer interference has grown rapidly with the purpose of reading a human’s mind, generating a certain output, controlling objects with this output and having an automated understanding of human reactions and responses to the surrounding environment. Electroencephalography (EEG) may provide an insight into human behavior and attention. There is a huge need in different fields, e.g. psychology and medical, for an automated approach that helps the psychologist in dealing with the massive amount of data in a sensible period. This research study proposes an approach to extract some features from infant EEG signals and evaluate the effect of the bad or good EEG channels on different EEG segments. The achieved work will provide an insight about the employment of the most suitable features to represent the EEG data. The acquired infant EEG data will be deployed to build an objectively evaluated framework that has the ability to provide an automated understanding of the infants’ behavior, underpin the infant specialists in analyzing the infant attentions for stimuli within different environments. IEEE 2018-02 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/20199/1/Evaluating%20Bad%20and%20Good%20EEG%20Segments%20Based%20on%20Extracted%20Features.pdf pdf en http://umpir.ump.edu.my/id/eprint/20199/2/Evaluating%20Bad%20and%20Good%20EEG%20Segments%20Based%20on%20Extracted%20Features.pdf Sharif, Mhd Saeed and Alsibai, Mohammed Hayyan and Kushnerenko, Elena (2018) Evaluating bad and good EEG segments based on extracted features: towards an automated understanding of infant behavior and attention. In: 7th IEEE International Conference on Control System, Computing and Engineering (ICCSCE), 24-26 November 2017 , Penang, Malaysia. pp. 1-6.. https://doi.org/10.1109/ICCSCE.2017.8284385
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
English
topic T Technology (General)
spellingShingle T Technology (General)
Sharif, Mhd Saeed
Alsibai, Mohammed Hayyan
Kushnerenko, Elena
Evaluating bad and good EEG segments based on extracted features: towards an automated understanding of infant behavior and attention
description The field of brain computer interference has grown rapidly with the purpose of reading a human’s mind, generating a certain output, controlling objects with this output and having an automated understanding of human reactions and responses to the surrounding environment. Electroencephalography (EEG) may provide an insight into human behavior and attention. There is a huge need in different fields, e.g. psychology and medical, for an automated approach that helps the psychologist in dealing with the massive amount of data in a sensible period. This research study proposes an approach to extract some features from infant EEG signals and evaluate the effect of the bad or good EEG channels on different EEG segments. The achieved work will provide an insight about the employment of the most suitable features to represent the EEG data. The acquired infant EEG data will be deployed to build an objectively evaluated framework that has the ability to provide an automated understanding of the infants’ behavior, underpin the infant specialists in analyzing the infant attentions for stimuli within different environments.
format Conference or Workshop Item
author Sharif, Mhd Saeed
Alsibai, Mohammed Hayyan
Kushnerenko, Elena
author_facet Sharif, Mhd Saeed
Alsibai, Mohammed Hayyan
Kushnerenko, Elena
author_sort Sharif, Mhd Saeed
title Evaluating bad and good EEG segments based on extracted features: towards an automated understanding of infant behavior and attention
title_short Evaluating bad and good EEG segments based on extracted features: towards an automated understanding of infant behavior and attention
title_full Evaluating bad and good EEG segments based on extracted features: towards an automated understanding of infant behavior and attention
title_fullStr Evaluating bad and good EEG segments based on extracted features: towards an automated understanding of infant behavior and attention
title_full_unstemmed Evaluating bad and good EEG segments based on extracted features: towards an automated understanding of infant behavior and attention
title_sort evaluating bad and good eeg segments based on extracted features: towards an automated understanding of infant behavior and attention
publisher IEEE
publishDate 2018
url http://umpir.ump.edu.my/id/eprint/20199/
http://umpir.ump.edu.my/id/eprint/20199/
http://umpir.ump.edu.my/id/eprint/20199/1/Evaluating%20Bad%20and%20Good%20EEG%20Segments%20Based%20on%20Extracted%20Features.pdf
http://umpir.ump.edu.my/id/eprint/20199/2/Evaluating%20Bad%20and%20Good%20EEG%20Segments%20Based%20on%20Extracted%20Features.pdf
first_indexed 2023-09-18T22:28:58Z
last_indexed 2023-09-18T22:28:58Z
_version_ 1777416157301571584

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