The effects of human brainwave signals due to mobile phone radio frequency exposure using artificial neural network / Roshakimah Mohd Isa

The frequency content of recorded electroencephalogram (EEG) signals plays an important role in describing the signals and also the state of the brain. It is found that the emitted of radiofrequency (RF) radiation energy due to the usage of mobile phones contributes to the changes of brainwave signa...

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Bibliographic Details
Main Author:	Mohd Isa, Roshakimah
Format:	Book Section
Language:	English
Published:	Institute of Graduate Studies, UiTM 2018
Subjects:	Radio Radio frequency identification systems Microelectronics
Online Access:	http://ir.uitm.edu.my/id/eprint/20543/ http://ir.uitm.edu.my/id/eprint/20543/1/ABS_ROSHAKIMAH%20MOHD%20ISA%20TDRA%20VOL%2013%20IGS%2018.pdf

id	uitm-20543
recordtype	eprints
spelling	uitm-205432018-07-06T06:21:53Z http://ir.uitm.edu.my/id/eprint/20543/ The effects of human brainwave signals due to mobile phone radio frequency exposure using artificial neural network / Roshakimah Mohd Isa Mohd Isa, Roshakimah Radio Radio frequency identification systems Microelectronics The frequency content of recorded electroencephalogram (EEG) signals plays an important role in describing the signals and also the state of the brain. It is found that the emitted of radiofrequency (RF) radiation energy due to the usage of mobile phones contributes to the changes of brainwave signals. Nevertheless, it is yet to be determined the effects of RF exposure to human’s health that related to the brain based on EEG and intelligent approach. Therefore this thesis proposed a novel approach for recognizing the characteristics of brainwave signals due to mobile phone RF exposure using intelligent techniques. The presented thought recognition methodology utilises correlation and asymmetry features between EEG and RF exposure and integrated with feed-forward Artificial Neural Networks (ANN) for classification. The procedures involved EEG recording at the frontal; left and right head and have been conducted in three sessions namely Before, During and After RF exposure. The duration of each session is five minutes. Ninety five volunteers involved in this study and they are divided into three exposure groups, which categorised as Left Exposure (LE), Right Exposure (RE) and Sham Exposure (SE) group. The RF exposure used in the experiment is sourced from a mobile phone with operating bandwidth between 0.9 to 2.2 GHz with 0.69 W/kg SAR rate. Then, the analysis to observe the brain hemisphere dominance due to the mobile phone RF exposure has been carried out through the Power Asymmetry Ratio (PAR) features… Institute of Graduate Studies, UiTM 2018 Book Section PeerReviewed text en http://ir.uitm.edu.my/id/eprint/20543/1/ABS_ROSHAKIMAH%20MOHD%20ISA%20TDRA%20VOL%2013%20IGS%2018.pdf Mohd Isa, Roshakimah (2018) The effects of human brainwave signals due to mobile phone radio frequency exposure using artificial neural network / Roshakimah Mohd Isa. In: The Doctoral Research Abstracts. IGS Biannual Publication, 18 (18). Institute of Graduate Studies, UiTM, Shah Alam.
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Teknologi MARA
building	UiTM Institutional Repository
collection	Online Access
language	English
topic	Radio Radio frequency identification systems Microelectronics
spellingShingle	Radio Radio frequency identification systems Microelectronics Mohd Isa, Roshakimah The effects of human brainwave signals due to mobile phone radio frequency exposure using artificial neural network / Roshakimah Mohd Isa
description	The frequency content of recorded electroencephalogram (EEG) signals plays an important role in describing the signals and also the state of the brain. It is found that the emitted of radiofrequency (RF) radiation energy due to the usage of mobile phones contributes to the changes of brainwave signals. Nevertheless, it is yet to be determined the effects of RF exposure to human’s health that related to the brain based on EEG and intelligent approach. Therefore this thesis proposed a novel approach for recognizing the characteristics of brainwave signals due to mobile phone RF exposure using intelligent techniques. The presented thought recognition methodology utilises correlation and asymmetry features between EEG and RF exposure and integrated with feed-forward Artificial Neural Networks (ANN) for classification. The procedures involved EEG recording at the frontal; left and right head and have been conducted in three sessions namely Before, During and After RF exposure. The duration of each session is five minutes. Ninety five volunteers involved in this study and they are divided into three exposure groups, which categorised as Left Exposure (LE), Right Exposure (RE) and Sham Exposure (SE) group. The RF exposure used in the experiment is sourced from a mobile phone with operating bandwidth between 0.9 to 2.2 GHz with 0.69 W/kg SAR rate. Then, the analysis to observe the brain hemisphere dominance due to the mobile phone RF exposure has been carried out through the Power Asymmetry Ratio (PAR) features…
format	Book Section
author	Mohd Isa, Roshakimah
author_facet	Mohd Isa, Roshakimah
author_sort	Mohd Isa, Roshakimah
title	The effects of human brainwave signals due to mobile phone radio frequency exposure using artificial neural network / Roshakimah Mohd Isa
title_short	The effects of human brainwave signals due to mobile phone radio frequency exposure using artificial neural network / Roshakimah Mohd Isa
title_full	The effects of human brainwave signals due to mobile phone radio frequency exposure using artificial neural network / Roshakimah Mohd Isa
title_fullStr	The effects of human brainwave signals due to mobile phone radio frequency exposure using artificial neural network / Roshakimah Mohd Isa
title_full_unstemmed	The effects of human brainwave signals due to mobile phone radio frequency exposure using artificial neural network / Roshakimah Mohd Isa
title_sort	effects of human brainwave signals due to mobile phone radio frequency exposure using artificial neural network / roshakimah mohd isa
publisher	Institute of Graduate Studies, UiTM
publishDate	2018
url	http://ir.uitm.edu.my/id/eprint/20543/ http://ir.uitm.edu.my/id/eprint/20543/1/ABS_ROSHAKIMAH%20MOHD%20ISA%20TDRA%20VOL%2013%20IGS%2018.pdf
first_indexed	2023-09-18T23:04:48Z
last_indexed	2023-09-18T23:04:48Z
_version_	1777418411370872832

The effects of human brainwave signals due to mobile phone radio frequency exposure using artificial neural network / Roshakimah Mohd Isa

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