Classification of EEG Signal for Body Earthing Application

Stress is the way of our body reacts to the threat and any kind of demand. Stress happened when your nervous system are released the stress hormones including adrenaline and cortisol that lead to emergency responds of the body. Body earthing technique is used to resolve this problem. Body earthing i...

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Main Authors:	Noor Aisyah , Ab Rahman, Mahfuzah, Mustafa, Rosdiyana, Samad, Nor Rul Hasma, Abdullah, Norizam, Sulaiman, Pebrianti, Dwi
Format:	Conference or Workshop Item
Language:	English English
Published:	2017
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/19720/ http://umpir.ump.edu.my/id/eprint/19720/1/Classification%20of%20EEG%20Signal%20for%20Body%20Earthing%20Application.pdf http://umpir.ump.edu.my/id/eprint/19720/7/Classification%20of%20EEG%20Signal%20for%20Body%20Earthing%20Application%201.pdf

id	ump-19720
recordtype	eprints
spelling	ump-197202018-02-20T03:02:30Z http://umpir.ump.edu.my/id/eprint/19720/ Classification of EEG Signal for Body Earthing Application Noor Aisyah , Ab Rahman Mahfuzah, Mustafa Rosdiyana, Samad Nor Rul Hasma, Abdullah Norizam, Sulaiman Pebrianti, Dwi TK Electrical engineering. Electronics Nuclear engineering Stress is the way of our body reacts to the threat and any kind of demand. Stress happened when your nervous system are released the stress hormones including adrenaline and cortisol that lead to emergency responds of the body. Body earthing technique is used to resolve this problem. Body earthing is a method that used for neutralize positive and negative charge in human body by connected to the earth. EEG signals can be used to verify the positive effect of body earthing. This project focuses on the classification of EEG signals for body earthing application. First, EEG signals from human brainwaves were recorded by using Emotive EPOC Headset, before and after body earthing for the 30 subjects. Alpha band and Beta band were filtered by using Band-pass filter ‘Butterworth’. After filtering, the threshold of signal amplitude was set in the range of -100 μV to 100 μV in order to remove the noise or artifact. For feature extraction, Short-time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT) were used. Lastly, the Artificial Neural Networks (ANN) model is employed to classify EEG signal taken from samples, before and after the body earthing. Number of neuron chosen for this project is 55 with the mean square error 0.0023738. Result showed that Alpha band signals before body earthing are low compare to after body earthing. While, for the Beta band signals, the result before body earthing is high compare to after body earthing. Alpha band signals increased shows that subjects are in relax state, while the Beta band signals decreased shows sample in stress state. These results imply for both feature of STFT and CWT. Based on confusion matrix, the result for the ANN classification yields that 86.7% of classification are correct. 2017 Conference or Workshop Item NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/19720/1/Classification%20of%20EEG%20Signal%20for%20Body%20Earthing%20Application.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/19720/7/Classification%20of%20EEG%20Signal%20for%20Body%20Earthing%20Application%201.pdf Noor Aisyah , Ab Rahman and Mahfuzah, Mustafa and Rosdiyana, Samad and Nor Rul Hasma, Abdullah and Norizam, Sulaiman and Pebrianti, Dwi (2017) Classification of EEG Signal for Body Earthing Application. In: 4th International Conference On Electrical, Control & Computer Engineering (INECCE2017), 16-17 October 2017 , Hotel Adya, Langkawi. pp. 1-6.. (Unpublished)
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Noor Aisyah , Ab Rahman Mahfuzah, Mustafa Rosdiyana, Samad Nor Rul Hasma, Abdullah Norizam, Sulaiman Pebrianti, Dwi Classification of EEG Signal for Body Earthing Application
description	Stress is the way of our body reacts to the threat and any kind of demand. Stress happened when your nervous system are released the stress hormones including adrenaline and cortisol that lead to emergency responds of the body. Body earthing technique is used to resolve this problem. Body earthing is a method that used for neutralize positive and negative charge in human body by connected to the earth. EEG signals can be used to verify the positive effect of body earthing. This project focuses on the classification of EEG signals for body earthing application. First, EEG signals from human brainwaves were recorded by using Emotive EPOC Headset, before and after body earthing for the 30 subjects. Alpha band and Beta band were filtered by using Band-pass filter ‘Butterworth’. After filtering, the threshold of signal amplitude was set in the range of -100 μV to 100 μV in order to remove the noise or artifact. For feature extraction, Short-time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT) were used. Lastly, the Artificial Neural Networks (ANN) model is employed to classify EEG signal taken from samples, before and after the body earthing. Number of neuron chosen for this project is 55 with the mean square error 0.0023738. Result showed that Alpha band signals before body earthing are low compare to after body earthing. While, for the Beta band signals, the result before body earthing is high compare to after body earthing. Alpha band signals increased shows that subjects are in relax state, while the Beta band signals decreased shows sample in stress state. These results imply for both feature of STFT and CWT. Based on confusion matrix, the result for the ANN classification yields that 86.7% of classification are correct.
format	Conference or Workshop Item
author	Noor Aisyah , Ab Rahman Mahfuzah, Mustafa Rosdiyana, Samad Nor Rul Hasma, Abdullah Norizam, Sulaiman Pebrianti, Dwi
author_facet	Noor Aisyah , Ab Rahman Mahfuzah, Mustafa Rosdiyana, Samad Nor Rul Hasma, Abdullah Norizam, Sulaiman Pebrianti, Dwi
author_sort	Noor Aisyah , Ab Rahman
title	Classification of EEG Signal for Body Earthing Application
title_short	Classification of EEG Signal for Body Earthing Application
title_full	Classification of EEG Signal for Body Earthing Application
title_fullStr	Classification of EEG Signal for Body Earthing Application
title_full_unstemmed	Classification of EEG Signal for Body Earthing Application
title_sort	classification of eeg signal for body earthing application
publishDate	2017
url	http://umpir.ump.edu.my/id/eprint/19720/ http://umpir.ump.edu.my/id/eprint/19720/1/Classification%20of%20EEG%20Signal%20for%20Body%20Earthing%20Application.pdf http://umpir.ump.edu.my/id/eprint/19720/7/Classification%20of%20EEG%20Signal%20for%20Body%20Earthing%20Application%201.pdf
first_indexed	2023-09-18T22:28:15Z
last_indexed	2023-09-18T22:28:15Z
_version_	1777416111972679680

Classification of EEG Signal for Body Earthing Application

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