research-article

Analysis and Interpretation of Brain Wave Signals

Authors:

Christofer N. Yalung,

Salah Al Majeed,

Jalal KaramAuthors Info & Claims

ICC '16: Proceedings of the International Conference on Internet of things and Cloud Computing

Article No.: 67, Pages 1 - 8

https://doi.org/10.1145/2896387.2900319

Published: 22 March 2016 Publication History

Abstract

Brainwave Computer Interface (BCI) application has the potential to improve the quality of life for disabled patients and overall improvement of human thought concentration. In this paper, BCI is implemented using NeuroSky's EEG biosensor. Brain wave signal analysis is presented through the consideration of a noisy environment to simulate a BCI in real world application. A total of 256 data points are acquired in each thought. The data are documented using MATLAB software via Bluetooth. A real time recording is implemented with different captured thoughts among seven participants. The standard deviation of the Mean Sample Value (MSV) and Value Above Zero(VAZ) shows high variation for the thought of backward, forward, left and move in comparison of each trial. The VAZ rate and Zero Crossing Rate (ZCR) have very minimal standard deviation in comparison of each trial. This shows that the environment could affect the concentration of the signals. The average of the results of each thought is also presented, in which each thought has distinct characteristics among other thoughts. This means that classification is possible even noise or interruption is present in the surroundings and wireless transmission is utilized. The total number of peak points was recorded in each EEG sample. Also, the correlation coefficients among three participants having the same tasked were analyzed.

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Cited By

Gutierrez LHusain M(2019)Design and Development of a Mobile EEG Data Analytics Framework2019 IEEE Fifth International Conference on Big Data Computing Service and Applications (BigDataService)10.1109/BigDataService.2019.00059(333-339)Online publication date: Apr-2019
https://doi.org/10.1109/BigDataService.2019.00059

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Information

Published In

cover image ACM Other conferences

ICC '16: Proceedings of the International Conference on Internet of things and Cloud Computing

March 2016

535 pages

ISBN:9781450340632

DOI:10.1145/2896387

Editors:
Djallel Eddine Boubiche
University of Batna 2, Algeria
,
Faouzi Hidoussi
Hadj Lakhdar University, Algeria
,
Lyamine Guezouli
University of Batna 2, Algeria
,
Ahcène Bounceur
University of Western Britanny, France
,
Homero Toral Cruz
University of Quintana Roo, Mexico

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 March 2016

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ICC '16

ICC '16: International Conference on Internet of things and Cloud Computing

March 22 - 23, 2016

Cambridge, United Kingdom

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Cited By

Gutierrez LHusain M(2019)Design and Development of a Mobile EEG Data Analytics Framework2019 IEEE Fifth International Conference on Big Data Computing Service and Applications (BigDataService)10.1109/BigDataService.2019.00059(333-339)Online publication date: Apr-2019
https://doi.org/10.1109/BigDataService.2019.00059

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