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EEG Signal Analysis in Decision Making.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	EEG Signal Analysis in Decision Making./
Author:	Salma, Nabila.
Description:	1 online resource (74 pages)
Notes:	Source: Masters Abstracts International, Volume: 57-04.
Contained By:	Masters Abstracts International57-04(E).
Subject:	Electrical engineering. -
Online resource:	click for full text (PQDT)
ISBN:	9780355560305

EEG Signal Analysis in Decision Making.
Salma, Nabila.

EEG Signal Analysis in Decision Making. - 1 online resource (74 pages)

Source: Masters Abstracts International, Volume: 57-04.

Thesis (M.S.)--University of North Texas, 2017.

Includes bibliographical references

Decision making can be a complicated process involving perception of the present situation, past experience and knowledge necessary to foresee a better future. This cognitive process is one of the essential human ability that is required from everyday walk of life to making major life choices. Although it may seem ambiguous to translate such a primitive process into quantifiable science, the goal of this thesis is to break it down to signal processing and quantifying the thought process with prominence of EEG signal power variance. This paper will discuss the cognitive science, the signal processing of brain signals and how brain activity can be quantifiable through data analysis. An experiment is analyzed in this thesis to provide evidence that theta frequency band activity is associated with stress and stress is negatively correlated with concentration and problem solving, therefore hindering decision making skill. From the results of the experiment, it is seen that theta is negatively correlated to delta and beta frequency band activity, thus establishing the fact that stress affects internal focus while carrying out a task.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355560305Subjects--Topical Terms:

596380
Electrical engineering.
Index Terms--Genre/Form:

554714
Electronic books.

EEG Signal Analysis in Decision Making.
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035 $a (MiAaPQ)AAI10753897
035 $a (MiAaPQ)0158vireo:664Salma
035 $a AAI10753897
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Salma, Nabila. $3 1194254
245 1 0 $a EEG Signal Analysis in Decision Making.
264 0 $c 2017
300 $a 1 online resource (74 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Masters Abstracts International, Volume: 57-04.
500 $a Advisers: Kamesh Namuduri; Vijay Vaidyanathan.
502 $a Thesis (M.S.)--University of North Texas, 2017.
504 $a Includes bibliographical references
520 $a Decision making can be a complicated process involving perception of the present situation, past experience and knowledge necessary to foresee a better future. This cognitive process is one of the essential human ability that is required from everyday walk of life to making major life choices. Although it may seem ambiguous to translate such a primitive process into quantifiable science, the goal of this thesis is to break it down to signal processing and quantifying the thought process with prominence of EEG signal power variance. This paper will discuss the cognitive science, the signal processing of brain signals and how brain activity can be quantifiable through data analysis. An experiment is analyzed in this thesis to provide evidence that theta frequency band activity is associated with stress and stress is negatively correlated with concentration and problem solving, therefore hindering decision making skill. From the results of the experiment, it is seen that theta is negatively correlated to delta and beta frequency band activity, thus establishing the fact that stress affects internal focus while carrying out a task.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Electrical engineering. $3 596380
655 7 $a Electronic books. $2 local $3 554714
690 $a 0544
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a University of North Texas. $b Department of Electrical Engineering. $3 1194253
773 0 $t Masters Abstracts International $g 57-04(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10753897 $z click for full text (PQDT)