[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
:: Volume 18, Number 7 (10-2015) ::
amuj 2015, 18(7): 1-16 Back to browse issues page
Studying the Independent Component Analysis (ICA) Algorithm for Detection and Separation of Two Conceptual Categories of the Words Danger and Information by Using Traffic Signs
Ehsan Imani , Ali Pourmohammad
MSc student Depatrment of Tehecommunications, Malek- Ashtar Industrial University, Tehran, Iran. , eh67.imani@gmail.com
Abstract:   (2128 Views)

  Background: In various researches, ICA is used for detecting and removing eye artifacts but here, for innovation, ICA algorithm is used not only for detecting eye artifacts, but also for detecting brain signals of two conceptual categories of the words Danger and Information.

  Materials and Methods: In this descriptive- analytical study, recording is done by using a Micromed device and a 19-channel helmet in unipolar mode that the Cz electrode is selected as reference electrode. The statistical community included four men and four women in the age range of 25-30. In the designed task, three groups of traffic signs are considered in which two groups refered to the concept of danger and the other one refered to the concept of information.

  Results: For two of the eight volunteers, alpha waves were observed with a very high power from back of the head in the test time, but it was different in thinking time. According to this alpha waves, in changing the task from thinking to rest, it takes at least 3 and at most 5 seconds for two volunteers till they go to the absolute rest. For seven of the eight volunteers, danger and information signals well separated that these differences for five of the eight volunteers observed in the right hemisphere and for the other three volunteers in the left hemisphere.

  Conclusion: ICA algorithm as one of Blind Source Seperation (BSS) algorithms is suitable for recognizing the word’s concept and its place in the brain. Achieved results from this experiment are the same as the results from other methods like fMRI and methods based on electroencephalograph (EEG) in vowel imagination and covert speech.

Keywords: Blind source separation (BSS), Brain-computer interfaces (BCI), Brain signals, Independent component analysis (ICA)
Full-Text [PDF 1556 kb]   (1354 Downloads)    
Type of Study: Original Atricle | Subject: Basic Sciences
Received: 2015/02/26 | Accepted: 2015/06/10 | Published: 2015/09/22
Send email to the article author

Add your comments about this article
Your username or email:

Write the security code in the box >



XML   Persian Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Imani E, Pourmohammad A. Studying the Independent Component Analysis (ICA) Algorithm for Detection and Separation of Two Conceptual Categories of the Words Danger and Information by Using Traffic Signs. amuj. 2015; 18 (7) :1-16
URL: http://amuj.arakmu.ac.ir/article-1-3536-en.html
Volume 18, Number 7 (10-2015) Back to browse issues page
مجله دانشگاه علوم پزشکی اراک Arak Medical University Journal
Persian site map - English site map - Created in 0.057 seconds with 787 queries by yektaweb 3506