DocumentCode :
2496491
Title :
Analyzing effect of distraction caused by dual-tasks on sharing of brain resources using SOM
Author :
Wang, Yu-Kai ; Pal, Nikhil R. ; Lin, Chin-Teng ; Chen, Shi-An
Author_Institution :
Dept. of Comput. Sci., Nat. Chiao-Tung Univ., Hsinchu, Taiwan
fYear :
2010
fDate :
18-23 July 2010
Firstpage :
1
Lastpage :
6
Abstract :
Drivers´ distraction is widely recognized as a leading cause of car accidents. To investigate the distracting effect of dual-tasks involving driving and answering mathematical equations in the stimulus onset asynchrony (SOA) conditions, we design five different cases: two cases involving single-tasks and three cases involving dual-tasks. We have found that there is no statistically significant change in the behavioral data among the three dual-tasks. This raises an important question - is there any detectable effect of the dual tasks on the brain waves? To answer this, we use the Self-Organizing Map (SOM) to recognize the changes, if any, in the Electroencephalography (EEG) dynamics associated with such dual-tasks. Our SOM analysis based on independent components corresponding to EEG signals extracted from Frontal and Motor areas revealed that single- and dual-tasks have distinguishable signatures in the EEG signals. Specifically, each of the two single-task conditions is clustered in a distinct spatial area of the map. Two of the dual-tasks also exhibit distinct spatial clusters, while the third case although shows differences from the other two, the neurons corresponding to this case are sub-clustered reflecting the fact that different subjects may give different priorities to the tasks when confronted with two tasks simultaneously. SOM-based exploratory analysis reveals the existence of distinct EEG signatures among the distracting and non-distracting tasks, although there is no any noticeable difference in the behavioral data among these cases.
Keywords :
behavioural sciences computing; electroencephalography; self-organising feature maps; statistical analysis; traffic engineering computing; EEG signals; brain resources; drivers distraction; electroencephalography dynamics; mathematical equations; self-organizing map; stimulus onset asynchrony; Accuracy; Brain; Electroencephalography; Equations; Feature extraction; Mathematical model; Neurons;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks (IJCNN), The 2010 International Joint Conference on
Conference_Location :
Barcelona
ISSN :
1098-7576
Print_ISBN :
978-1-4244-6916-1
Type :
conf
DOI :
10.1109/IJCNN.2010.5596860
Filename :
5596860
Link To Document :
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