Feasibility Study on Estimating Visual Attention using Electrodermal Activity

Publications

Share / Export Citation / Email / Print / Text size:

International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

Exeley Inc. (New York)

Subject: Computational Science & Engineering, Engineering, Electrical & Electronic

GET ALERTS

eISSN: 1178-5608

DESCRIPTION

8
Reader(s)
16
Visit(s)
0
Comment(s)
0
Share(s)

VOLUME 7 , ISSUE 5 (December 2014) > List of articles

Special issue ICST 2014

Feasibility Study on Estimating Visual Attention using Electrodermal Activity

Ryuichi Yoshida / Tomohiro Nakayama / Takeki Ogitsu / Hiroshi Takemura / Hiroshi Mizoguchi / Miki Namatame / Etsuji Yamaguchi / Shigenori Inagaki / Yoshiaki Takeda / Masanori Sugimoto / Fusako Kusunoki

Keywords : skin conductance response; Precuing Methsis; Visual Search

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 7, Issue 5, Pages 1-4, DOI: https://doi.org/10.21307/ijssis-2019-050

License : (CC BY-NC-ND 4.0)

Published Online: 15-February-2020

ARTICLE

ABSTRACT

Electrodermal Activity (EDA) refers to change in the electrical properties of skin during mental exertion caused by tension and agitation. In recent studies, it has been revealed that there is an overlap between the brain activation area where emotion occurs and the brain activation area responsible for attentiveness. Consequently, in this paper we test our hypothesis that, given these findings, visual attention can be estimated via EDA. The results of experiments conducted verify that EDA can be used as an attention index.

Content not available PDF Share

FIGURES & TABLES

REFERENCES

[1] Torch W, Cardillo C, “Oculometric measures as an index of driver distraction, inattention, drowsiness and sleep onset,” Driver Distraction and Inattention Conference, 2009.

[2] Hermann MJ, Plichta MM, Ehlis AC, Fallgatter AJ, “Optical topography during a Go-NoGo task assessed with multichannel near-infrared spectoroscopy,” Behavioural Brain Research 160, 2005, pp. 135-140.

[3] Kurniawan H, Maslov AV, Pechenizkiy M, “Stress detection from speech and galvanic skin response signals,” 26th IEEE International Symposium on Computer-Based Medical Systems, 2013, pp.209-214.

[4] Weistroffer V, Paljic A, Callebert L, Fuchs P, “A methodology to assess the acceptability of human-robot collaboration using virtual reality,” 19th ACM Symposium on Virtual Reality Software and Technology, 2013, pp. 39-48.

[5] Posner MI, Snyder CR, Davidson BJ, “Attention and the detection of signals,” Journal of Experimental Psychology: General, 109, 1908, pp. 160-174.  

[6] Treisman A, “Feature and Objects in visual processing,” Scientific American, 254(11), 1986, pp. 114-125.

EXTRA FILES

COMMENTS