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Entropy 2016, 18(11), 390;

Possibility of Using Entropy Method to Evaluate the Distracting Effect of Mobile Phones on Pedestrians

Department of Industrial Management, National Taiwan University of Science and Technology, Taipei City 10607, Taiwan
Author to whom correspondence should be addressed.
Academic Editor: Anne Humeau-Heurtier
Received: 7 September 2016 / Revised: 20 October 2016 / Accepted: 28 October 2016 / Published: 4 November 2016
(This article belongs to the Special Issue Multivariate Entropy Measures and Their Applications)
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The number of mobile phone users keeps increasing every year and mobile phones have become a primary need for most people. Ordinarily, people are not aware of the risk from a common dual-task study, such as using a mobile phone while walking or simply standing. This study reviewed the methodology in evaluating the distracting effect of mobile phones on pedestrians. A comprehensive review of literature revealed that the most common method in quantifying pedestrian performance is to evaluate postural task performance. Since using a mobile phone while crossing the road is a type of dual-task study, it would give more clarity to investigate it using entropy methods that have been proven more sensitive than the traditional center of pressure (COP) in discriminating the changes in human balance. The descriptions of commonly used entropy methods were also given in order to give a broad overview of the possibility in applying the methods to further clarify the distracting effect of mobile phones. View Full-Text
Keywords: mobile phone; walking; standing; pedestrian; dual-task; entropy mobile phone; walking; standing; pedestrian; dual-task; entropy
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Nurwulan, N.R.; Jiang, B.C. Possibility of Using Entropy Method to Evaluate the Distracting Effect of Mobile Phones on Pedestrians. Entropy 2016, 18, 390.

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