Correction to: Detecting deception using machine learning with facial expressions and pulse rate

Artificial Life and Robotics -     

A link selection method for web‐browser using eye‐gaze input

Methods for browsing Web pages using eye‐gaze input have been proposed for severely physically handicapped people who cannot handle a computer mouse to utilize convenient services on the Internet. There are two important functions for Web‐browsers, namely scroll and link selection. Since it is difficult to introduce existing link selection methods using eye‐gaze input for home usage because of high costs or complexity, we propose in this paper a novel link selection method using eye‐gaze input. The proposed method analyzes the HTML source in a Web page and makes a group of links by the content of each. In evaluation experiments, we compare the proposed method with a comparative method using eye‐gaze input with respect to the average response time in selecting the links. The results of the experiments show that the average response is nearly twice as fast as that of the compared method. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.