Next Article in Journal
A Multi-Stage Method for Connecting Participatory Sensing and Noise Simulations
Next Article in Special Issue
Adding Pluggable and Personalized Natural Control Capabilities to Existing Applications
Previous Article in Journal
A Chronoamperometric Screen Printed Carbon Biosensor Based on Alkaline Phosphatase Inhibition for W(VI) Determination in Water, Using 2-Phospho-l-Ascorbic Acid Trisodium Salt as a Substrate
Previous Article in Special Issue
A Survey of Online Activity Recognition Using Mobile Phones
Article Menu

Export Article

Open AccessArticle
Sensors 2015, 15(2), 2244-2264;

Eye/Head Tracking Technology to Improve HCI with iPad Applications

DeustoTech-Life Research Unit. DeustoTech Institute of Technology, University of Deusto, Avda. Universidades, 24. 48007 Bilbao, Spain
These authors contributed equally to this work.
Author to whom correspondence should be addressed.
Received: 6 November 2014 / Revised: 28 November 2014 / Accepted: 12 January 2015 / Published: 22 January 2015
(This article belongs to the Special Issue HCI In Smart Environments)
Full-Text   |   PDF [826 KB, uploaded 23 January 2015]   |  


In order to improve human computer interaction (HCI) for people with special needs, this paper presents an alternative form of interaction, which uses the iPad’s front camera and eye/head tracking technology. With this functional nature/capability operating in the background, the user can control already developed or new applications for the iPad by moving their eyes and/or head. There are many techniques, which are currently used to detect facial features, such as eyes or even the face itself. Open source bookstores exist for such purpose, such as OpenCV, which enable very reliable and accurate detection algorithms to be applied, such as Haar Cascade using very high-level programming. All processing is undertaken in real time, and it is therefore important to pay close attention to the use of limited resources (processing capacity) of devices, such as the iPad. The system was validated in tests involving 22 users of different ages and characteristics (people with dark and light-colored eyes and with/without glasses). These tests are performed to assess user/device interaction and to ascertain whether it works properly. The system obtained an accuracy of between 60% and 100% in the three test exercises taken into consideration. The results showed that the Haar Cascade had a significant effect by detecting faces in 100% of cases, unlike eyes and the pupil where interference (light and shade) evidenced less effectiveness. In addition to ascertaining the effectiveness of the system via these exercises, the demo application has also helped to show that user constraints need not affect the enjoyment and use of a particular type of technology. In short, the results obtained are encouraging and these systems may continue to be developed if extended and updated in the future. View Full-Text
Keywords: HCI; eye/head tracking; blinking; iPad; Haar Cascade HCI; eye/head tracking; blinking; iPad; Haar Cascade

Graphical abstract

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).

Share & Cite This Article

MDPI and ACS Style

Lopez-Basterretxea, A.; Mendez-Zorrilla, A.; Garcia-Zapirain, B. Eye/Head Tracking Technology to Improve HCI with iPad Applications. Sensors 2015, 15, 2244-2264.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top