IDEA: Index of Difficulty for Eye tracking Applications. An Analysis Model for Target Selection Tasks, HUCAPP, 2021

IDEA: Index of Difficulty for Eye tracking Applications. An Analysis Model for Target Selection Tasks, HUCAPP, 2021

ICT lab researcher Mohsen Parisay will be presenting our work “IDEA: Index of Difficulty for Eye Tracking Applications. An Analysis Model for Target Selection Tasks”. The work was co-authored by Mohsen Parisay, Charalambos Poullis, and Marta Kersten.

Abstract:
Fitts’ law is a prediction model to measure the difficulty level of target selection for pointing devices. However, emerging devices and interaction techniques require more flexible parameters to adopt the original Fitts’ law to new circumstances and case scenarios. We propose Index of Difficulty for Eye tracking Applications (IDEA) which integrates Fitts’ law with users’ feedback from the NASA TLX to measure the difficulty of target selection. The COVID-19 pandemic has shown the necessity of contact-free interactions on public and shared devices, thus in this work, we aim to propose a model for evaluating contact-free interaction techniques, which can accurately measure the difficulty of eye tracking applications and can be adapted to children, users with disabilities, and elderly without requiring the acquisition of physiological sensory data. We tested the IDEA model using data from a three-part user study with 33 participants that compared two eye tracking selection techniques, dwell-time, and a multi-modal eye tracking technique using voice commands.