Secure, digitized data collection of human subjects information and experimental logs.
Jasmine Kim 1, Sohail Rafiqi 2, and Eric Larson 3
1 Department of Physics, Department of Mathematics, Southern Methodist University
2,3 Department of Computer Science and Engineering, Southern Methodist University
Date : June, 2014 - August, 2014 (Summer Research Assistant)
What's the motivation?
Cognitive load refers to the amount of effort required by an individual to process information. Dating back more than fifty years, the cognitive psychology community has conducted experiments on cognitive loads. These experiments have shown that the cognitive load experienced by an individual can be measured using sub-millimeter fluctuations in their pupil size, assessed using medical grade infrared devices known as pupillometers, and more recently, infrared eye-trackers. However, the cost and availability of these eye-trackers limit most pupil response measurements to laboratory settings. We argue that ubiquitously measuring pupillary response could transform the next generation of context aware computing applications—enabling computational devices to understand a user’s current ability to process information, especially for users with cognitive disabilities.
To this end, we present PupilWare, a system that analyzes pupil size changes through commodity cameras like those in a laptop. We evaluate PupilWare’s ability to measure changes in pupil dilation using classic cognitive psychology experiments. In addition, we validate its performance compared to infrared gaze trackers and medical grade pupillometers. We conclude that, in controlled conditions, PupilWare is as accurate as infrared eye-tracking for assessing a task evoked cognitive load, though it has problems with dark eyed individuals and eyelid occlusion.
What was needed?
In order to perform psychological experiments and collect data, we need a platform to store participants' information more efficiently. The user interface is created to store both demographics and test data of the participants. The information stores predetermined ID numbers instead of names for privacy purposes.
Create an iOS platform that can store demographic information and test data of experiment participants (Program in Objective C using Xcode on an iOS machine).
Format functionality for users to easily navigate through the platform.
Receive instant feedback from potential user for improvement.