Online Testing and Webcam Based Eye Tracking Technologies: A Comparative Study with Laboratory Standards and Future Directions for Development

Abstract

Online behavioural experiments are vital across various domains, including academia, market research, and clinical studies. The incorporation of advanced technologies like eye tracking offers immense value for patients with restricted clinic access. Online research provides several benefits, including broad participant recruitment, ease of access via home or mobile devices, and substantial technological capabilities. Numerous cutting-edge web technology applications utilise eye trackers for fixation detection, blink saccades, and potentially, future pupillary and pulse detection. These indicators pave the way for expanded opportunities in behavioural research. This PhD thesis specifically examines webcam-based eye tracking implemented in an online behavioural research application. We compared the online system with the gold-standard laboratory EyeLink 1000, presenting a series of tests that provided a detailed analysis of both technologies in relation to established benchmarks and metrics. Additionally, we showcased the technology’s application in recording data from Parkinson’s and dementia patients in various medical environments, with a control group recruited in a home setting. The thesis concluded with an in-depth discussion of potential advancements, including AI utilization to enhance existing algorithms and technology applications, as well as addressing potential limitations related to technology, research recruitment, and personal data protection. The objective of this work was to delineate the prospective direction and evolution of web technologies while acknowledging the potential limitations and challenges that lie ahead