Analysing low-quality eye-tracking data

I’ve been involved in many eye-tracking studies with infants and young children as the participant group. While eye tracking can provide valuable insights into (cognitive) development, eye-tracking data obtained from infants and children are generally of lower quality as compared with eye-tracking data from adults. This is in part due to the fact that infants are difficult to restrain in their movement. I’ve been involved in two eye-tracker tests in which we compared eye trackers on their robustness to movement (view the first and the second here). Moreover, I’ve developed a fixation-classification algorithm that is specifically built for eye-tracking data of low quality. The software is freely available from GitHub.

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