GraFIX: Developing a novel semi-automatic approach for detecting fixation durations in low quality data from infants and adults I Rodriguez Saez de Urabain, M H Johnson, T J Smith |
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Centre for Brain and Cognitive Development, Birkbeck, University of London, United Kingdom
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| Fixation durations (FD) have been used widely as a measurement of information processing in infants. Common issues with testing infants (e.g. high degree of movement, unreliable eye detection) result in highly variable data quality and render existing FD detection approaches highly time consuming (hand-coding) or imprecise (automatic detection). To address this problem we developed GraFIX, a novel semi-automatic method consisting of a two-step process in which eye-tracking data is initially parsed by using adaptive velocity and dispersal-based algorithms, before it is hand-coded using the graphical interface, allowing accurate and rapid adjustments of the algorithms’ outcome. The present algorithms (1) smooth the rough data, (2) interpolate missing data points, and (3) apply a number of criteria to evaluate and remove artifactual fixations. The input parameters (e.g. velocity threshold, interpolation latency) can be easily manually adapted to fit each participant. We assessed this method by testing its reliability in data from over 100 infants ranging from 3 to 12-month-old and comparing it with previous methods regarding expenditure of time and accuracy of detection. Results revealed that being able to adapt FD detection criteria and hand-code its outcome gives rise to more reliable and stable measures in infants. |
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