An automated segmentation approach to calibrating infantile nystagmus waveforms 2013-2019

Dunn, Matt J (2019). An automated segmentation approach to calibrating infantile nystagmus waveforms 2013-2019. [Data Collection]. Colchester, Essex: UK Data Service. 10.5255/UKDA-SN-853460

Data description (abstract)

Infantile nystagmus (IN) describes a regular, repetitive movement of the eyes. A characteristic feature of each cycle of the IN eye movement waveform is a period in which the eyes are moving at minimal velocity. This so-called ‘foveation’ period has long been considered the basis for best vision in individuals with IN. In recent years, the technology for measuring eye movements has improved considerably, but there remains the challenge of calibrating the direction of gaze in tracking systems when the eyes are continuously moving. Identifying portions of the nystagmus waveform suitable for calibration typically involves time-consuming manual selection of foveation periods from the eye trace. Without an accurate calibration, the exact parameters of the waveform cannot be determined. In this study, we present an automated method for segmenting IN waveforms with the purpose of determining foveation positions to be used for calibration of an eye tracker. On average, the ‘point of regard’ was found to be within 0.21° of that determined by hand-marking by an expert observer. This method enables rapid clinical quantification of waveforms and the possibility of gaze-contingent research paradigms in this patient group.

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