000			01854 am a22002413u 4500
042			_adc
100	1	0	_aTeng, Clare _eauthor _92258
700	1	0	_aSharma, Harshita _eauthor _92259
700	1	0	_aDrukker, Lior _eauthor
700	1	0	_aPapageorghiou, Aris T. _eauthor
700	1	0	_aNoble, Alison J. _eauthor
245	0	0	_aVisualising Spatio-Temporal Gaze Characteristics for Exploratory Data Analysis in Clinical Fetal Ultrasound Scans
260			_c2022-06.
500			_a/pmc/articles/PMC7614061/
500			_a/pubmed/36649381
520			_aVisualising patterns in clinicians' eye movements while interpreting fetal ultrasound imaging videos is challenging. Across and within videos, there are differences in size an d position of Areas-of-Interest (AOIs) due to fetal position, movement and sonographer skill. Currently, AOIs are manually labelled or identified using eye-tracker manufacturer specifications which are not study specific. We propose using unsupervised clustering to identify meaningful AOIs and bi-contour plots to visualise spatio-temporal gaze characteristics. We use Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) to identify the AOIs, and use their corresponding images to capture granular changes within each AOI. Then we visualise transitions within and between AOIs as read by the sonographer. We compare our method to a standardised eye-tracking manufacturer algorithm. Our method captures granular changes in gaze characteristics which are otherwise not shown. Our method is suitable for exploratory data analysis of eye-tracking data involving multiple participants and AOIs.
540			_a
546			_aen
690			_aArticle
655	7		_aText _2local
786	0		_nProc Eye Track Res Appl Symp
856	4	1	_uhttp://dx.doi.org/10.1145/3517031.3529635 _zConnect to this object online.
999			_c2056 _d2056