Visualization and quantification of eye tracking data for the evaluation of oculomotor function
Oculomotor dysfunction may originate from physical, physiological or psychological causes and may be a marker for schizophrenia or other disorders. Observational tests for oculomotor dysfunction are easy to administer, but are subjective and transient, and it is difficult to quantify deviations. To...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2019-01-01
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| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844018348709 |
| _version_ | 1818778472353366016 |
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| author | Pieter Blignaut Elize Janse van Rensburg Marsha Oberholzer |
| author_facet | Pieter Blignaut Elize Janse van Rensburg Marsha Oberholzer |
| author_sort | Pieter Blignaut |
| collection | DOAJ |
| description | Oculomotor dysfunction may originate from physical, physiological or psychological causes and may be a marker for schizophrenia or other disorders. Observational tests for oculomotor dysfunction are easy to administer, but are subjective and transient, and it is difficult to quantify deviations. To date, video-based eye tracking systems have not provided a contextual overview of gaze data that integrates the eye video recording with the stimulus and gaze data together with quantitative feedback of metrics in relation to typical values. A system was developed with an interactive timeline to allow the analyst to scroll through a recording frame-by-frame while comparing data from three different sources. The visual and integrated nature of the analysis allows localisation and quantification of saccadic under- and overshoots as well as determination of the frequency and amplitude of catch-up and anticipatory saccades. Clinicians will be able to apply their expertise to diagnose disorders based on abnormal patterns in the gaze plots. They can use the line charts to quantify deviations from benchmark values for reaction time, saccadic accuracy and smooth pursuit gain. A clinician can refer to the eye video at any time to confirm that observed deviations originated from gaze behaviour and not from systemic errors. |
| first_indexed | 2024-12-18T11:45:16Z |
| format | Article |
| id | doaj.art-e13a960f86ae41dd983644f861f208df |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-12-18T11:45:16Z |
| publishDate | 2019-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-e13a960f86ae41dd983644f861f208df2022-12-21T21:09:19ZengElsevierHeliyon2405-84402019-01-0151e01127Visualization and quantification of eye tracking data for the evaluation of oculomotor functionPieter Blignaut0Elize Janse van Rensburg1Marsha Oberholzer2Department of Computer Science and Informatics, University of the Free State, South Africa; Corresponding author.Department of Occupational Therapy, University of the Free State, South AfricaDepartment of Optometry, University of the Free State, South AfricaOculomotor dysfunction may originate from physical, physiological or psychological causes and may be a marker for schizophrenia or other disorders. Observational tests for oculomotor dysfunction are easy to administer, but are subjective and transient, and it is difficult to quantify deviations. To date, video-based eye tracking systems have not provided a contextual overview of gaze data that integrates the eye video recording with the stimulus and gaze data together with quantitative feedback of metrics in relation to typical values. A system was developed with an interactive timeline to allow the analyst to scroll through a recording frame-by-frame while comparing data from three different sources. The visual and integrated nature of the analysis allows localisation and quantification of saccadic under- and overshoots as well as determination of the frequency and amplitude of catch-up and anticipatory saccades. Clinicians will be able to apply their expertise to diagnose disorders based on abnormal patterns in the gaze plots. They can use the line charts to quantify deviations from benchmark values for reaction time, saccadic accuracy and smooth pursuit gain. A clinician can refer to the eye video at any time to confirm that observed deviations originated from gaze behaviour and not from systemic errors.http://www.sciencedirect.com/science/article/pii/S2405844018348709Computer scienceMedical imaging |
| spellingShingle | Pieter Blignaut Elize Janse van Rensburg Marsha Oberholzer Visualization and quantification of eye tracking data for the evaluation of oculomotor function Heliyon Computer science Medical imaging |
| title | Visualization and quantification of eye tracking data for the evaluation of oculomotor function |
| title_full | Visualization and quantification of eye tracking data for the evaluation of oculomotor function |
| title_fullStr | Visualization and quantification of eye tracking data for the evaluation of oculomotor function |
| title_full_unstemmed | Visualization and quantification of eye tracking data for the evaluation of oculomotor function |
| title_short | Visualization and quantification of eye tracking data for the evaluation of oculomotor function |
| title_sort | visualization and quantification of eye tracking data for the evaluation of oculomotor function |
| topic | Computer science Medical imaging |
| url | http://www.sciencedirect.com/science/article/pii/S2405844018348709 |
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