Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/77973
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dc.contributorDepartment of Electronic and Information Engineering-
dc.creatorChen, ZH-
dc.creatorFu, H-
dc.creatorLo, WL-
dc.creatorChi, Z-
dc.creatorXu, B-
dc.date.accessioned2018-08-28T01:35:59Z-
dc.date.available2018-08-28T01:35:59Z-
dc.identifier.urihttp://hdl.handle.net/10397/77973-
dc.language.isoenen_US
dc.publisherInstitution of Engineering and Technologyen_US
dc.rights© 2018 Healthcare Technology Letters published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology. This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)en_US
dc.rightsThe following publication Chen, Z. H., Fu, H., Lo, W. L., Chi, Z., & Xu, B. (2018). Eye-tracking-aided digital system for strabismus diagnosis. Healthcare technology letters, 5(1), 1-6 is available at https://doi.org/10.1049/htl.2016.0081en_US
dc.titleEye-tracking-aided digital system for strabismus diagnosisen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1-
dc.identifier.epage6-
dc.identifier.volume5-
dc.identifier.issue1-
dc.identifier.doi10.1049/htl.2016.0081-
dcterms.abstractStrabismus is one of the most common vision disorders in preschool children. It can cause amblyopia and even permanent vision loss. In addition to a vision problem, strabismus brings to both children and adults serious negative impacts in their daily life, education, employment etc. Timely diagnosis of strabismus is thus crucial. However, traditional diagnosis methods conducted by ophthalmologists rely significantly on their experiences, making the diagnosis results subjective. It is also inconvenient for those methods being used for strabismus examination in large communities such as schools. In light of that, in this Letter, the authors develop an objective, digital and automatic system based on eye-tracking technique for diagnosing strabismus. The system exploits eye-tracking technique to acquire a person’s eye gaze data while he or she is looking at some targets. A group of features are proposed to characterise the gaze data. The person’s strabismus condition can be diagnosed according to the features. A strabismus gaze dataset is built using the system. Experimental results on the dataset demonstrate the effectiveness of the proposed system for strabismus diagnosis.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationHealthcare technology letters, 2018, v. 5, no. 1, p. 1-6-
dcterms.isPartOfHealthcare technology letters-
dcterms.issued2018-
dc.identifier.isiWOS:000426532800001-
dc.identifier.scopus2-s2.0-85042913025-
dc.identifier.eissn2053-3713-
dc.identifier.rosgroupid2017001915-
dc.description.ros2017-2018 > Academic research: refereed > Publication in refereed journal-
dc.description.validate201808 bcrc-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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