Eye-tracking-aided digital system for strabismus diagnosis

Zeng Hai Chen, Hong Fu, Wai Lun Lo, Zheru Chi, Bingang Xu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

13 Citations (Scopus)

Abstract

Strabismus 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.
Original languageEnglish
Pages (from-to)1-6
Number of pages6
JournalHealthcare Technology Letters
Volume5
Issue number1
DOIs
Publication statusPublished - 1 Jan 2018

ASJC Scopus subject areas

  • Health Informatics
  • Health Information Management

Cite this