Detection of High-Risk Depression Groups Based on Eye-Tracking Data

Simeng Lu, Shen Huang, Yun Zhang, Xiujuan Zheng, Danmin Miao, Jiajun Wang, Zheru Chi

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review


Depression is the most common psychiatric disorder in the general population. An effective treatment of depression requires early detection. In reschedule this paper, a novel algorithm is presented based on eye-tracking and a self-rating high-risk depression screening scale (S-hr-DS) for early depression screening. In this algorithm, a subject scan path is encoded by semantic areas of interest (AOIs). AOIs are dynamically generated by the POS (part-of-speech) tagging of Chinese words in the S-hr-DS items. The proposed method considers both temporal and spatial information of the eye-tracking data and encodes the subject scan path with semantic features of items. The support vector machine recursive feature elimination (SVM-RFE) algorithm is employed for feature selection and model training. Experimental results on a data set including 69 subjects show that our proposed algorithm can achieve an accuracy of 81% with 76% in sensitivity and 79% in F1-score, demonstrating a potential application in high-risk depression detection.

Original languageEnglish
Title of host publicationPattern Recognition and Computer Vision - 3rd Chinese Conference, PRCV 2020, Proceedings
EditorsYuxin Peng, Hongbin Zha, Qingshan Liu, Huchuan Lu, Zhenan Sun, Chenglin Liu, Xilin Chen, Jian Yang
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages12
ISBN (Print)9783030606381
Publication statusPublished - Oct 2020
Event3rd Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2020 - Nanjing, China
Duration: 16 Oct 202018 Oct 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12306 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference3rd Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2020


  • Eye-tracking
  • Feature selection
  • High-risk depression groups
  • Word-fixation driven feature coding

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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