Please use this identifier to cite or link to this item:
10.16910/JEMR.16.2.6
Title: | Depression detection using virtual avatar communication and eye tracking |
Authors: | Takemoto, Ayumi Aispuriete, Inese Niedra, Laima Dreimane, Lana Franceska Rīga Stradiņš University |
Keywords: | Depression detection;Eye tracking;Human-computer interaction;Saccades;Virtual avatar communication;3.2 Clinical medicine;3.1 Basic medicine;1.1. Scientific article indexed in Web of Science and/or Scopus database;Ophthalmology;Sensory Systems;SDG 3 - Good Health and Well-being |
Issue Date: | 2023 |
Citation: | Takemoto , A , Aispuriete , I , Niedra , L & Dreimane , L F 2023 , ' Depression detection using virtual avatar communication and eye tracking ' , Journal of Eye Movement Research , vol. 16 , no. 2 , 6 . https://doi.org/10.16910/JEMR.16.2.6 |
Abstract: | Globally, depression is one of the most common mental health issues. Therefore, finding an effective way to detect mental health problems is an important subject for study in human-machine interactions. In order to examine the potential in using a virtual avatar communication and eye tracking system to identify people as being with or without depression symptoms, this study has devised three research aims; 1) to understand the effect of different types of interviewers on eye gaze patterns, 2) to clarify the effect of neutral conversation topics on eye gaze, and 3) to compare eye gaze patterns between people with or without depression. Twenty-seven participants - fifteen in the control group and twelve in the depression symptoms group -were involved in this study and they were asked to talk to both a virtual avatar and human interviewers. Gaze patterns were recorded by an eye tracking device during both types of interaction. The experiment results indicated significant differences in eye movements between the control group and depression symptoms group. Moreover, larger gaze distribution was observed when people with depression symptoms were discussing neutral conversation topics rather than those without depression. |
Description: | Publisher Copyright: © 2023 This article is licensed under a Creative Commons Attribution 4.0 International license. (oc) BY |
DOI: | 10.16910/JEMR.16.2.6 |
ISSN: | 1995-8692 |
Appears in Collections: | Research outputs from Pure / Zinātniskās darbības rezultāti no ZDIS Pure |
Files in This Item:
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Depression_detection_using_virtual_avatar_communication_and_eye_tracking.pdf | 1.08 MB | Adobe PDF | View/Open |
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