Depression detection using virtual avatar communication and eye tracking

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dc.contributor.authorTakemoto, Ayumi
dc.contributor.authorAispuriete, Inese
dc.contributor.authorNiedra, Laima
dc.contributor.authorDreimane, Lana Franceska
dc.contributor.institutionRīga Stradiņš University
dc.date.accessioned2024-02-29T07:55:01Z
dc.date.available2024-02-29T07:55:01Z
dc.date.issued2023
dc.descriptionPublisher Copyright: © 2023 This article is licensed under a Creative Commons Attribution 4.0 International license. (oc) BY
dc.description.abstractGlobally, 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.en
dc.description.statusPeer reviewed
dc.format.extent1105420
dc.identifier.citationTakemoto, 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
dc.identifier.doi10.16910/JEMR.16.2.6
dc.identifier.issn1995-8692
dc.identifier.urihttps://dspace.rsu.lv/jspui/handle/123456789/15346
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85173227284&partnerID=8YFLogxK
dc.language.isoeng
dc.relation.ispartofJournal of Eye Movement Research
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectDepression detection
dc.subjectEye tracking
dc.subjectHuman-computer interaction
dc.subjectSaccades
dc.subjectVirtual avatar communication
dc.subject3.2 Clinical medicine
dc.subject3.1 Basic medicine
dc.subject1.1. Scientific article indexed in Web of Science and/or Scopus database
dc.subjectOphthalmology
dc.subjectSensory Systems
dc.subjectSDG 3 - Good Health and Well-being
dc.titleDepression detection using virtual avatar communication and eye trackingen
dc.type/dk/atira/pure/researchoutput/researchoutputtypes/contributiontojournal/article

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