VRNavigSS: A Two-dimensionality Virtual Reality System for Depression Level Detection

IF 2 3区 计算机科学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Ji Zheng, D. Ding, Yuang Zhang, Zidu Cheng, Zhuying Li
{"title":"VRNavigSS: A Two-dimensionality Virtual Reality System for Depression Level Detection","authors":"Ji Zheng, D. Ding, Yuang Zhang, Zidu Cheng, Zhuying Li","doi":"10.1109/CSCWD57460.2023.10152830","DOIUrl":null,"url":null,"abstract":"Depression is a severe mental illness that can lead to negative moods and activities. The traditional clinical approach for diagnosing depression is face-to-face consultation, which is limited by time and space. Virtual Reality (VR), as a novel technology with higher accessibility and lower cost, can serve as an effective digital approach to diagnosing psychological disorders. In VR systems, users are exposed to various experimental scenarios, gaining immersive and interactive experiences. Recent research has demonstrated a relationship between depression and low spatial memory navigation ability (SMNA). Based on these considerations, we propose a VR system to detect one’s depression level by measuring spatial memory navigation performances. The system consists of three virtual scenarios with different spatial scales and dimensions. To study the system’s effectiveness, a pilot study with eight participants was conducted. The results showed differences in the participants’ spatial memory navigation performances in the three scenarios and a correlation between depression level and their spatial memory navigation performances.","PeriodicalId":51008,"journal":{"name":"Computer Supported Cooperative Work-The Journal of Collaborative Computing","volume":"1 1","pages":"820-824"},"PeriodicalIF":2.0000,"publicationDate":"2023-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Supported Cooperative Work-The Journal of Collaborative Computing","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1109/CSCWD57460.2023.10152830","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

Abstract

Depression is a severe mental illness that can lead to negative moods and activities. The traditional clinical approach for diagnosing depression is face-to-face consultation, which is limited by time and space. Virtual Reality (VR), as a novel technology with higher accessibility and lower cost, can serve as an effective digital approach to diagnosing psychological disorders. In VR systems, users are exposed to various experimental scenarios, gaining immersive and interactive experiences. Recent research has demonstrated a relationship between depression and low spatial memory navigation ability (SMNA). Based on these considerations, we propose a VR system to detect one’s depression level by measuring spatial memory navigation performances. The system consists of three virtual scenarios with different spatial scales and dimensions. To study the system’s effectiveness, a pilot study with eight participants was conducted. The results showed differences in the participants’ spatial memory navigation performances in the three scenarios and a correlation between depression level and their spatial memory navigation performances.
VRNavigSS:一种用于抑郁水平检测的二维虚拟现实系统
抑郁症是一种严重的精神疾病,会导致消极的情绪和行为。传统的临床诊断抑郁症的方法是面对面的咨询,受时间和空间的限制。虚拟现实技术作为一种可及性高、成本低的新技术,可以作为一种有效的心理障碍诊断的数字化手段。在VR系统中,用户可以接触到各种各样的实验场景,获得身临其境的互动体验。最近的研究已经证明了抑郁与低空间记忆导航能力(SMNA)之间的关系。基于这些考虑,我们提出了一个VR系统,通过测量空间记忆导航性能来检测一个人的抑郁程度。该系统由三个不同空间尺度和维度的虚拟场景组成。为了研究该系统的有效性,我们进行了一项有8名参与者的试点研究。结果表明,三种情境下被试空间记忆导航表现存在差异,抑郁程度与空间记忆导航表现存在相关性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Computer Supported Cooperative Work-The Journal of Collaborative Computing
Computer Supported Cooperative Work-The Journal of Collaborative Computing COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
6.40
自引率
4.20%
发文量
31
审稿时长
>12 weeks
期刊介绍: Computer Supported Cooperative Work (CSCW): The Journal of Collaborative Computing and Work Practices is devoted to innovative research in computer-supported cooperative work (CSCW). It provides an interdisciplinary and international forum for the debate and exchange of ideas concerning theoretical, practical, technical, and social issues in CSCW. The CSCW Journal arose in response to the growing interest in the design, implementation and use of technical systems (including computing, information, and communications technologies) which support people working cooperatively, and its scope remains to encompass the multifarious aspects of research within CSCW and related areas. The CSCW Journal focuses on research oriented towards the development of collaborative computing technologies on the basis of studies of actual cooperative work practices (where ‘work’ is used in the wider sense). That is, it welcomes in particular submissions that (a) report on findings from ethnographic or similar kinds of in-depth fieldwork of work practices with a view to their technological implications, (b) report on empirical evaluations of the use of extant or novel technical solutions under real-world conditions, and/or (c) develop technical or conceptual frameworks for practice-oriented computing research based on previous fieldwork and evaluations.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信