利用虚拟现实技术的眼动追踪特征估计情感状态的变化

M. Pszeida, Amir Dini, M. Schneeberger, M. Lenger, L. Paletta, S. Russegger, S. Reidl, S. Beranek, B. ., Msc ., Sandra Schuessler, A. Haeussl, B. ., R. Hartmann, Martin Sighart, Sebastian Mayer, Patricia Papic, Beatrix Koch, Hermine Fürli
{"title":"利用虚拟现实技术的眼动追踪特征估计情感状态的变化","authors":"M. Pszeida, Amir Dini, M. Schneeberger, M. Lenger, L. Paletta, S. Russegger, S. Reidl, S. Beranek, B. ., Msc ., Sandra Schuessler, A. Haeussl, B. ., R. Hartmann, Martin Sighart, Sebastian Mayer, Patricia Papic, Beatrix Koch, Hermine Fürli","doi":"10.54941/ahfe1001843","DOIUrl":null,"url":null,"abstract":"Affective states play a prominent role in the context of human activation and motivation. Immersive VR-based presence provides opportunities to activate elderly people in the context of preferred leisure activities (Häussl et al., 2021) or to apply mindfulness interventions for their cognitive reserve (Paletta et al., 2021). The appropriate design of positively activating content is pivotal for appropriate changes in users’ affective states. The presented study provided insight into the potential of non-invasive VR-based eye tracking for automated estimation of affective state induced by video content, in an explorative pilot study with seven elderly persons living in a nursing home. The results indicate the feasibility of estimating mood change from typical eye movement features, such as, fixation duration and pupil diameter, as a promising future research topic.","PeriodicalId":285612,"journal":{"name":"Cognitive Computing and Internet of Things","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Estimation of Change in Affective State Using Eye Tracking Features from Virtual Reality Technologies\",\"authors\":\"M. Pszeida, Amir Dini, M. Schneeberger, M. Lenger, L. Paletta, S. Russegger, S. Reidl, S. Beranek, B. ., Msc ., Sandra Schuessler, A. Haeussl, B. ., R. Hartmann, Martin Sighart, Sebastian Mayer, Patricia Papic, Beatrix Koch, Hermine Fürli\",\"doi\":\"10.54941/ahfe1001843\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Affective states play a prominent role in the context of human activation and motivation. Immersive VR-based presence provides opportunities to activate elderly people in the context of preferred leisure activities (Häussl et al., 2021) or to apply mindfulness interventions for their cognitive reserve (Paletta et al., 2021). The appropriate design of positively activating content is pivotal for appropriate changes in users’ affective states. The presented study provided insight into the potential of non-invasive VR-based eye tracking for automated estimation of affective state induced by video content, in an explorative pilot study with seven elderly persons living in a nursing home. The results indicate the feasibility of estimating mood change from typical eye movement features, such as, fixation duration and pupil diameter, as a promising future research topic.\",\"PeriodicalId\":285612,\"journal\":{\"name\":\"Cognitive Computing and Internet of Things\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cognitive Computing and Internet of Things\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.54941/ahfe1001843\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cognitive Computing and Internet of Things","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54941/ahfe1001843","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

情感状态在人的激活和动机中起着重要的作用。基于沉浸式vr的存在为老年人提供了在首选休闲活动的背景下激活老年人的机会(Häussl等人,2021),或者为他们的认知储备应用正念干预(Paletta等人,2021)。积极激活内容的适当设计对于用户情感状态的适当变化至关重要。本研究通过对七名住在养老院的老年人进行探索性试点研究,深入了解了基于vr的无创眼动追踪技术在自动估计视频内容引起的情感状态方面的潜力。结果表明,从典型眼动特征(如注视时间和瞳孔直径)估计情绪变化是可行的,是一个有前景的未来研究课题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimation of Change in Affective State Using Eye Tracking Features from Virtual Reality Technologies
Affective states play a prominent role in the context of human activation and motivation. Immersive VR-based presence provides opportunities to activate elderly people in the context of preferred leisure activities (Häussl et al., 2021) or to apply mindfulness interventions for their cognitive reserve (Paletta et al., 2021). The appropriate design of positively activating content is pivotal for appropriate changes in users’ affective states. The presented study provided insight into the potential of non-invasive VR-based eye tracking for automated estimation of affective state induced by video content, in an explorative pilot study with seven elderly persons living in a nursing home. The results indicate the feasibility of estimating mood change from typical eye movement features, such as, fixation duration and pupil diameter, as a promising future research topic.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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