From the lab to the real-world: An investigation on the influence of human movement on Emotion Recognition using physiological signals

Yaqian Xu, I. Hübener, Ann-Kathrin Seipp, Sandra Ohly, K. David
{"title":"From the lab to the real-world: An investigation on the influence of human movement on Emotion Recognition using physiological signals","authors":"Yaqian Xu, I. Hübener, Ann-Kathrin Seipp, Sandra Ohly, K. David","doi":"10.1109/PERCOMW.2017.7917586","DOIUrl":null,"url":null,"abstract":"The recognition of human emotions using physiological signals such as Electrodermal Activity (EDA), Electrocardiogram (ECG) or Electromyography (EMG), has been extensively researched in the past attracting a lot of interest during the last few decades. Although showing a relatively satisfactory performance under lab conditions, Emotion Recognition (ER) systems using physiological signals are not widely used in real-world scenarios. One important fact is that, in the real world, physiological signals may be influenced by human movement and therefore, they cannot be used as a unique indicative of emotions. In this paper, we investigate the influence of human movement on ER using physiological signals. We compare different measures of emotion before and after a test person has performed some physical activity (e.g. walking, going upstairs). We discuss the main differences between recognizing emotions in the lab and the real world and provide new insights into the development of ER systems in real-world scenarios.","PeriodicalId":319638,"journal":{"name":"2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PERCOMW.2017.7917586","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 21

Abstract

The recognition of human emotions using physiological signals such as Electrodermal Activity (EDA), Electrocardiogram (ECG) or Electromyography (EMG), has been extensively researched in the past attracting a lot of interest during the last few decades. Although showing a relatively satisfactory performance under lab conditions, Emotion Recognition (ER) systems using physiological signals are not widely used in real-world scenarios. One important fact is that, in the real world, physiological signals may be influenced by human movement and therefore, they cannot be used as a unique indicative of emotions. In this paper, we investigate the influence of human movement on ER using physiological signals. We compare different measures of emotion before and after a test person has performed some physical activity (e.g. walking, going upstairs). We discuss the main differences between recognizing emotions in the lab and the real world and provide new insights into the development of ER systems in real-world scenarios.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
从实验室到现实世界:利用生理信号研究人体运动对情绪识别的影响
利用皮肤电活动(EDA)、心电图(ECG)或肌电图(EMG)等生理信号识别人类情绪,在过去的几十年里得到了广泛的研究,引起了人们的极大兴趣。尽管在实验室条件下表现出相对令人满意的性能,但使用生理信号的情绪识别(ER)系统在现实世界中的应用并不广泛。一个重要的事实是,在现实世界中,生理信号可能会受到人体运动的影响,因此,它们不能作为情感的唯一指示。在本文中,我们利用生理信号来研究人体运动对内质网的影响。我们比较了测试者在进行一些体力活动(如散步、上楼)之前和之后的不同情绪测量。我们讨论了在实验室和现实世界中识别情绪的主要区别,并为现实场景中急诊室系统的开发提供了新的见解。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Sensitivity to web hosting in a mobile field survey NFC based dataset annotation within a behavioral alerting platform An aggregation and visualization technique for crowd-sourced continuous monitoring of transport infrastructures Trainwear: A real-time assisted training feedback system with fabric wearable sensors Toward real-time in-home activity recognition using indoor positioning sensor and power meters
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1