Multimodal frustration detection on smartphones

Esther Vasiete; Tom Yeh

doi:10.1145/2702613.2732867

Multimodal frustration detection on smartphones

Esther Vasiete, Tom Yeh

Department of Psychology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Detecting user's frustration on a smartphone could have a significant impact on applications such as intelligent tutoring systems or app testing systems. Our goal is to provide a multimodal frustration detection system using data exclusively retrieved from a smartphone; motion sensor readings, touch gestures and face videos recorded from the smartphone's front camera. Copyright is held by the author/owner(s).

Original language	English
Title of host publication	CHI 2015 - Extended Abstracts Publication of the 33rd Annual CHI Conference on Human Factors in Computing Systems
Subtitle of host publication	Crossings
Publisher	Association for Computing Machinery
Pages	1307-1312
Number of pages	6
ISBN (Electronic)	9781450331463
DOIs	https://doi.org/10.1145/2702613.2732867
State	Published - 18 Apr 2015
Event	33rd Annual CHI Conference on Human Factors in Computing Systems, CHI EA 2015 - Seoul, Korea, Republic of Duration: 18 Apr 2015 → 23 Apr 2015

Publication series

Name	Conference on Human Factors in Computing Systems - Proceedings
Volume	18

Conference

Conference	33rd Annual CHI Conference on Human Factors in Computing Systems, CHI EA 2015
Country/Territory	Korea, Republic of
City	Seoul
Period	18/04/15 → 23/04/15

Bibliographical note

Funding Information:
This work was supported by a DARPA grant FA8750-13-2-0279.

Keywords

Frustration detection
Multimodal system
Multitask game

Access to Document

10.1145/2702613.2732867

Cite this

Vasiete, E., & Yeh, T. (2015). Multimodal frustration detection on smartphones. In CHI 2015 - Extended Abstracts Publication of the 33rd Annual CHI Conference on Human Factors in Computing Systems: Crossings (pp. 1307-1312). (Conference on Human Factors in Computing Systems - Proceedings; Vol. 18). Association for Computing Machinery. https://doi.org/10.1145/2702613.2732867

@inproceedings{28ce8e7e31444c65ac52e2e34293fb77,

title = "Multimodal frustration detection on smartphones",

abstract = "Detecting user's frustration on a smartphone could have a significant impact on applications such as intelligent tutoring systems or app testing systems. Our goal is to provide a multimodal frustration detection system using data exclusively retrieved from a smartphone; motion sensor readings, touch gestures and face videos recorded from the smartphone's front camera. Copyright is held by the author/owner(s).",

keywords = "Frustration detection, Multimodal system, Multitask game",

author = "Esther Vasiete and Tom Yeh",

note = "Funding Information: This work was supported by a DARPA grant FA8750-13-2-0279.; 33rd Annual CHI Conference on Human Factors in Computing Systems, CHI EA 2015 ; Conference date: 18-04-2015 Through 23-04-2015",

year = "2015",

month = apr,

day = "18",

doi = "10.1145/2702613.2732867",

language = "English",

series = "Conference on Human Factors in Computing Systems - Proceedings",

publisher = "Association for Computing Machinery",

pages = "1307--1312",

booktitle = "CHI 2015 - Extended Abstracts Publication of the 33rd Annual CHI Conference on Human Factors in Computing Systems",

}

Vasiete, E & Yeh, T 2015, Multimodal frustration detection on smartphones. in CHI 2015 - Extended Abstracts Publication of the 33rd Annual CHI Conference on Human Factors in Computing Systems: Crossings. Conference on Human Factors in Computing Systems - Proceedings, vol. 18, Association for Computing Machinery, pp. 1307-1312, 33rd Annual CHI Conference on Human Factors in Computing Systems, CHI EA 2015, Seoul, Korea, Republic of, 18/04/15. https://doi.org/10.1145/2702613.2732867

Multimodal frustration detection on smartphones. / Vasiete, Esther; Yeh, Tom.
CHI 2015 - Extended Abstracts Publication of the 33rd Annual CHI Conference on Human Factors in Computing Systems: Crossings. Association for Computing Machinery, 2015. p. 1307-1312 (Conference on Human Factors in Computing Systems - Proceedings; Vol. 18).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Detecting user's frustration on a smartphone could have a significant impact on applications such as intelligent tutoring systems or app testing systems. Our goal is to provide a multimodal frustration detection system using data exclusively retrieved from a smartphone; motion sensor readings, touch gestures and face videos recorded from the smartphone's front camera. Copyright is held by the author/owner(s).

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KW - Multimodal system

KW - Multitask game

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Multimodal frustration detection on smartphones

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

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Cite this