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It's not complicated: a study of non-specialists analyzing GSR sensor data to detect UX related events

Author:

Anders BruunAuthors Info & Claims

NordiCHI '18: Proceedings of the 10th Nordic Conference on Human-Computer Interaction

Pages 170 - 183

https://doi.org/10.1145/3240167.3240183

Published: 29 September 2018 Publication History

Abstract

Emotion is a key factor in understanding user experiences (UX) of interactive systems. An emerging trend within HCI is to apply physiological sensors for uncovering emotions. Previous studies rely on various sophisticated analysis techniques and specialized knowledge to interpret sensor data. While commendable for increasing accuracy at fine grained latencies (to detect events within seconds), this can be challenging for UX practitioners without specialized knowledge. This study contributes in two ways. Firstly by understanding the level of sensor accuracy in detecting UX related events. Secondly by applying a basic analysis approach where sensor data is interpreted by 21 non-specialist participants (no previous experience in doing this). Their performance is compared to random guessing. Findings show that sensor data analyzed by non-specialists are significantly more accurate in capturing subjectively reported UX events than random guessing. An accuracy level of 60-80% was obtained at granularities within 3.5-11 seconds of UX related events.

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Cited By

da Silveira ALima de Souza MGhinea GSaibel Santos C(2024)Physiological Data for User Experience and Quality of Experience: A Systematic Review (2018–2022)International Journal of Human–Computer Interaction10.1080/10447318.2024.2311972(1-30)Online publication date: 13-Feb-2024
https://doi.org/10.1080/10447318.2024.2311972
Borawska AMateja A(2024)Unveiling the User Experience: A Synthesis of Cognitive Neuroscience Methods in Digital Product DesignAdvances in Information Systems Development10.1007/978-3-031-57189-3_10(199-218)Online publication date: 18-Jul-2024
https://doi.org/10.1007/978-3-031-57189-3_10
Sahar YWagner MBarel AShoval S(2022)Stress-Adaptive Training: An Adaptive Psychomotor Training According to Stress Measured by Grip ForceSensors10.3390/s2221836822:21(8368)Online publication date: 1-Nov-2022
https://doi.org/10.3390/s22218368
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cover image ACM Other conferences

NordiCHI '18: Proceedings of the 10th Nordic Conference on Human-Computer Interaction

September 2018

1002 pages

ISBN:9781450364379

DOI:10.1145/3240167

General Chairs:
Tone Bratteteig
University of Oslo
,
Frode Eika Sandnes
Oslo Metropolitan University
,
Publications Chair:
Gerd Berget
Oslo Metropolitan University

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 29 September 2018

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NordiCHI'18: Nordic Conference on Human-Computer Interaction

September 29 - October 3, 2018

Oslo, Norway

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NordiCHI '18 Paper Acceptance Rate 59 of 240 submissions, 25%;

Overall Acceptance Rate 379 of 1,572 submissions, 24%

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Cited By

da Silveira ALima de Souza MGhinea GSaibel Santos C(2024)Physiological Data for User Experience and Quality of Experience: A Systematic Review (2018–2022)International Journal of Human–Computer Interaction10.1080/10447318.2024.2311972(1-30)Online publication date: 13-Feb-2024
https://doi.org/10.1080/10447318.2024.2311972
Borawska AMateja A(2024)Unveiling the User Experience: A Synthesis of Cognitive Neuroscience Methods in Digital Product DesignAdvances in Information Systems Development10.1007/978-3-031-57189-3_10(199-218)Online publication date: 18-Jul-2024
https://doi.org/10.1007/978-3-031-57189-3_10
Sahar YWagner MBarel AShoval S(2022)Stress-Adaptive Training: An Adaptive Psychomotor Training According to Stress Measured by Grip ForceSensors10.3390/s2221836822:21(8368)Online publication date: 1-Nov-2022
https://doi.org/10.3390/s22218368
Sahar YElbaum TWagner MMusicant OHirsh TShoval S(2021)Grip Force on Steering Wheel as a Measure of StressFrontiers in Psychology10.3389/fpsyg.2021.61788912Online publication date: 7-Jun-2021
https://doi.org/10.3389/fpsyg.2021.617889
Bruun ALaw ENielsen THeintz M(2021)Do You Feel the Same? On the Robustness of Cued-Recall Debriefing for User Experience EvaluationACM Transactions on Computer-Human Interaction10.1145/345347928:4(1-45)Online publication date: 23-Jul-2021
https://dl.acm.org/doi/10.1145/3453479
Liapis AFaliagka EKatsanos CAntonopoulos CVoros N(2021)Detection of Subtle Stress Episodes During UX Evaluation: Assessing the Performance of the WESAD Bio-Signals DatasetHuman-Computer Interaction – INTERACT 202110.1007/978-3-030-85613-7_17(238-247)Online publication date: 30-Aug-2021
https://dl.acm.org/doi/10.1007/978-3-030-85613-7_17
Elsborg MBruun AJensen R(2020)Supporting Anxiety Patients’ Self-Reflection through Visualization of Physiological Data.Proceedings of the 32nd Australian Conference on Human-Computer Interaction10.1145/3441000.3441037(742-747)Online publication date: 2-Dec-2020
https://dl.acm.org/doi/10.1145/3441000.3441037
Liapis AKatsanos CKarousos NXenos MOrphanoudakis T(2020)User Experience Evaluation: A Validation Study of a Tool-based Approach for Automatic Stress Detection Using Physiological SignalsInternational Journal of Human–Computer Interaction10.1080/10447318.2020.182520537:5(470-483)Online publication date: 4-Oct-2020
https://doi.org/10.1080/10447318.2020.1825205

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