Estimating Attention Allocation by Electrodermal Activity
Pages 87 - 91
Abstract
Electrodermal activity (EDA) represents changes in the electrical activity of the palmar skin and serves as an indicator of sympathetic nervous system activity. This paper presents a novel method for estimating attention allocation under divided attention conditions using only EDA data. Our approach involves the use of the low-frequency power spectrum derived from the phasic component of EDA associated with attentional focus, combined with a machine learning classification model. We conducted three user studies aimed at estimating participants’ attention allocation during the performance of simple tasks under both visual and auditory stimuli where the frequencies of the stimuli were different, identical, or ambiguous. The goal was to estimate whether participants focused on visual or auditory stimuli. The results showed that our method could estimate attention allocation with the accuracy of 96% and 73% when the frequencies of the two stimuli were different and ambiguous, respectively, and could not estimate when the frequencies were identical.
References
[1]
James A Arnett and Seth S Labovitz. 1995. Effect of physical layout in performance of the Trail Making Test.Psychological Assessment 7, 2 (1995), 220. https://doi.org/10.1037/1040-3590.7.2.220
[2]
Ebrahim Babaei, Benjamin Tag, Tilman Dingler, and Eduardo Velloso. 2021. A Critique of Electrodermal Activity Practices at CHI. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 1–14. https://doi.org/10.1145/3411764.3445370
[3]
Stefania Cecchi, Agnese Piersanti, Angelica Poli, and Susanna Spinsante. 2020. Physical stimuli and emotions: EDA features analysis from a wrist-worn measurement sensor. In 2020 IEEE 25th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD). IEEE, 1–6. https://doi.org/10.1109/CAMAD50429.2020.9209307
[4]
Lan-lan Chen, Ao Zhang, and Xiao-guang Lou. 2019. Cross-subject driver status detection from physiological signals based on hybrid feature selection and transfer learning. Expert Systems with Applications 137 (2019), 266–280. https://doi.org/10.1016/j.eswa.2019.02.005
[5]
Francesco Chiossi, Yagiz Turgut, Robin Welsch, and Sven Mayer. 2023. Adapting Visual Complexity Based on Electrodermal Activity Improves Working Memory Performance in Virtual Reality. Proc. ACM Hum.-Comput. Interact 7 (2023). https://doi.org/10.1145/3604243
[6]
Francesco Chiossi, Robin Welsch, Steeven Villa, Lewis Chuang, and Sven Mayer. 2022. Virtual reality adaptation using electrodermal activity to support the user experience. Big Data and Cognitive Computing 6, 2 (2022), 55. https://doi.org/10.3390/bdcc6020055
[7]
Marvin M Chun, Julie D Golomb, and Nicholas B Turk-Browne. 2011. A taxonomy of external and internal attention. Annual review of psychology 62 (2011), 73–101. https://doi.org/10.1146/annurev.psych.093008.100427
[8]
Natalia B Fernandez, Wiebke J Trost, and Patrik Vuilleumier. 2019. Brain networks mediating the influence of background music on selective attention. Social cognitive and affective neuroscience 14, 12 (2019), 1441–1452. https://doi.org/10.1093/scan/nsaa004
[9]
Society for Psychophysiological Research Ad Hoc Committee on Electrodermal Measures, Wolfram Boucsein, Don C Fowles, Sverre Grimnes, Gershon Ben-Shakhar, Walton T Roth, Michael E Dawson, and Diane L Filion. 2012. Publication recommendations for electrodermal measurements. Psychophysiology 49, 8 (2012), 1017–1034. https://doi.org/10.1111/j.1469-8986.2012.01384.x
[10]
Pascal E Fortin, Elisabeth Sulmont, and Jeremy Cooperstock. 2019. Detecting perception of smartphone notifications using skin conductance responses. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. 1–9. https://doi.org/10.1145/3290605.3300420
[11]
Timothy Greer, Benjamin Ma, Matthew Sachs, Assal Habibi, and Shrikanth Narayanan. 2019. A multimodal view into music’s effect on human neural, physiological, and emotional experience. In Proceedings of the 27th ACM International Conference on Multimedia. 167–175. https://doi.org/10.1145/3343031.3350867
[12]
Sogand Hasanzadeh, Behzad Esmaeili, and Michael D Dodd. 2017. Measuring the impacts of safety knowledge on construction workers’ attentional allocation and hazard detection using remote eye-tracking technology. Journal of management in engineering 33, 5 (2017), 04017024. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000526
[13]
Mahmoud Hashash, Maya Abou Zeid, and Nadine Marie Moacdieh. 2019. Social media browsing while driving: Effects on driver performance and attention allocation. Transportation research part F: traffic psychology and behaviour 63 (2019), 67–82. https://doi.org/10.1016/j.trf.2019.03.021
[14]
Luca Kiss and Karina J Linnell. 2021. The effect of preferred background music on task-focus in sustained attention. Psychological research 85, 6 (2021), 2313–2325. https://doi.org/10.1007/s00426-020-01400-6
[15]
Simon Ladouce, David I Donaldson, Paul A Dudchenko, and Magdalena Ietswaart. 2019. Mobile EEG identifies the re-allocation of attention during real-world activity. Scientific reports 9, 1 (2019), 1–10. https://doi.org/10.1038/s41598-019-51996-y
[16]
Liat Liberman and Ilana Dubovi. 2023. The effect of the modality principle to support learning with virtual reality: An eye-tracking and electrodermal activity study. Journal of Computer Assisted Learning 39, 2 (2023), 547–557. https://doi.org/10.1111/jcal.12763
[17]
Russell A Lockhart. 1972. Interrelations between amplitude, latency, rise time, and the Edelberg recovery measure of the galvanic skin response. Psychophysiology 9, 4 (1972), 437–442. https://doi.org/10.1111/j.1469-8986.1972.tb01791.x
[18]
Nobuo Masataka and Leonid Perlovsky. 2013. Cognitive interference can be mitigated by consonant music and facilitated by dissonant music. Scientific Reports 3, 1 (2013), 1–6. https://doi.org/10.1038/srep02028
[19]
Éva Nadon, Barbara Tillmann, Arnaud Saj, and Nathalie Gosselin. 2021. The emotional effect of background music on selective attention of adults. Frontiers in Psychology (2021), 4472. https://doi.org/10.3389/fpsyg.2021.729037
[20]
Matthew KXJ Pan, Jih-Shiang Chang, Gokhan H Himmetoglu, AJung Moon, Thomas W Hazelton, Karon E MacLean, and Elizabeth A Croft. 2011. Now where was I? Physiologically-triggered bookmarking. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. 363–372. https://doi.org/10.1145/1978942.1978995
[21]
Thomas D Parsons and Christopher G Courtney. 2016. Interactions between threat and executive control in a virtual reality stroop task. IEEE Transactions on Affective Computing 9, 1 (2016), 66–75. https://doi.org/10.1109/TAFFC.2016.2569086
[22]
Hugo F Posada-Quintero and Ki H Chon. 2016. Frequency-domain electrodermal activity index of sympathetic function. In 2016 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI). IEEE, 497–500. https://doi.org/10.1109/BHI.2016.7455943
[23]
Tsugunosuke Sakai, Haruya Tamaki, Yosuke Ota, Ryohei Egusa, Shigenori Inagaki, Fusako Kusunoki, Masanori Sugimoto, Hiroshi Mizoguchi, 2017. EDA-based estimation of visual attention by observation of eye blink frequency. International Journal on Smart Sensing and Intelligent Systems 10, 2 (2017), 296–307. https://doi.org/10.21307/ijssis-2017-212
[24]
G Turpin, T Grandfield, and G Fink. 2009. Electrodermal activity. Stress Science: Neuroendocrinology (2009), 313–316.
[25]
Theresa F Wechsler, Michael Pfaller, Rahel E van Eickels, Luise H Schulz, and Andreas Mühlberger. 2021. Look at the audience? a randomized controlled study of shifting attention from self-focus to nonsocial vs. social external stimuli during virtual reality exposure to public speaking in social anxiety. Frontiers in psychiatry 12 (2021), 751272. https://doi.org/10.3389/fpsyt.2021.751272
[26]
Jinn-Tsai Wong and Shih-Hsuan Huang. 2013. Attention allocation patterns in naturalistic driving. Accident Analysis & Prevention 58 (2013), 140–147. https://doi.org/10.1016/j.aap.2013.04.033
Index Terms
- Estimating Attention Allocation by Electrodermal Activity
Recommendations
Towards long term monitoring of electrodermal activity in daily life
Manic depression, also known as bipolar disorder, is a common and severe form of mental disorder. The European research project MONARCA aims at developing and validating mobile technologies for multi-parametric, long term monitoring of physiological and ...
The complexity of electrodermal activity is altered in mental cognitive stressors
The aim of this study was to evaluate potential changes in the electrodermal activity (EDA) to enable the detection of variations in the sympathetic nervous system during mental load and recovery period. Several EDA parameters were used: SCA (skin ...
A More Complete Picture of Emotion Using Electrocardiogram and Electrodermal Activity to Complement Cognitive Data
Proceedings, Part I, 10th International Conference on Foundations of Augmented Cognition: Neuroergonomics and Operational Neuroscience - Volume 9743We describe a method of achieving emotion classification using ECG and EDA data. There have been many studies conducted on usage of heart rate and EDA data to quantify the arousal level of a user [1---3]. Researchers have identified a connection between ...
Comments
Information & Contributors
Information
Published In
October 2023
145 pages
ISBN:9798400701993
DOI:10.1145/3594738
Copyright © 2023 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].
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 08 October 2023
Check for updates
Author Tags
Qualifiers
- Short-paper
- Research
- Refereed limited
Conference
UbiComp/ISWC '23
Sponsor:
UbiComp/ISWC '23: The 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing
October 8 - 12, 2023
Cancun, Quintana Roo, Mexico
Acceptance Rates
Overall Acceptance Rate 38 of 196 submissions, 19%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 173Total Downloads
- Downloads (Last 12 months)85
- Downloads (Last 6 weeks)14
Reflects downloads up to 05 Mar 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format