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Towards Enhancing Emotional Responses to Media using Auto-Calibrating Electric Muscle Stimulation (EMS)

Authors:

Takashi Goto,

Benjamin Tag,

Kai Kunze,

Tilman DinglerAuthors Info & Claims

AH '18: Proceedings of the 9th Augmented Human International Conference

Article No.: 29, Pages 1 - 2

https://doi.org/10.1145/3174910.3174939

Published: 06 February 2018 Publication History

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Abstract

We evaluate the use of Electric Muscle Stimulation (EMS) as a method of amplifying emotional responses to multimedia content. This paper presents an auto-calibration method to stimulate two facial expressions using EMS. We focus on two expressions: frown and smile. We attempted control of facial muscles with facial feedback for automatically calibrating these facial expressions: our computer vision system detects the facial expression and auto-calibrates the EMS parameters (intensity and duration) based on the user's current facial expression. We present results from a pilot study with four participants evaluating the auto-calibration system and collecting initial feedback on the use of EMS to augment, for example, media experiences: while watching movies we can enhance the emotional response of the users during happy and sad scenes by stimulating corresponding face muscles.

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Cited By

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Cheng CChen YHandani SBalabantaray AChen M(2024)Paired-EMS: Enhancing Electrical Muscle Stimulation (EMS)-based Force Feedback Experience by Stimulating Both Muscles in Antagonistic PairsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642841(1-7)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642841
Jiang WWindl MTag BSarsenbayeva ZMayer S(2024)An Immersive and Interactive VR Dataset to Elicit EmotionsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2024.345620230:11(7343-7353)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1109/TVCG.2024.3456202
Efthimiou THernandez MElsenaar AMehu MKorb S(2023)Application of facial neuromuscular electrical stimulation (fNMES) in psychophysiological research: Practical recommendations based on a systematic review of the literatureBehavior Research Methods10.3758/s13428-023-02262-756:4(2941-2976)Online publication date: 20-Oct-2023
https://doi.org/10.3758/s13428-023-02262-7
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Index Terms

Towards Enhancing Emotional Responses to Media using Auto-Calibrating Electric Muscle Stimulation (EMS)
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interactive systems and tools

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Published In

AH '18: Proceedings of the 9th Augmented Human International Conference

February 2018

229 pages

ISBN:9781450354158

DOI:10.1145/3174910

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 February 2018

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Poster
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JST(CRESTO, Presto)

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AH2018

AH2018: The 9th Augmented Human International Conference

February 7 - 9, 2018

Seoul, Republic of Korea

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Overall Acceptance Rate 121 of 306 submissions, 40%

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Cheng CChen YHandani SBalabantaray AChen M(2024)Paired-EMS: Enhancing Electrical Muscle Stimulation (EMS)-based Force Feedback Experience by Stimulating Both Muscles in Antagonistic PairsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642841(1-7)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642841
Jiang WWindl MTag BSarsenbayeva ZMayer S(2024)An Immersive and Interactive VR Dataset to Elicit EmotionsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2024.345620230:11(7343-7353)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1109/TVCG.2024.3456202
Efthimiou THernandez MElsenaar AMehu MKorb S(2023)Application of facial neuromuscular electrical stimulation (fNMES) in psychophysiological research: Practical recommendations based on a systematic review of the literatureBehavior Research Methods10.3758/s13428-023-02262-756:4(2941-2976)Online publication date: 20-Oct-2023
https://doi.org/10.3758/s13428-023-02262-7
Baker JEfthimiou TScherer RGartus AElsenaar AMehu MKorb S(2023)Measurement of the N170 during facial neuromuscular electrical stimulation (fNMES)Journal of Neuroscience Methods10.1016/j.jneumeth.2023.109877393(109877)Online publication date: Jun-2023
https://doi.org/10.1016/j.jneumeth.2023.109877
Faltaous SKoelle MSchneegass S(2022)From Perception to Action: A Review and Taxonomy on Electrical Muscle Stimulation in HCIProceedings of the 21st International Conference on Mobile and Ubiquitous Multimedia10.1145/3568444.3568460(159-171)Online publication date: 27-Nov-2022
https://dl.acm.org/doi/10.1145/3568444.3568460
Yoshida SNarumi TTanikawa TKuzuoka HHirose MKitamura YQuigley AIsbister KIgarashi TBjørn PDrucker S(2021)Teardrop Glasses: Pseudo Tears Induce Sadness in You and Those Around YouProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3445741(1-12)Online publication date: 6-May-2021
https://dl.acm.org/doi/10.1145/3411764.3445741
Khamis MSchuster NGeorge CPfeiffer M(2019)ElectroCutscenes: Realistic Haptic Feedback in Cutscenes of Virtual Reality Games Using Electric Muscle StimulationProceedings of the 25th ACM Symposium on Virtual Reality Software and Technology10.1145/3359996.3364250(1-10)Online publication date: 12-Nov-2019
https://dl.acm.org/doi/10.1145/3359996.3364250

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Psychological responses to simulated displays of mismatched emotional expressions

Real-time classification of evoked emotions using facial feature tracking and physiological responses

Affective agents for enhancing emotional experience

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