E4UnityIntegration-MIT: An Open-Source Unity Plug-in for Collecting Physiological Data using Empatica E4 during Gameplay
Article No.: 49, Pages 1 - 3
Abstract
Physiological measurement of player experience (PX) during gameplay has been of increasing interest within game research circles. A commonly-used non-invasive wearable device for physiological measurement is the Empatica E4 wristband, which offers multiple physiological metrics, ranging from electrodermal activity to heart rate. That said, the E4’s integration with popular game engines such as Unity 3D presents certain challenges due to non-obvious critical bugs in the library and limited documentation applicability within the Unity context. In this paper, we present an open-source Unity plug-in designed to mitigate the challenges associated with integrating the E4 into Unity projects: E4UnityIntegration-MIT. The plug-in exposes the E4’s API for interfacing with Unity C# scripts, thereby enabling realtime data collection and monitoring. E4UnityIntegration-MIT also provides the affordance of saving the E4 data into an external file for data analysis purposes.
References
[1]
Aaron Frederick Bulagang, James Mountstephens, and Jason Teo. 2021. Multiclass emotion prediction using heart rate and virtual reality stimuli. Journal of Big Data 8 (2021), 1–12.
[2]
Arne Herdick. 2020. Native Code expects “didUpdateOnWristStatus” in “EmpaDataDelegate”. https://github.com/empatica/e4link-sample-project-android/issues/2.
[3]
Lennart E Nacke. 2013. An introduction to physiological player metrics for evaluating games. Game Analytics: Maximizing the value of player data (2013), 585–619.
[4]
Helena Polman. 2022. The Impact of Changing Moods Based on Real-Time Biometric Measurements on Player Experience. In Gaming, Simulation and Innovations: Challenges and Opportunities: 52nd International Simulation and Gaming Association Conference, ISAGA 2021, Indore, India, September 6–10, 2021, Revised Selected Papers. Springer, 171–181.
[5]
Elton Sarmanho Siqueira, Marcos Cordeiro Fleury, Marcus Vinicius Lamar, Anders Drachen, Carla Denise Castanho, and Ricardo Pezzuol Jacobi. 2022. An automated approach to estimate player experience in game events from psychophysiological data. Multimedia Tools and Applications (2022), 1–32.
[6]
Caglar Yildirim. 2023. An Android Plugin for E4 Wristband Integration in Unity. https://osf.io/v9whk/?view_only=dc43354770044134a45c0a74c312514f.
Index Terms
- E4UnityIntegration-MIT: An Open-Source Unity Plug-in for Collecting Physiological Data using Empatica E4 during Gameplay
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Published In
October 2023
424 pages
ISBN:9798400700965
DOI:10.1145/3586182
Copyright © 2023 Owner/Author.
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
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Published: 29 October 2023
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UIST '23: The 36th Annual ACM Symposium on User Interface Software and Technology
October 29 - November 1, 2023
CA, San Francisco, USA
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