Publikation:

Evaluating Typing Performance in Different Mixed Reality Manifestations Using Physiological Features

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2024

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Chiossi, Francesco
El Khaoudi, Yassmine
Ou, Changkun
Sidenmark, Ludwig

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Deutsche Forschungsgemeinschaft (DFG): 251654672 TRR 161
European Union (EU): 952026

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Accepted

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Proceedings of the ACM on Human-Computer Interaction. ACM. 2024, 8, 542. eISSN 2573-0142. Verfügbar unter: doi: 10.1145/3698142

Zusammenfassung

Mixed reality enables users to immerse themselves in high-workload interaction spaces like office work scenarios. We envision physiologically adaptive systems that can move users into different mixed reality manifestations, to improve their focus on the primary task. However, it is unclear which manifestation is most conducive for high productivity and engagement. In this work, we evaluate whether physiological indicators for engagement can be discriminated for different manifestations. For this, we engaged participants in a typing task in three different mixed reality manifestations (augmented reality, augmented virtuality, virtual reality) and monitored physiological correlates (EEG, ECG, and eye tracking) of users’ engagement and workload. We found that users achieved best typing performances in augmented reality and augmented virtuality. At the same time, physiological engagement peaked in augmented virtuality, while workload decreased. We conclude that augmented virtuality strikes a good balance between the different manifestations, as it facilitates displaying the physical keyboard for improved typing performance and, at the same time, allows one to block out the real world, removing many real-world distractors.

Zusammenfassung in einer weiteren Sprache

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004 Informatik

Schlagwörter

Mixed Reality, Virtual Reality, Augmented Reality, Augmented Virtuality, Engagement, Electroencephalography, Eye Tracking, Physiological Computing

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ISO 690CHIOSSI, Francesco, Yassmine EL KHAOUDI, Changkun OU, Ludwig SIDENMARK, Abdelrahman ZAKY, Tiare FEUCHTNER, 2024. Evaluating Typing Performance in Different Mixed Reality Manifestations Using Physiological Features. In: Proceedings of the ACM on Human-Computer Interaction. ACM. 2024, 8, 542. eISSN 2573-0142. Verfügbar unter: doi: 10.1145/3698142
BibTex
@article{Chiossi2024Evalu-70964,
  year={2024},
  doi={10.1145/3698142},
  title={Evaluating Typing Performance in Different Mixed Reality Manifestations Using Physiological Features},
  volume={8},
  journal={Proceedings of the ACM on Human-Computer Interaction},
  author={Chiossi, Francesco and El Khaoudi, Yassmine and Ou, Changkun and Sidenmark, Ludwig and Zaky, Abdelrahman and Feuchtner, Tiare},
  note={Article Number: 542}
}
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Beschreibung der Forschungsdaten
Collected datasets, sentence stimuli, MR environments, and experiment setup and analysis script
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