research-article

Total VREcall: Using Biosignals to Recognize Emotional Autobiographical Memory in Virtual Reality

Authors:

Sam W. T. Chan,

Nicholas Strachan,

Alexander Sumich,

Suranga Nanayakkara,

Mark BillinghurstAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 6, Issue 2

Article No.: 55, Pages 1 - 21

https://doi.org/10.1145/3534615

Published: 07 July 2022 Publication History

Abstract

Our memories and past experiences contribute to guiding our perception and action of future affective experiences. Virtual Reality (VR) experiences are more vividly memorized and recalled than non-VR ones, but there is little research on how to detect this recall in VR. We investigate the feasibility of recognizing autobiographical memory (AM) recall in VR using physiological cues: skin conductance, heart-rate variability, eye gaze, and pupillary response. We devised a methodology replicating an existing AM Test in VR. We conducted a user study with 20 participants recalling AM using three valence categories cue words: positive, negative, and neutral. We found a significant effect of AM recalls on EDA peak, and eye blink rate, with a generalized recognition accuracy of 77.1% and person dependent accuracy of up to 95.1%. This shows a promising approach for detecting AM recall in VR and we discuss the implications for VR experience design.

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Index Terms

Total VREcall: Using Biosignals to Recognize Emotional Autobiographical Memory in Virtual Reality
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Empirical studies in HCI
    2. Interaction paradigms
      1. Virtual reality

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cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 6, Issue 2

June 2022

1551 pages

EISSN:2474-9567

DOI:10.1145/3547347

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Published: 07 July 2022

Published in IMWUT Volume 6, Issue 2

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Zhang HLi XSun YFu XQiu CCarroll J(2024)VRMN-bD: A Multi-modal Natural Behavior Dataset of Immersive Human Fear Responses in VR Stand-up Interactive Games2024 IEEE Conference Virtual Reality and 3D User Interfaces (VR)10.1109/VR58804.2024.00054(320-330)Online publication date: 16-Mar-2024
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