Total VREcall: using biosignals to recognize emotional autobiographical memory in virtual reality

Tools

Gupta, K, Chan, SWT, Pai, YS, Strachan, N, Su, J, Sumich, A ORCID: https://orcid.org/0000-0003-4333-8442, Nanayakkara, S and Billinghurst, M, 2022. Total VREcall: using biosignals to recognize emotional autobiographical memory in virtual reality. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 6 (2): 55. ISSN 2474-9567

Preview

Text
1566446_Sumich.pdf - Post-print
Download (1MB) | Preview

Official URL: https://doi.org/10.1145/3534615

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.

Item Type:	Journal article
Publication Title:	Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
Creators:	Gupta, K., Chan, S.W.T., Pai, Y.S., Strachan, N., Su, J., Sumich, A., Nanayakkara, S. and Billinghurst, M.
Publisher:	Association for Computing Machinery
Date:	7 July 2022
Volume:	6
Number:	2
ISSN:	2474-9567
Identifiers:	Number Type 10.1145/3534615 DOI 1566446 Other
Divisions:	Schools > School of Social Sciences
Record created by:	Jonathan Gallacher
Date Added:	11 Nov 2022 09:14
Last Modified:	11 Nov 2022 09:14
URI:	https://irep.ntu.ac.uk/id/eprint/47375