Virtual Reality Data for Predicting Mental Health Conditions

Vibhav Chitale; Daniel Playne; Hai Ning Liang; Nilufar Baghaei

doi:10.1109/ISMAR-Adjunct57072.2022.00011

Virtual Reality Data for Predicting Mental Health Conditions

Vibhav Chitale^*
, Daniel Playne
, Hai Ning Liang
, Nilufar Baghaei

^*Corresponding author for this work

Department of Computing

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

6 Citations (Scopus)

Abstract

Mental health conditions pose a significant challenge worldwide. Recently, virtual reality (VR) has gained tremendous popularity and has emerged as a promising technological alternative for addressing a variety of mental health conditions. Virtual reality simulates real-world experiences and generates a large amount of virtual data from participants interacting within the virtual world. Harnessing this VR data is key to better understanding participant behaviour and potentially revealing behaviour correlates of mental health conditions. The discovery of such correlates can enable researchers to design and develop targeted VR scenarios or applications for predicting, monitoring, or improving the therapeutic outcomes for mental health conditions. As a result, in this paper, we propose a novel method of using virtual reality data for predicting the presence of mental health conditions.

Original language	English
Title of host publication	Proceedings - 2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	6-8
Number of pages	3
ISBN (Electronic)	9781665453653
DOIs	https://doi.org/10.1109/ISMAR-Adjunct57072.2022.00011
Publication status	Published - 2022
Event	21st IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2022 - Singapore, Singapore Duration: 17 Oct 2022 → 21 Oct 2022

Publication series

Name	Proceedings - 2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2022

Conference

Conference	21st IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2022
Country/Territory	Singapore
City	Singapore
Period	17/10/22 → 21/10/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Data-Machine Learning
Mental Health
Modelling
Prediction
Virtual Reality

Access to Document

10.1109/ISMAR-Adjunct57072.2022.00011

Cite this

Chitale, V., Playne, D., Liang, H. N., & Baghaei, N. (2022). Virtual Reality Data for Predicting Mental Health Conditions. In Proceedings - 2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2022 (pp. 6-8). (Proceedings - 2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISMAR-Adjunct57072.2022.00011

Chitale, Vibhav ; Playne, Daniel ; Liang, Hai Ning et al. / Virtual Reality Data for Predicting Mental Health Conditions. Proceedings - 2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2022. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 6-8 (Proceedings - 2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2022).

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title = "Virtual Reality Data for Predicting Mental Health Conditions",

abstract = "Mental health conditions pose a significant challenge worldwide. Recently, virtual reality (VR) has gained tremendous popularity and has emerged as a promising technological alternative for addressing a variety of mental health conditions. Virtual reality simulates real-world experiences and generates a large amount of virtual data from participants interacting within the virtual world. Harnessing this VR data is key to better understanding participant behaviour and potentially revealing behaviour correlates of mental health conditions. The discovery of such correlates can enable researchers to design and develop targeted VR scenarios or applications for predicting, monitoring, or improving the therapeutic outcomes for mental health conditions. As a result, in this paper, we propose a novel method of using virtual reality data for predicting the presence of mental health conditions.",

keywords = "Data-Machine Learning, Mental Health, Modelling, Prediction, Virtual Reality",

author = "Vibhav Chitale and Daniel Playne and Liang, \{Hai Ning\} and Nilufar Baghaei",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 21st IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2022 ; Conference date: 17-10-2022 Through 21-10-2022",

year = "2022",

doi = "10.1109/ISMAR-Adjunct57072.2022.00011",

language = "English",

series = "Proceedings - 2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "6--8",

booktitle = "Proceedings - 2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2022",

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Chitale, V, Playne, D, Liang, HN & Baghaei, N 2022, Virtual Reality Data for Predicting Mental Health Conditions. in Proceedings - 2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2022. Proceedings - 2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2022, Institute of Electrical and Electronics Engineers Inc., pp. 6-8, 21st IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2022, Singapore, Singapore, 17/10/22. https://doi.org/10.1109/ISMAR-Adjunct57072.2022.00011

Virtual Reality Data for Predicting Mental Health Conditions. / Chitale, Vibhav; Playne, Daniel; Liang, Hai Ning et al.
Proceedings - 2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 6-8 (Proceedings - 2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2022).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

TY - GEN

T1 - Virtual Reality Data for Predicting Mental Health Conditions

AU - Chitale, Vibhav

AU - Playne, Daniel

AU - Liang, Hai Ning

AU - Baghaei, Nilufar

PY - 2022

Y1 - 2022

N2 - Mental health conditions pose a significant challenge worldwide. Recently, virtual reality (VR) has gained tremendous popularity and has emerged as a promising technological alternative for addressing a variety of mental health conditions. Virtual reality simulates real-world experiences and generates a large amount of virtual data from participants interacting within the virtual world. Harnessing this VR data is key to better understanding participant behaviour and potentially revealing behaviour correlates of mental health conditions. The discovery of such correlates can enable researchers to design and develop targeted VR scenarios or applications for predicting, monitoring, or improving the therapeutic outcomes for mental health conditions. As a result, in this paper, we propose a novel method of using virtual reality data for predicting the presence of mental health conditions.

AB - Mental health conditions pose a significant challenge worldwide. Recently, virtual reality (VR) has gained tremendous popularity and has emerged as a promising technological alternative for addressing a variety of mental health conditions. Virtual reality simulates real-world experiences and generates a large amount of virtual data from participants interacting within the virtual world. Harnessing this VR data is key to better understanding participant behaviour and potentially revealing behaviour correlates of mental health conditions. The discovery of such correlates can enable researchers to design and develop targeted VR scenarios or applications for predicting, monitoring, or improving the therapeutic outcomes for mental health conditions. As a result, in this paper, we propose a novel method of using virtual reality data for predicting the presence of mental health conditions.

KW - Data-Machine Learning

KW - Mental Health

KW - Modelling

KW - Prediction

KW - Virtual Reality

UR - https://www.scopus.com/pages/publications/85146050335

U2 - 10.1109/ISMAR-Adjunct57072.2022.00011

DO - 10.1109/ISMAR-Adjunct57072.2022.00011

M3 - Conference Proceeding

AN - SCOPUS:85146050335

T3 - Proceedings - 2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2022

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BT - Proceedings - 2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 21st IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2022

Y2 - 17 October 2022 through 21 October 2022

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Chitale V, Playne D, Liang HN, Baghaei N. Virtual Reality Data for Predicting Mental Health Conditions. In Proceedings - 2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 6-8. (Proceedings - 2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct, ISMAR-Adjunct 2022). doi: 10.1109/ISMAR-Adjunct57072.2022.00011

Virtual Reality Data for Predicting Mental Health Conditions

Abstract

Publication series

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UN SDGs

Keywords

Access to Document

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