Data Collection and Analysis in Social Anxiety VR Therapies

Virtual reality (VR) therapy has emerged as a promising approach for treating social anxiety disorder by allowing controlled exposure to anxiety-provoking social situations in a safe virtual environment. Collecting and analyzing physiological data from participants during VR therapy sessions is crucial for monitoring their anxiety levels, tailoring the therapy, and assessing treatment outcomes. This article discusses the challenges and solutions for collecting and analyzing rapidly generated physiological data, such as galvanic skin response, heart rate, and respiration rate, in the context of social anxiety VR therapies. It explores techniques for real-time data streaming, storage in efficient file formats like Apache Parquet, and subsequent analysis of the collected data. The article also examines the role of data analysis in improving therapy protocols, personalizing treatment, and advancing our understanding of the physiological responses associated with social anxiety. By leveraging modern data engineering practices, VR therapy platforms can unlock valuable insights and enhance the effectiveness of exposure-based interventions for social anxiety disorder.

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Publication Details

Journal
Studia Informatica System and information technology
Published
2025-03-31
DOI
https://doi.org/10.34739/si.2024.31.05
Primary Topic
Virtual Reality Applications and Impacts
Type
article
Field-Weighted Citation Impact
0.00
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article

Data Collection and Analysis in Social Anxiety VR Therapies

Waldemar Bartyna, Marcin Stępniak
Studia Informatica System and information technology
Virtual Reality Applications and Impacts
article

Data Collection and Analysis in Social Anxiety VR Therapies

Waldemar Bartyna, Marcin Stępniak
article en

Abstract

Virtual reality (VR) therapy has emerged as a promising approach for treating social anxiety disorder by allowing controlled exposure to anxiety-provoking social situations in a safe virtual environment. Collecting and analyzing physiological data from participants during VR therapy sessions is crucial for monitoring their anxiety levels, tailoring the therapy, and assessing treatment outcomes. This article discusses the challenges and solutions for collecting and analyzing rapidly generated physiological data, such as galvanic skin response, heart rate, and respiration rate, in the context of social anxiety VR therapies. It explores techniques for real-time data streaming, storage in efficient file formats like Apache Parquet, and subsequent analysis of the collected data. The article also examines the role of data analysis in improving therapy protocols, personalizing treatment, and advancing our understanding of the physiological responses associated with social anxiety. By leveraging modern data engineering practices, VR therapy platforms can unlock valuable insights and enhance the effectiveness of exposure-based interventions for social anxiety disorder.

Studia Informatica System and information technologyVol. 31(2)
University of Siedlce (PL), Institute of Computer Science (PL)
Openalex Percentile: Top 95%
Virtual Reality Applications and Impacts
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