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Evaluating the efficacy of haptic feedback, 360° treadmill-integrated Virtual Reality framework and longitudinal training on decision-making performance in a complex search-and-shoot simulation

  • Akash K. Rao*
  • , Arnav Bhavsar
  • , Shubhajit Roy Chowdhury
  • , Sushil Chandra
  • , Ramsingh Negi
  • , Prakash Duraisamy
  • , Varun Dutt
  • *Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Virtual Reality (VR) has made significant strides, offering users a multitude of ways to interact with virtual environments. Each sensory modality in VR provides distinct inputs and interactions, enhancing the user's immersion and presence. However, the potential of additional sensory modalities, such as haptic feedback and 360° locomotion, to improve decision-making performance has not been thoroughly investigated. This study addresses this gap by evaluating the impact of a haptic feedback, 360° locomotion-integrated VR framework and longitudinal, heterogeneous training on decision-making performance in a complex search-and-shoot simulation. The study involved 32 participants from a defence simulation base in India, who were randomly divided into two groups: experimental (haptic feedback, 360° locomotion-integrated VR framework with longitudinal, heterogeneous training) and placebo control (longitudinal, heterogeneous VR training without extrasensory modalities). The experiment lasted 10 days. On Day 1, all subjects executed a search-and-shoot simulation closely replicating the elements/situations in the real world. From Day 2 to Day 9, the subjects underwent heterogeneous training, imparted by the design of various complexity levels in the simulation using changes in behavioral attributes/artificial intelligence of the enemies. On Day 10, they repeated the search-and-shoot simulation executed on Day 1. The results showed that the experimental group experienced a gradual increase in presence, immersion, and engagement compared to the placebo control group. However, there was no significant difference in decision-making performance between the two groups on day 10. We intend to use these findings to design multisensory VR training frameworks that enhance engagement levels and decision-making performance.

    Original languageEnglish
    Title of host publicationArtificial Intelligence and Machine Learning for Multi-Domain Operations Applications VI
    EditorsPeter J. Schwartz, Benjamin Jensen, Myron E. Hohil
    PublisherSPIE
    ISBN (Electronic)9781510674202
    DOIs
    Publication statusPublished - 2024
    EventArtificial Intelligence and Machine Learning for Multi-Domain Operations Applications VI 2024 - National Harbor, United States
    Duration: 22-04-202426-04-2024

    Publication series

    NameProceedings of SPIE - The International Society for Optical Engineering
    Volume13051
    ISSN (Print)0277-786X
    ISSN (Electronic)1996-756X

    Conference

    ConferenceArtificial Intelligence and Machine Learning for Multi-Domain Operations Applications VI 2024
    Country/TerritoryUnited States
    CityNational Harbor
    Period22-04-2426-04-24

    All Science Journal Classification (ASJC) codes

    • Electronic, Optical and Magnetic Materials
    • Condensed Matter Physics
    • Computer Science Applications
    • Applied Mathematics
    • Electrical and Electronic Engineering

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