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VR – Fear of Flying

In this demo, the participant is seated in an airplane and experiences normal flight, turbulence, and landing. Tactile feedback is employed to increase the experience of presence.

Usage Guidelines

This demo is also intended to serve as a tutorial on how to construct a virtual reality experiment. It can be fully modified and has been designed in a modular format with extensive comments to allow reuse of parts in other experiments. Code is written in the Python programming language and extensive support on programming with Python is provided in the software package and user forums. 3D models from the demo can be reused within the VR platform (only).

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Details

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Virtual environment for fear of flying Objectives

  1. Expose participants to an airplane environment.
  2. Record their physiological responses to different aspects of the experience of being in an airplane.

Overview

Participants are immersed in a virtual environment where they are seated in an airplane and experience normal flight, turbulence, and a landing. Tactile feedback is employed (a low-frequency driver is placed underneath the chair) to increase the experience of presence. The experimenter can trigger certain events (e.g. landing sequence, turbulence, cabin announcements, etc.).

Data analysis

All events are marked in the physiological record, which facilitates automated data analysis.

Support

Application Notes

Knowledge Base

Hardware Packages   |   VR – Fear of Flying

Hardware Bundles are complete solutions for the specified application. Choose your preferred platform and bundle, then click "Request Pricing" to request an estimate, add/remove items, or complete purchase. If you have questions about specific items, click through to the product web page for details and specifications, or contact your Local Sales contact.

Wired

Spotlight On
free BIOPAC webinar

fNIRS Data Analysis

In this fNIRS training, you will see a typical analysis workflow for fNIRS data in experiments featuring both event-based and continuous stimulation. Learn about a powerful yet easy-to-use software package with both a graphical user interface and scripting capability (for automation).

What You Will Learn:
• Preparing data for analysis
• Signal conditioning, noise removal, and managing artifacts
• Best practices for visualizing recorded data
• Block analysis using event markers and/or time
• Further temporal and spatial processing of data, including cell-by-cell processing
• Automation of analysis procedures
• Performing common statistical comparisons (t-test, ANOVA)
• Spatial visualization
LIVE Webinar Aug 25th 8am PT/11am ET

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