VR Motion Sickness Analysis Database Using Bio-Signal and Eye-Tracking Data
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Solution Overview
Problem
Current methods lack comprehensive biopsychological data and experimental results to effectively analyze and prevent Virtual Reality (VR) motion sickness, primarily due to insufficient understanding of the relationship between VR content elements and motion sickness, and most studies are conducted with small participant groups, limiting the construction of a robust database for research and development.
Innovation Solution
A method and apparatus for analyzing VR content elements inducing motion sickness by conducting experiments on a large number of participants using a predetermined protocol, acquiring both objective and subjective data, and constructing a database to quantify the degree of motion sickness caused by various content elements, including bio-signal and eye-tracking data, and statistical analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If experiments are conducted on a large number of participants to construct a robust database, then the reliability and comprehensiveness of the database is improved, but the complexity and cost of the experiment increases
Solution Approach 1:
The experiment is divided into multiple sessions, each focusing on specific VR content elements (camera movement, object movement, special effects, scenario). This segmentation allows systematic data collection from large participant groups while managing experiment complexity through structured organization of data acquisition processes.
Solution Approach 2:
The database construction system is designed to handle multiple types of data (objective bio-signal data, subjective questionnaires, eye-tracking data) and store them in a unified structure. This universal approach enables comprehensive analysis of motion sickness causes across diverse VR content elements while maintaining systematic organization.
2Measurement precision
If comprehensive biopsychological data is collected to analyze VR motion sickness, then the measurement precision and comprehensiveness is improved, but the device complexity and data processing requirements increase
Solution Approach 1:
Multiple data sources (objective bio-signal measurements, subjective questionnaire responses, eye-tracking data) are merged into a single integrated database structure. This consolidation enables comprehensive analysis of motion sickness by combining different types of data while maintaining systematic organization and reducing overall system complexity.
Solution Approach 2:
A centralized database system serves as an intermediary to manage and organize the complex multi-type data collection process. The database structure acts as a mediator between diverse data sources and analysis requirements, providing systematic storage and retrieval mechanisms that simplify the overall data management complexity.
3Device complexity
If existing experiments with small participant groups are used, then the experiment complexity is reduced, but the reliability and comprehensiveness of the data is insufficient
Solution Approach 1:
The experimental design allows for dynamic adjustment of participant numbers and data collection protocols based on research requirements. This flexibility enables the system to maintain manageable experiment complexity while scaling up participant involvement to achieve sufficient data reliability and comprehensiveness for robust analysis.
Data Source
AI summary
Disclosed herein are a method and apparatus for analyzing elements inducing motion sickness in VR content. The method includes acquiring objective data based on an experiment using the VR content for measuring VR motion sickness, the experiment being conducted according to a predetermined protocol; acquiring subjective data input from the multiple participants of the experiment; and constructing a database based on the objective data and the subjective data and analyzing the degree of motion sickness induced by each of the content elements of the VR content using statistical information based on the database.