Virtual-Environment Audio Mapping to Reduce Motion Sickness
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Solution Overview
Problem
Motion sickness or cyber sickness occurs due to a mismatch between movement-related visual and auditory sensations in virtual environments, such as VR, AR, and 3D movies, which existing technologies have not adequately addressed.
Innovation Solution
A device and method that includes a processor to analyze image parameters of virtual-environment content, set corresponding voice parameters, and adjust voice information to minimize mismatches, using quantitative indices and individual characteristics to predict and reduce the likelihood of motion sickness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If voice parameters are adjusted to correspond to image parameters, then the mismatch between visual and auditory sensations is reduced, but the device complexity increases
Solution Approach 1:
The system divides the content into discrete image and voice parameter sets, analyzing each parameter independently (impact intensity, color, brightness, contact time) and adjusting corresponding voice parameters separately. This segmentation allows complex sensory coordination to be managed through systematic, modular parameter matching rather than treating the entire audio-visual stream as a monolithic problem.
Solution Approach 2:
The system dynamically adjusts voice parameters (loudness, timbre, pitch, duration) based on quantitative analysis of image parameters. By changing voice parameters in response to detected image characteristics, the system creates synchronized audio-visual experiences that reduce sensory conflict and motion sickness without requiring complex hardware modifications.
2Measurement precision
If quantitative analysis of image parameters is performed, then the precision of voice parameter adjustment is improved, but the processing time increases
Solution Approach 1:
The system pre-establishes correspondence relationships between image parameters and voice parameters before actual content processing. By defining the mapping rules in advance (impact intensity→loudness, color→timbre, brightness→pitch, contact time→duration), the system avoids complex real-time calculations and can quickly adjust voice parameters based on pre-computed quantitative image analyses.
Solution Approach 2:
The system incorporates feedback mechanisms where voice parameters are continuously adjusted based on the analyzed image parameters. This feedback loop ensures precise synchronization while maintaining efficient processing by using the quantitative image analysis results to directly guide voice parameter modifications rather than requiring iterative trial-and-error adjustments.
Data Source
AI summary
In a device for managing virtual-environment content, the device including at least one processor and a memory operatively connected to the at least one processor and configured to store at least one program executed by the at least one processor, the processor includes a first processing unit configured to extract image information of virtual-environment content output through a head-mounted display (HMD), a second processing unit configured to analyze image parameters forming the image information and determine first scores which are quantitative indices of the image parameters, a third processing unit configured to set voice parameters corresponding to the image parameters and determine second scores which are quantitative indices of the corresponding voice parameters using the first scores, and a fourth processing unit configured to output voice information of the virtual-environment content by replacing the voice parameters with the second scores.