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Updated: Jun 30, 2025
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Published on: April 28, 2020
Statistical Considerations for Subjective Visual Vertical and Subjective Visual Horizontal Assessment in Normal
Carey D Balaban1, Erin Williams2,3, Cynthia L Holland4
1Departments of Otolaryngology, Neurobiology, Communication Sciences and Disorders, Bioengineering, and Mechanical Engineering and Materials Science, University of Pittsburgh, Pittsburgh, PA.
This study analyzed subjective visual vertical (SVV) and subjective visual horizontal (SVH) data, finding that common clinical measures are not significantly affected by device type or sex. Normative data and Gaussian distributions support objective outlier detection in vestibular function testing.
Area of Science:
- Neuroscience
- Vestibular System Function
- Clinical Audiology
Background:
- Subjective visual vertical (SVV) and subjective visual horizontal (SVH) assessments are standard in clinical vestibular function testing.
- Understanding the statistical distributions and normative values of SVV and SVH is crucial for accurate clinical interpretation.
Purpose of the Study:
- To analyze retrospective SVV and SVH data to determine statistical distributions and normative values.
- To assess the impact of preset effects, sex differences, and device platforms (fixed-head vs. head-free) on SVV and SVH measurements.
- To evaluate the suitability of current clinical measurement averaging methods.
Main Methods:
- Retrospective analysis of SVV and SVH data from 408 healthy individuals (18-50 years) using two test platforms.
- Statistical analysis using SPSS and MATLAB to examine preset effects, sex differences, and device interactions.
- Distributional analyses to test for Gaussian distributions of clinical metrics.
Main Results:
- No significant age-related effects were observed in SVV or SVH measurements.
- Preset angle effects and deviations from orthogonality were consistent with previous reports.
- Sex and device type showed small-magnitude differences, and the common clinical averaging method for SVV and SVH was not significantly affected by these factors.
- Distributional analyses supported the hypothesis of underlying Gaussian distributions for the clinical metrics.
Conclusions:
- Established normative data and validated Gaussian distributions for SVV and SVH metrics.
- The findings support the use of z scores derived from these normative values for objective identification of functional outliers in clinical settings.
- Common clinical measures for SVV and SVH are robust across different devices and sexes.
