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Development of An Algorithm for Slippage-Induced Motion Artifacts Reduction in Video-Nystagmography
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Yerin Lee, Young Joon Seo, Sejung Yang
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Res Vestib Sci. 2022;21(4):104-110. Published online December 15, 2022
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DOI: https://doi.org/10.21790/rvs.2022.21.4.104
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 Abstract
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- Objectives
The slippage of the video-nystagmography devices causes motion artifacts in the trajectory of the pupil and thus results in distortion in the nystagmus waveform. In this study, the moving average was proposed to reduce slippage-induced motion artifacts from the real-world data obtained in the field.
Methods
The dataset consists of an infrared video of positional tests performed on eight patients with a lateral semicircular canal benign paroxysmal positional vertigo. The trajectories of the pupil were obtained from the video with binarization, morphological operation, and elliptical fitting algorithm. The acquired data was observed and the section where the slippage occurred was labeled by an otolaryngologist. The moving average with windows of various lengths was calculated and subtracted from the original signal and evaluated to find the most adequate parameter to reduce the motion artifact.
Results
The period of nystagmus in the given data was found to be ranged from 0.01 to 4 seconds. The slippages that appeared in the data can be categorized into fast and slow slippages. The length, distance, and speed of trajectories in the slippage ranges were also measured to find the characteristics of the motion artifact in video-nystagmography data. The shape of the nystagmus waveform was preserved, and the motion artifacts were reduced in both types of slippages when the length of the window in moving average was set to 1 second.
Conclusions
The algorithm developed in this study is expected to minimize errors caused by slippage when developing a diagnostic algorithm that can assist clinicians.
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