A wavelet approach for unsupervised nystagmus analysis on ENG and VOG recordings

Several algorithms are available to quantify nystagmus beats in electro nystagmography (ENG) and video-oculography (VOG) recordings. These algorithms use parameterized approaches to detect the fast components of nystagmus beats. This paper proposes a wavelet approach to detect fast components of nys...

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Bibliographic Details
Published in:2010 Annual International Conference of the IEEE Engineering in Medicine and Biology 2010-01, p.6333-6336
Main Authors: Jansen, S M H, Kingma, H, Peeters, R L M
Format: Article
Language:English
Subjects:
Algorithm design and analysis
Noise
Phase detection
Sensitivity
Wavelet analysis
Wavelet transforms
Online Access:Request full text
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Summary:Several algorithms are available to quantify nystagmus beats in electro nystagmography (ENG) and video-oculography (VOG) recordings. These algorithms use parameterized approaches to detect the fast components of nystagmus beats. This paper proposes a wavelet approach to detect fast components of nystagmus beats. The main advantage of this approach compared to alternatives, is the completely unsupervised automated routine. The algorithm is implemented and validated in different clinical experiments. The results are compared to that of an alternative parameterized technique. Results show that the wavelet approach is suitable for automated nystagmus analysis.
ISSN:1094-687X
1558-4615
DOI:10.1109/IEMBS.2010.5627643