Vergence Variability: A Key to Understanding Oculomotor Adaptability?

Vergence eye movements were recorded from three different populations: healthy young (ages 18-35 years), adaptive presbyopic and non-adaptive presbyopic (the presbyopic groups aged above 45 years) to determine how the variability of the eye movements made by the populations differs. The variability...

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Bibliographic Details
Published in:2006 International Conference of the IEEE Engineering in Medicine and Biology Society Vol. Supplement; pp. 6777 - 6780
Main Authors: Petrock, Anne Marie, Reisman, S., Alvarez, T.
Format: Conference Proceeding Journal Article
Language:English
Published: United States IEEE 2006
Subjects:
Adolescent
Adult
Aging
Aging - physiology
Algorithms
Cities and towns
Displays
Entropy
Eye Movements - physiology
Frequency
Heart rate variability
Humans
Lenses
Middle Aged
USA Councils
Vision defects
Wavelet analysis
ISBN:9781424400324, 1424400325
ISSN:1557-170X
Online Access:Get full text
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Summary:Vergence eye movements were recorded from three different populations: healthy young (ages 18-35 years), adaptive presbyopic and non-adaptive presbyopic (the presbyopic groups aged above 45 years) to determine how the variability of the eye movements made by the populations differs. The variability was determined using Shannon Entropy calculations of Wavelet transform coefficients, to yield a non-linear analysis of the vergence movement variability. The data were then fed through a kmeans clustering algorithm to classify each subject, with no a priori knowledge of true subject classification. The results indicate a highly significant difference in the total entropy values between the three groups, indicating a difference in the level of information content, and thus hypothetically the oculomotor adaptability, between the three groups. Further, the frequency distribution of the entropy varied across groups.
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ISBN:9781424400324
1424400325
ISSN:1557-170X
DOI:10.1109/IEMBS.2006.260945