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Fractal Dimension Analysis of Transient Visual Evoked Potentials: Optimisation and Applications.

Mei Ying Boon1, Bruce Ian Henry2, Byoung Sun Chu1

  • 1School of Optometry and Vision Science, UNSW Australia, Sydney, New South Wales, Australia.

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|September 7, 2016
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Summary

This study developed a fractal dimension analysis protocol for visual evoked potentials (VEPs). The method successfully distinguished between normal and abnormal VEPs, showing higher fractal dimensions in abnormal cases.

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Visual evoked potentials (VEPs) reflect brain activity in the visual cortex.
  • VEP analysis typically focuses on peak latency and amplitude.
  • VEPs possess complex, non-periodic structures potentially quantifiable by fractal dimension.

Purpose of the Study:

  • To systematically investigate parameters for measuring VEP fractal dimension.
  • To develop an optimal analysis protocol for VEP fractal dimension measurement.
  • To apply the developed protocol to differentiate normal and abnormal VEPs.

Main Methods:

  • Mathematical transformation of VEP time series using delay time (τ) and embedding dimension (m).
  • Fractal dimension calculation via scaling analysis of transformed VEP data.
  • Optimization of τ, m, and scaling parameters by assessing result consistency across sampling frequencies.
  • Pilot testing of the optimized protocol on normal and abnormal VEP samples.

Main Results:

  • Consistent fractal dimension (D2) estimates were achieved with specific τ and m values across different sampling frequencies.
  • Higher fractal dimensions were observed in abnormal than normal achromatic VEPs in adults (p=0.02).
  • Increased variance in fractal dimensions was found in abnormal compared to normal chromatic VEPs in children (p=0.01).

Conclusions:

  • An effective analysis protocol for assessing the fractal dimension of transformed VEPs has been successfully developed.
  • The developed protocol shows potential for differentiating between normal and abnormal VEPs.