Waveform type evaluation in congenital nystagmus

  • Authors:

  • Giulio Pasquariello;Mario Cesarelli;Maria Romano;Antonio La Gatta;Paolo Bifulco;Antonio Fratini

  • Affiliations:

  • Dept. of Biomedical, Electronic and Telecommunication Engineering, University "Federico II" of Naples, Via Claudio 21, 80125 Napoli, Italy;Dept. of Biomedical, Electronic and Telecommunication Engineering, University "Federico II" of Naples, Via Claudio 21, 80125 Napoli, Italy;Dept. of Biomedical, Electronic and Telecommunication Engineering, University "Federico II" of Naples, Via Claudio 21, 80125 Napoli, Italy;Math4Tech Center, University of Ferrara, via Saragat 1, 44100 Ferrara, Italy;Dept. of Biomedical, Electronic and Telecommunication Engineering, University "Federico II" of Naples, Via Claudio 21, 80125 Napoli, Italy;Dept. of Biomedical, Electronic and Telecommunication Engineering, University "Federico II" of Naples, Via Claudio 21, 80125 Napoli, Italy

  • Venue:
  • Computer Methods and Programs in Biomedicine
  • Year:
  • 2010

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Abstract

Congenital nystagmus is an ocular-motor disorder characterised by involuntary, conjugated and bilateral to and fro ocular oscillations. In this study a method to recognise automatically jerk waveform inside a congenital nystagmus recording and to compute foveation time and foveation position variability is presented. The recordings were performed with subjects looking at visual targets, presented in nine eye gaze positions; data were segmented into blocks corresponding to each gaze position. The nystagmus cycles were identified searching for local minima and maxima (SpEp sequence) in intervals centred on each slope change of the eye position signal (position criterion). The SpEp sequence was then refined using an adaptive threshold applied to the eye velocity signal; the outcome is a robust detection of each slow phase start point, fundamental to accurately compute some nystagmus parameters. A total of 1206 slow phases was used to compute the specificity in waveform recognition applying only the position criterion or adding the adaptive threshold; results showed an increase in negative predictive value of 25.1% using both features. The duration of each foveation window was measured on raw data or using an interpolating function of the congenital nystagmus slow phases; foveation time estimation less sensitive to noise was obtained in the second case.