Detection of central fixation using short-time autoregressive spectral estimation during retinal birefringence scanning

Research output: Contribution to journalArticle

Abstract

The manuscript reports on the implementation of autoregressive spectral estimation aimed at improving the accuracy of detecting short-lasting events in signals acquired by a retinal birefringence scanning device that was reported earlier. A signal consisting of two frequency components is generated, where each frequency is a multiple of the scanning frequency. One frequency is produced during central fixation, while another one prevails during off-central fixation. These components may be of a very short duration, presenting a challenge for the FFT to identify them with sufficient time- and frequency resolution. Autoregressive spectral estimation using the Burg algorithm provided a satisfactory solution, capable of reliably differentiating between the two frequency components (96 and 192 Hz) on signal segments of duration as short as 5 ms. The device and the signal analysis methods were developed originally with the purpose of checking for eye alignment and strabismus - a major risk factor for amblyopia. The method enables the technology to work with less-cooperative patients, such as young children. Other medical and non-medical applications are possible.

Original languageEnglish (US)
Pages (from-to)905-910
Number of pages6
JournalMedical Engineering and Physics
Volume37
Issue number9
DOIs
StatePublished - Sep 1 2015

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Birefringence
Scanning
Equipment and Supplies
Amblyopia
Manuscripts
Strabismus
Signal analysis
Fast Fourier transforms
Technology

Keywords

  • Amblyopia
  • Autoregressive spectral estimation
  • Central fixation
  • Eye alignment
  • Retinal birefringence scanning
  • Strabismus

ASJC Scopus subject areas

  • Biomedical Engineering
  • Biophysics

Cite this

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title = "Detection of central fixation using short-time autoregressive spectral estimation during retinal birefringence scanning",
abstract = "The manuscript reports on the implementation of autoregressive spectral estimation aimed at improving the accuracy of detecting short-lasting events in signals acquired by a retinal birefringence scanning device that was reported earlier. A signal consisting of two frequency components is generated, where each frequency is a multiple of the scanning frequency. One frequency is produced during central fixation, while another one prevails during off-central fixation. These components may be of a very short duration, presenting a challenge for the FFT to identify them with sufficient time- and frequency resolution. Autoregressive spectral estimation using the Burg algorithm provided a satisfactory solution, capable of reliably differentiating between the two frequency components (96 and 192 Hz) on signal segments of duration as short as 5 ms. The device and the signal analysis methods were developed originally with the purpose of checking for eye alignment and strabismus - a major risk factor for amblyopia. The method enables the technology to work with less-cooperative patients, such as young children. Other medical and non-medical applications are possible.",
keywords = "Amblyopia, Autoregressive spectral estimation, Central fixation, Eye alignment, Retinal birefringence scanning, Strabismus",
author = "Boris Gramatikov",
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N2 - The manuscript reports on the implementation of autoregressive spectral estimation aimed at improving the accuracy of detecting short-lasting events in signals acquired by a retinal birefringence scanning device that was reported earlier. A signal consisting of two frequency components is generated, where each frequency is a multiple of the scanning frequency. One frequency is produced during central fixation, while another one prevails during off-central fixation. These components may be of a very short duration, presenting a challenge for the FFT to identify them with sufficient time- and frequency resolution. Autoregressive spectral estimation using the Burg algorithm provided a satisfactory solution, capable of reliably differentiating between the two frequency components (96 and 192 Hz) on signal segments of duration as short as 5 ms. The device and the signal analysis methods were developed originally with the purpose of checking for eye alignment and strabismus - a major risk factor for amblyopia. The method enables the technology to work with less-cooperative patients, such as young children. Other medical and non-medical applications are possible.

AB - The manuscript reports on the implementation of autoregressive spectral estimation aimed at improving the accuracy of detecting short-lasting events in signals acquired by a retinal birefringence scanning device that was reported earlier. A signal consisting of two frequency components is generated, where each frequency is a multiple of the scanning frequency. One frequency is produced during central fixation, while another one prevails during off-central fixation. These components may be of a very short duration, presenting a challenge for the FFT to identify them with sufficient time- and frequency resolution. Autoregressive spectral estimation using the Burg algorithm provided a satisfactory solution, capable of reliably differentiating between the two frequency components (96 and 192 Hz) on signal segments of duration as short as 5 ms. The device and the signal analysis methods were developed originally with the purpose of checking for eye alignment and strabismus - a major risk factor for amblyopia. The method enables the technology to work with less-cooperative patients, such as young children. Other medical and non-medical applications are possible.

KW - Amblyopia

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