A fast automated method for calculating the EOG Arden ratio
Background Recording of the dark trough/light peak of the electrooculogram (EOG) remains a useful electrodiagnostic tool. Manual analysis of the recording is tedious and lengthy, and automated analysis needs to deal with artefacts due to suboptimal patient cooperation. Methods We present a novel met...
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Published in | Documenta ophthalmologica Vol. 128; no. 3; pp. 169 - 178 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.06.2014
Springer Nature B.V |
Subjects | |
Online Access | Get full text |
ISSN | 0012-4486 1573-2622 1573-2622 |
DOI | 10.1007/s10633-014-9430-5 |
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Abstract | Background
Recording of the dark trough/light peak of the electrooculogram (EOG) remains a useful electrodiagnostic tool. Manual analysis of the recording is tedious and lengthy, and automated analysis needs to deal with artefacts due to suboptimal patient cooperation.
Methods
We present a novel method of automating the processing and analysis of raw EOG data using the open-source statistical software R. Rather than attempting saccade detection, we utilize the fact that basic properties of the response (rough waveform timing) are known and simply fit a square wave to each response run—free parameters are amplitude and phase. To assess this analysis method, responses from 54 eyes of 27 patients with a variety of ophthalmic diagnoses were analysed with manual calculation and with a number of automated methods of fitting the response curve. The Arden ratio was the main outcome measure.
Results
Robust regression of a fundamental with a three-harmonic approximation of a square wave was found to be the best method. Classification accuracy with this method compared with the manual calculations as gold standard; using a lower normal threshold of 200 %, Arden ratio was found to achieve a sensitivity of 96 % and specificity of 81 %. Time taken to process and analyse the data for a subject was reduced from 20 min for the manual method to 2 min for the automated method.
Conclusions
The simple approach yielded a surprisingly effective automatic estimation of the Arden ratio. In one author’s laboratory (MB), this procedure has proved to be useful over 5 years for routine analysis. |
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AbstractList | Recording of the dark trough/light peak of the electrooculogram (EOG) remains a useful electrodiagnostic tool. Manual analysis of the recording is tedious and lengthy, and automated analysis needs to deal with artefacts due to suboptimal patient cooperation.BACKGROUNDRecording of the dark trough/light peak of the electrooculogram (EOG) remains a useful electrodiagnostic tool. Manual analysis of the recording is tedious and lengthy, and automated analysis needs to deal with artefacts due to suboptimal patient cooperation.We present a novel method of automating the processing and analysis of raw EOG data using the open-source statistical software R. Rather than attempting saccade detection, we utilize the fact that basic properties of the response (rough waveform timing) are known and simply fit a square wave to each response run-free parameters are amplitude and phase. To assess this analysis method, responses from 54 eyes of 27 patients with a variety of ophthalmic diagnoses were analysed with manual calculation and with a number of automated methods of fitting the response curve. The Arden ratio was the main outcome measure.METHODSWe present a novel method of automating the processing and analysis of raw EOG data using the open-source statistical software R. Rather than attempting saccade detection, we utilize the fact that basic properties of the response (rough waveform timing) are known and simply fit a square wave to each response run-free parameters are amplitude and phase. To assess this analysis method, responses from 54 eyes of 27 patients with a variety of ophthalmic diagnoses were analysed with manual calculation and with a number of automated methods of fitting the response curve. The Arden ratio was the main outcome measure.Robust regression of a fundamental with a three-harmonic approximation of a square wave was found to be the best method. Classification accuracy with this method compared with the manual calculations as gold standard; using a lower normal threshold of 200%, Arden ratio was found to achieve a sensitivity of 96% and specificity of 81%. Time taken to process and analyse the data for a subject was reduced from 20 min for the manual method to 2 min for the automated method.RESULTSRobust regression of a fundamental with a three-harmonic approximation of a square wave was found to be the best method. Classification accuracy with this method compared with the manual calculations as gold standard; using a lower normal threshold of 200%, Arden ratio was found to achieve a sensitivity of 96% and specificity of 81%. Time taken to process and analyse the data for a subject was reduced from 20 min for the manual method to 2 min for the automated method.The simple approach yielded a surprisingly effective automatic estimation of the Arden ratio. In one author's laboratory (MB), this procedure has proved to be useful over 5 years for routine analysis.CONCLUSIONSThe simple approach yielded a surprisingly effective automatic estimation of the Arden ratio. In one author's laboratory (MB), this procedure has proved to be useful over 5 years for routine analysis. Background Recording of the dark trough/light peak of the electrooculogram (EOG) remains a useful electrodiagnostic tool. Manual analysis of the recording is tedious and lengthy, and automated analysis needs to deal with artefacts due to suboptimal patient cooperation. Methods We present a novel method of automating the processing and analysis of raw EOG data using the open-source statistical software R. Rather than attempting saccade detection, we utilize the fact that basic properties of the response (rough waveform timing) are known and simply fit a square wave to each response run—free parameters are amplitude and phase. To assess this analysis method, responses from 54 eyes of 27 patients with a variety of ophthalmic diagnoses were analysed with manual calculation and with a number of automated methods of fitting the response curve. The Arden ratio was the main outcome measure. Results Robust regression of a fundamental with a three-harmonic approximation of a square wave was found to be the best method. Classification accuracy with this method compared with the manual calculations as gold standard; using a lower normal threshold of 200 %, Arden ratio was found to achieve a sensitivity of 96 % and specificity of 81 %. Time taken to process and analyse the data for a subject was reduced from 20 min for the manual method to 2 min for the automated method. Conclusions The simple approach yielded a surprisingly effective automatic estimation of the Arden ratio. In one author’s laboratory (MB), this procedure has proved to be useful over 5 years for routine analysis. Recording of the dark trough/light peak of the electrooculogram (EOG) remains a useful electrodiagnostic tool. Manual analysis of the recording is tedious and lengthy, and automated analysis needs to deal with artefacts due to suboptimal patient cooperation. We present a novel method of automating the processing and analysis of raw EOG data using the open-source statistical software R. Rather than attempting saccade detection, we utilize the fact that basic properties of the response (rough waveform timing) are known and simply fit a square wave to each response run--free parameters are amplitude and phase. To assess this analysis method, responses from 54 eyes of 27 patients with a variety of ophthalmic diagnoses were analysed with manual calculation and with a number of automated methods of fitting the response curve. The Arden ratio was the main outcome measure. Robust regression of a fundamental with a three-harmonic approximation of a square wave was found to be the best method. Classification accuracy with this method compared with the manual calculations as gold standard; using a lower normal threshold of 200 %, Arden ratio was found to achieve a sensitivity of 96 % and specificity of 81 %. Time taken to process and analyse the data for a subject was reduced from 20 min for the manual method to 2 min for the automated method. The simple approach yielded a surprisingly effective automatic estimation of the Arden ratio. In one author's laboratory (MB), this procedure has proved to be useful over 5 years for routine analysis.[PUBLICATION ABSTRACT] Recording of the dark trough/light peak of the electrooculogram (EOG) remains a useful electrodiagnostic tool. Manual analysis of the recording is tedious and lengthy, and automated analysis needs to deal with artefacts due to suboptimal patient cooperation. We present a novel method of automating the processing and analysis of raw EOG data using the open-source statistical software R. Rather than attempting saccade detection, we utilize the fact that basic properties of the response (rough waveform timing) are known and simply fit a square wave to each response run-free parameters are amplitude and phase. To assess this analysis method, responses from 54 eyes of 27 patients with a variety of ophthalmic diagnoses were analysed with manual calculation and with a number of automated methods of fitting the response curve. The Arden ratio was the main outcome measure. Robust regression of a fundamental with a three-harmonic approximation of a square wave was found to be the best method. Classification accuracy with this method compared with the manual calculations as gold standard; using a lower normal threshold of 200%, Arden ratio was found to achieve a sensitivity of 96% and specificity of 81%. Time taken to process and analyse the data for a subject was reduced from 20 min for the manual method to 2 min for the automated method. The simple approach yielded a surprisingly effective automatic estimation of the Arden ratio. In one author's laboratory (MB), this procedure has proved to be useful over 5 years for routine analysis. |
Author | Sarossy, Marc G. Bach, Michael Lee, Matthew H. A. |
Author_xml | – sequence: 1 givenname: Marc G. surname: Sarossy fullname: Sarossy, Marc G. email: marc.sarossy@eyeandear.org.au organization: Centre for Eye Research Australia, RMIT University – sequence: 2 givenname: Matthew H. A. surname: Lee fullname: Lee, Matthew H. A. organization: Faculty of Medicine, Nursing and Health Sciences, Monash University – sequence: 3 givenname: Michael surname: Bach fullname: Bach, Michael organization: Eye Center, University of Freiburg |
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Recording of the dark trough/light peak of the electrooculogram (EOG) remains a useful electrodiagnostic tool. Manual analysis of the recording is... Recording of the dark trough/light peak of the electrooculogram (EOG) remains a useful electrodiagnostic tool. Manual analysis of the recording is tedious and... |
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SubjectTerms | Electrooculography - methods Humans Light Medicine Medicine & Public Health Models, Statistical Ophthalmology Original Research Article Retinal Pigment Epithelium - physiology Retrospective Studies |
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Title | A fast automated method for calculating the EOG Arden ratio |
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