A

Convolutional neural networks for quantitative smartphone video nystagmography: ConVNG

medRxiv

Abstract

Abstract Background Eye movement abnormalities are paramount in neurological disorders. However, unaided eye movement assessments lack granularity. Although videooculography (VOG) improves diagnostic accuracy, resource intensiveness preclude its broad use. To bridge this care gap, we here validate a framework for smartphone video-based nystagmography capitalizing on recent computer vision advances. Methods A recurrent convolutional network was fine-tuned for pupil tracking using >550 annotated frames: ConVNG. Slow phase velocity of optokinetic nystagmus was calculated in 10 subjects using both ConVNG and VOG. Equivalence of accuracy and precision was assessed using the “two one-sample t-test” (TOST) and Bayesian interval-null approaches. Results ConVNG tracking accuracy reached 9-15% of an average pupil diameter. SPV measurement accuracy was equivalent to VOG (p< .017; Bayes factors (BF) > 24). Average precision was 0.30° for ConVNG and 0.12° for VOG. Conclusions ConVNG enables smartphone video nystagmography with an accuracy comparable to VOG and precision approximately one order of magnitude higher than comparable ARKit applications. This serves as a blueprint for highly accessible tools with potential to accelerate progress toward precise and personalized Medicine.

Authors 8

  1. Maximilian Uwe Friedrich corresponding

    Universitätsklinikum Würzburg

    Affiliation as printed

    University Hospital Wuerzburg, Department of Neurology, Josef-Schneider Strasse 11, 97080 Wuerzburg, Germany

    University Hospital Wuerzburg, Department of Neurology, Josef-Schneider Strasse , 97080 Wuerzburg, Germany

  2. Brandenburg University of Technology Cottbus-Senftenberg

    Affiliation as printed

    Brandenburg University of Technology Cottbus, Senftenberg, Germany

  3. Universitätsklinikum Würzburg

    Affiliation as printed

    University Hospital Wuerzburg, Department of Otorhinolaryngology, Josef-Schneider Strasse 11, 97080 Wuerzburg, Germany

  4. Universitätsklinikum Aachen

    Affiliation as printed

    University Hospital Aachen, Department of Otorhinolaryngology, Pauwelsstraße 30, 52074 Aachen

    University Hospital Aachen, Department of Otorhinolaryngology, Pauwelsstraße 30, 5207 Aachen

  5. Universitätsklinikum Würzburg

    Affiliation as printed

    University Hospital Wuerzburg, Department of Neurology, Josef-Schneider Strasse 11, 97080 Wuerzburg, Germany

    University Hospital Wuerzburg, Department of Neurology, Josef-Schneider Strasse , 97080 Wuerzburg, Germany

  6. Universitätsklinikum Würzburg

    Affiliation as printed

    University Hospital Wuerzburg, Department of Neurology, Josef-Schneider Strasse 11, 97080 Wuerzburg, Germany

    University Hospital Wuerzburg, Department of Neurology, Josef-Schneider Strasse , 97080 Wuerzburg, Germany

  7. Robert Lucien Peach corresponding

    Engineering and Physical Sciences Research Council · Universitätsklinikum Würzburg · Imperial College London

    Affiliation as printed

    Department of Brain Sciences and EPSRC Centre for Mathematics of Precision Healthcare, Imperial College London, London, SW7 2AZ, UK

    University Hospital Wuerzburg, Department of Neurology, Josef-Schneider Strasse 11, 97080 Wuerzburg, Germany

    University Hospital Wuerzburg, Department of Neurology, Josef-Schneider Strasse , 97080 Wuerzburg, Germany

  8. Universitätsklinikum Würzburg

    Affiliation as printed

    University Hospital Wuerzburg, Department of Neurology, Josef-Schneider Strasse 11, 97080 Wuerzburg, Germany

    University Hospital Wuerzburg, Department of Neurology, Josef-Schneider Strasse , 97080 Wuerzburg, Germany

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References 63