Eye-Rubbing Detection Using a Smartwatch: A Feasibility Study Demonstrated High Accuracy With Machine Learning.

Journal: Translational vision science & technology
PMID: 39226066

Abstract

PURPOSE: In this work, we present a new machine learning method based on the transformer neural network to detect eye rubbing using a smartwatch in a real-life setting. In ophthalmology, the accurate detection and prevention of eye rubbing could reduce incidence and progression of ectasic disorders, such as keratoconus, and to prevent blindness.

Authors

  • Sina Elahi
    Department of Ophthalmology, Rothschild Foundation Hospital, Paris, France.
  • Tom Mery
    Visual Intelligence for Transportation, Ecole Polytechnique Fédérale de Lausanne, Route Cantonale, Lausanne, Switzerland.
  • Christophe Panthier
    Department of Ophthalmology, Rothschild Foundation, 25 Rue Manin, Paris 75019, France.
  • Alain Saad
    Fondation Ophtalmologique Adolphe de Rothschild, Rue Manin, Paris, France.
  • Damien Gatinel
    Department of Ophthalmology, Rothschild Foundation, Paris, France; CEROC (Center of Expertise and Research in Optics for Clinicians), Paris, France.
  • Alexandre Alahi
    VITA group, Civil Engineering Institute, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland.

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