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

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

Elahi, Sina
•
Mery, Tom  
•
Panthier, Christophe
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September 1, 2024
Translational Vision Science and Technology

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. Methods: Our approach leverages the state-of-the-art capabilities of the transformer network, widely recognized for its success in the field of natural language processing (NLP). We evaluate our method against several baselines using a newly collected dataset, which consist of data from smartwatch sensors associated with various hand-face interactions. Results: The current algorithm achieves an eye-rubbing detection accuracy greater than 80% with minimal (20 minutes) and up to 97% with moderate (3 hours) user-specific fine-tuning. Conclusions: This research contributes to advancing eye-rubbing detection and establishes the groundwork for further studies in hand-face interactions monitoring using smartwatches. Translational Relevance: This experiment is a proof-of-concept that eye-rubbing detection is effectively detectable and distinguishable from other similar hand gestures, solely through a wrist-worn device and could lead to further studies and patient education in keratoconus management.

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Type
research article
DOI
10.1167/tvst.13.9.1
Scopus ID

2-s2.0-85203114621

PubMed ID

39226066

Author(s)
Elahi, Sina

Fondation Adolphe de Rothschild

Mery, Tom  

École Polytechnique Fédérale de Lausanne

Panthier, Christophe

Fondation Adolphe de Rothschild

Saad, Alain

Fondation Adolphe de Rothschild

Gatinel, Damien

Fondation Adolphe de Rothschild

Alahi, Alexandre  

École Polytechnique Fédérale de Lausanne

Date Issued

2024-09-01

Published in
Translational Vision Science and Technology
Volume

13

Issue

9

Article Number

1

Subjects

algorithm

•

deep learning

•

detection

•

eye rubbing

•

smartwatch

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
VITA  
Available on Infoscience
January 24, 2025
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/243715
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