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Previously submitted to: JMIR Biomedical Engineering (no longer under consideration since Jul 02, 2024)

Date Submitted: Feb 25, 2024

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

DEDector: Noninvasive Detection of Dry Eye Disease using Smartphones.

  • Vaibhav Ganatra; 
  • Soumyasis Gun; 
  • Pallavi Joshi; 
  • Anand Balasubramaniam; 
  • Kaushik Murali; 
  • Nipun Kwatra; 
  • Mohit Jain

ABSTRACT

Background:

Dry Eye Disease (DED) is a prevalent eye condition characterized by abnormalities in tear film stability. Despite its high prevalence, diagnosing DED remains challenging, primarily due to the invasive nature of most diagnostic tests, such as the Tear BreakUp Time (TBUT).

Objective:

The aim of this paper is to propose a novel smartphone-based methodology for non-invasive screening of Dry Eye Disease.

Methods:

In this work, we propose DEDector, a low-cost, smartphone-based automated Non-Invasive Break-Up Time (NIBUT) measurement methodology for DED diagnosis. Utilizing a 3D-printed placido ring attachment on a smartphone’s camera, DEDector projects concentric rings onto the cornea, capturing a video for subsequent analysis using our proposed video processing pipeline to identify tear film stability.

Results:

We conducted a real-world evaluation on 46 eyes from 23 patients, comparing the performance of DEDector against the traditional Fluorescein Break-Up Time (TBUT) method. Our results indicate a sensitivity of 77.78% and specificity of 82.14% for DEDector, outperforming the TBUT-based approach (Sensitivity = 72.22%, Specificity = 75%)

Conclusions:

DEDector may be used for large-scale and point-of-care screening of Dry Eye Disease, due to its low cost, portability, and effectiveness in detecting Dry Eye Disease.


 Citation

Please cite as:

Ganatra V, Gun S, Joshi P, Balasubramaniam A, Murali K, Kwatra N, Jain M

DEDector: Noninvasive Detection of Dry Eye Disease using Smartphones.

JMIR Preprints. 25/02/2024:57743

DOI: 10.2196/preprints.57743

URL: https://preprints.jmir.org/preprint/57743

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