June 2023
Volume 64, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2023
Infrared-Based Blink Detecting Device: A Validation Study
Author Affiliations & Notes
  • Everardo Hernandez-Quintela
    Ophthalmology, Johns Hopkins Medicine, Baltimore, Maryland, United States
  • Laura Elisa Drew-Bear
    Ophthalmology, Johns Hopkins Medicine, Baltimore, Maryland, United States
  • Hailey Spencer
    Ophthalmology, Johns Hopkins Medicine, Baltimore, Maryland, United States
  • Ashley Behrens
    Ophthalmology, Johns Hopkins Medicine, Baltimore, Maryland, United States
  • Footnotes
    Commercial Relationships   Everardo Hernandez-Quintela None; Laura Drew-Bear None; Hailey Spencer None; Ashley Behrens None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2023, Vol.64, 3999. doi:
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    • Get Citation

      Everardo Hernandez-Quintela, Laura Elisa Drew-Bear, Hailey Spencer, Ashley Behrens; Infrared-Based Blink Detecting Device: A Validation Study. Invest. Ophthalmol. Vis. Sci. 2023;64(8):3999.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : The blinking mechanism is an essential self-protection function of the eye, which maintains ocular health. The study of eyelid dynamics allows us to diagnose systemic, neurological, and ophthalmological diseases. This study aims to validate a safe, wearable, and low-cost device for measuring the blink rate (blinks per minute, b/min) that can be used in further research studies.

Methods : The blink rate of 3 healthy subjects was measured by an infrared reflective sensor (IR) on an eyewear frame. Each eye side had a single IR sensor wired to a microcontroller. The signal was recorded into an SD card and later uploaded to statistical analysis software (SPSS version 28). The device monitored the blink rate in three experiments for 5 minutes at two different distances: 1) 15 mm from the eye (S1) and 2) 10 mm from the eye (S2). The blink rate that the device registered was compared to the blink rate in the video recordings. Mean blink rates were compared using ANOVA, regression analysis, intraclass correlation coefficient, and 95% limits of agreement (Bland and Altman).

Results :
The mean blink rate measured with S1, S2, and video recording was 24.2 b/min (95%CI 22.5 to 26.0), 23.1 b/min (95% CI 21.4 to 24.7), and 24.2 b/min (95%CI 22.4 to 25.9), respectively. No statistically significant differences were found (ANOVA, p = 0.78) between all comparisons. We observed a high statistically significant correlation between sensors and video recordings (Pearson's r >= 0.96, p < 0.001). The intraclass correlation coefficient was 0.97 (95%CI 0.94 to 0.98, p < 0.001, F test) for the S1-S2 comparison and 0.96 (95%CI 0.93 to 0.97) for the S1-video comparison. The 95% limits of agreement ranged from −3.28 to 3.16 b/min in the S1-video comparison. The width of the interval was 6.44 b/min.

Conclusions : There was no significant difference in the infrared sensor's overall accuracy over the blink rate video recording. The blink rate device prototype proved to be a reliable, precise, and accurate method of measuring eyelid kinetics.

This abstract was presented at the 2023 ARVO Annual Meeting, held in New Orleans, LA, April 23-27, 2023.

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