Pupillary escape

Cox, Terry A.

doi:10.1212/wnl.42.7.1271

Cited by 16 publications

(1 citation statement)

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“…The ability of pupillometry to capture reflexive pupil contraction has been investigated for glaucoma (Adhikari et al 2016, Najjar et al 2018 and other disorders (Ferrari et al 2010, Martínez-Ricarte et al 2013. However, it has been shown that during steady-state lighting conditions, the pupil diameter undergoes oscillations (Miller and Thompson 1978, Cox 1992, Hunter et al 2000. The association of the time period of these oscillations with neuro-ophthalmological diseases has been reported (Ukai et al 1980, Hamilton and Drewry 1983, Kim et al 1995, Milton et al 1988.…”

Section: Introductionmentioning

confidence: 99%

Pupillometric recordings to detect glaucoma

Bhowmik¹,

Arjunan²,

Sarossy³

et al. 2021

Physiol. Meas.

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Objective. Glaucoma is the second cause of vision loss with early diagnosis having significantly better prognosis. We propose the use of hippus, the steady-state pupil oscillations, obtained from an eye-tracker for computerised detection of glaucoma. Approach. Pupillary data were recorded using a commercial eye-tracker device directly to the laptop. A total of 40 glaucoma patients and 30 age-matched controls were recruited for the study. The signals were de-noised, and the entropy of the steady-state oscillations was obtained for two light intensities, 34 and 100 cd m−2. Main results. The results show that at 100 cd m−2, there was significant difference (p < 0.05) between the sample entropy of the healthy eyes (0.55 ± 0.017) and glaucoma eyes (0.7 ± 0.034). The results at 34 cd m−2 were also significantly different, though to a lesser extent. Significance. Entropy of the pupillary oscillations, or hippus, obtained using an eye-tracking device showed a significant difference between glaucoma and healthy eyes. The method used commercially available inexpensive hardware and thus has the potential for wide-scale deployment for computerized detection of glaucoma.

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