• Andrew E Neice, Cedar Fowler, Richard A Jaffe, and John G Brock-Utne.
• Oregon Anesthesiology Group, Portland, OR, USA. Andrew.Neice@gmail.com.
• J Clin Monit Comput. 2021 Dec 1; 35 (6): 1269-1277.

AbstractMeasurement of pupillary characteristics, such as pupillary unrest in ambient light, and reflex dilation have been shown to be useful in a variety of clinical situations. Dedicated pupillometers typically capture images in the near-infrared to allow imaging in both light and darkness. However, because a subset of pupillary measurements can be acquired with levels of visible light suitable for conventional cameras, it is theoretically possible to capture data using general purpose cameras and computing devices such as those found on smartphones. Here we describe the development of a smartphone-based pupillometer and compare its performance with a commercial pupillometer. Smartphone pupillometry software was developed and then compared with a commercial pupillometer by performing simultaneous scans in both eyes, using the smartphone pupillometer and a commercial pupillometer. The raw scans were compared, as well as a selected pupillary index: pupillary unrest in ambient light. In 77% of the scans the software was able to successfully identify the pupil and iris. The raw data as well as calculated values of pupillary unrest in ambient light were in clinically acceptable levels of agreement; Bland-Altman analysis of raw pupil measurements yielded a 95% confidence interval of 0.26 mm. In certain situations a smartphone pupillometer may be an appropriate alternative to a commercial pupillometer.© 2020. Springer Nature B.V.

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