Development and validation of a machine learning, smartphone-based tonometer.

Journal Article

BACKGROUND/AIMS: To compare intraocular pressure (IOP) measurements using a prototype smartphone tonometer with other tonometers used in clinical practice. METHODS: Patients from an academic glaucoma practice were recruited. The smartphone tonometer uses fixed force applanation and in conjunction with a machine-learning computer algorithm is able to calculate the IOP. IOP was also measured using Goldmann applanation tonometry (GAT) in all subjects. A subset of patients were also measured using ICare, pneumotonometry (upright and supine positions) and Tono-Pen (upright and supine positions) and the results were compared. RESULTS: 92 eyes of 81 subjects were successfully measured. The mean difference (in mm Hg) for IOP measurements of the smartphone tonometer versus other devices was +0.24 mm Hg for GAT, -1.39 mm Hg for ICare, -3.71 mm Hg for pneumotonometry and -1.30 mm Hg for Tono-Pen. The 95% limits of agreement for the smartphone tonometer versus other devices was -4.35 to 4.83 mm Hg for GAT, -6.48 to 3.70 mm Hg for ICare, -7.66 to -0.15 mm Hg for pneumotonometry and -5.72 to 3.12 mm Hg for Tono-Pen. Overall, the smartphone tonometer results correlated best with GAT (R2=0.67, p<0.001). Of the 92 videos, 90 (97.8%) were within ±5 mm Hg of GAT and 58 (63.0%) were within ±2 mm Hg of GAT. CONCLUSIONS: Preliminary IOP measurements using a prototype smartphone-based tonometer was grossly equivalent to the reference standard.

Full Text

Duke Authors

Cited Authors

  • Wu, Y; Luttrell, I; Feng, S; Chen, PP; Spaide, T; Lee, AY; Wen, JC

Published Date

  • October 2020

Published In

Volume / Issue

  • 104 / 10

Start / End Page

  • 1394 - 1398

PubMed ID

  • 31871048

Pubmed Central ID

  • 31871048

Electronic International Standard Serial Number (EISSN)

  • 1468-2079

Digital Object Identifier (DOI)

  • 10.1136/bjophthalmol-2019-315446

Language

  • eng

Conference Location

  • England