Skip to main content

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

Publication ,  Journal Article
Wu, Y; Luttrell, I; Feng, S; Chen, PP; Spaide, T; Lee, AY; Wen, JC
Published in: Br J Ophthalmol
October 2020

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.

Duke Scholars

Altmetric Attention Stats
Dimensions Citation Stats

Published In

Br J Ophthalmol

DOI

EISSN

1468-2079

Publication Date

October 2020

Volume

104

Issue

10

Start / End Page

1394 / 1398

Location

England

Related Subject Headings

  • Tonometry, Ocular
  • Smartphone
  • Reproducibility of Results
  • Pilot Projects
  • Ophthalmology & Optometry
  • Ocular Hypertension
  • Middle Aged
  • Male
  • Machine Learning
  • Low Tension Glaucoma
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Wu, Y., Luttrell, I., Feng, S., Chen, P. P., Spaide, T., Lee, A. Y., & Wen, J. C. (2020). Development and validation of a machine learning, smartphone-based tonometer. Br J Ophthalmol, 104(10), 1394–1398. https://doi.org/10.1136/bjophthalmol-2019-315446
Wu, Yue, Ian Luttrell, Shu Feng, Philip P. Chen, Ted Spaide, Aaron Y. Lee, and Joanne C. Wen. “Development and validation of a machine learning, smartphone-based tonometer.Br J Ophthalmol 104, no. 10 (October 2020): 1394–98. https://doi.org/10.1136/bjophthalmol-2019-315446.
Wu Y, Luttrell I, Feng S, Chen PP, Spaide T, Lee AY, et al. Development and validation of a machine learning, smartphone-based tonometer. Br J Ophthalmol. 2020 Oct;104(10):1394–8.
Wu, Yue, et al. “Development and validation of a machine learning, smartphone-based tonometer.Br J Ophthalmol, vol. 104, no. 10, Oct. 2020, pp. 1394–98. Pubmed, doi:10.1136/bjophthalmol-2019-315446.
Wu Y, Luttrell I, Feng S, Chen PP, Spaide T, Lee AY, Wen JC. Development and validation of a machine learning, smartphone-based tonometer. Br J Ophthalmol. 2020 Oct;104(10):1394–1398.

Published In

Br J Ophthalmol

DOI

EISSN

1468-2079

Publication Date

October 2020

Volume

104

Issue

10

Start / End Page

1394 / 1398

Location

England

Related Subject Headings

  • Tonometry, Ocular
  • Smartphone
  • Reproducibility of Results
  • Pilot Projects
  • Ophthalmology & Optometry
  • Ocular Hypertension
  • Middle Aged
  • Male
  • Machine Learning
  • Low Tension Glaucoma