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Development and validation of a machine learning, smartphone-based tonometer
  1. Yue Wu1,
  2. Ian Luttrell1,
  3. Shu Feng2,
  4. Philip P Chen2,
  5. Ted Spaide2,
  6. Aaron Y Lee2,
  7. Joanne C Wen3
  1. 1Ophthalmology, University of Washington, Seattle, Washington, USA
  2. 2University of Washington, Seattle, Washington, USA
  3. 3Ophthalmology, Duke University, Durham, North Carolina, USA
  1. Correspondence to Dr Joanne C Wen, Ophthalmology, Duke University, Durham, NC 27708, USA; joanne.wen{at}


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.

  • intraocular pressure
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  • AYL and JCW contributed equally.

  • Presented at This study was previously presented at the American Glaucoma Society Annual Meeting, San Francisco, CA, 2019.

  • Contributors YW analysed and interpreted the data and drafted and revised the paper. IL acquired the data and revised the paper. SF acquired and analysed the data and revised the paper. PPC acquired the data and revised the paper. TS analysed and interpreted the data and revised the paper. AYL designed the study, analysed and interpreted the data and revised the paper. JCW conceived of and designed the study, acquired, analysed and interpreted the data and drafted and revised the paper. All authors (YW, IL, SF, PPC, TS, AYL, JCW) have given final approval of the version to be published and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

  • Funding Research to Prevent Blindness. University of Washington CoMotion Innovation Fund. AYL was supported by the NEI/NIH K23EY029246.

  • Disclaimer The funding organisations had no role in the design or conduct of this research.

  • Competing interests AYL has received grant support from Novartis and Carl Zeiss Meditec. AYL has received honoraria from Topcon and Verana Health. JCW has a patent pending US20170215728A1. None of the other authors have any competing interests related to this study.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement Data are available on reasonable request. Deidentified participant data can be requested from the co-corresponding authors.

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