Top Five: Wearables and Consumer Devices in Vision Monitoring

Fatima Kalabi

Wearables and consumer-grade devices are shifting “monitoring” from episodic clinic snapshots to higher-frequency, patient-driven data. The opportunity is real – but the evidence base is uneven, and implementation succeeds or fails on workflow: what triggers review, how false alarms are handled, and whether the pathway can deliver timely confirmation and treatment.

1) Smartphone self-testing for macular disease: useful signal, but not a standalone substitute

Hyperacuity-based self-tests (notably Alleye) can discriminate wet from dry AMD in clinical cohorts and are usable on patients’ own devices. In a clinical practice study, the app showed good diagnostic performance for detecting wet AMD (1). Real-world monitoring studies also suggest that “alarm” events can correlate with subsequent deterioration in vision and/or OCT changes, supporting use as an adjunct between visits (2). Importantly, prospective work quantifying false alarms found relatively low false-alarm rates, addressing a common clinician concern about workload and patient anxiety (3).

Caution: rigorous diagnostic-accuracy evaluation in treated nAMD found that several home-monitoring tests did not achieve sufficient accuracy to be ready for routine clinical deployment as a replacement for clinic-based assessment (4). In practice, these tools work best as triage enrichers – helping you decide who should be brought forward – rather than as arbiters of disease activity.

2) Home tonometry with patient-operated devices: a practical step change for selected glaucoma patients

Self-tonometry is one of the most “clinic-ready” consumer-adjacent monitoring approaches because it addresses a known limitation: sparse IOP sampling. Evidence suggests home tonometry can detect therapy-related IOP changes that might be missed by office measurements, supporting its use for targeted questions (e.g., suspected peaks, steroid response, adherence uncertainty) rather than blanket rollout (5). The clinical value is highest when you specify what pattern would change management (e.g., consistent peaks above a threshold; large diurnal range; IOP rise after medication change) and document an action rule.

3) Continuous IOP monitoring: telemetric implants and smart contact lenses are maturing, but adoption hinges on “what you do with the curve”

Implantable telemetric sensors (e.g., suprachoroidal systems) are generating longer-term safety/performance data, including multi-year follow-up in glaucoma patients with agreement analyses versus Goldmann applanation (6). In parallel, smart contact lens sensor systems are being evaluated for accuracy in human eyes, representing a less invasive route to denser IOP information—though these are still early in the clinical translation curve and require careful validation and interpretation (7).

Clinical reality: continuous data is only helpful if you have (a) a validated measurement construct, (b) clear thresholds linked to management changes, and (c) capacity to act. Without these, continuous monitoring risks becoming “high-resolution uncertainty.”

4) Smart glasses and AR for low vision: measurable gains, but indications must be precise

Consumer-style headsets and AR smart glasses can enhance functional vision via contrast enhancement, magnification, edge detection, and field remapping. A controlled study using a consumer AR device demonstrated both promise and clear limitations, reinforcing the need to match technology to task (mobility, object recognition, reading) and patient phenotype (8). Newer AR aids designed for peripheral field loss (e.g., retinitis pigmentosa) show early efficacy signals in small cohorts, suggesting a role as part of structured low-vision rehabilitation rather than an off-the-shelf fix (9). Wearable electronic vision enhancement systems have also been tested in randomized crossover designs in AMD, supporting the idea that some benefits can be quantified under trial conditions (10).

5) At-home visual field and functional testing using tablets/VR: the most scalable frontier (if reliability holds)

Remote functional testing is attractive because it leverages ubiquitous hardware (tablets/VR headsets) and targets outcomes that matter to patients (field, sensitivity, function). Virtual reality oculokinetic perimetry has shown reproducibility and meaningful relationships with conventional perimetry/OCT measures, supporting continued development as a monitoring adjunct (11). Separately, real-world home studies using online perimetry platforms (e.g., Melbourne Rapid Fields) are now reporting early results, including feasibility of home deployment—an important step toward scalable glaucoma monitoring outside clinics (12).

References

  1. Schmid MK, Thiel MA, Lienhard KR, Schlingemann RO, Faes L, Bachmann LM. Reliability and diagnostic performance of a novel mobile app for hyperacuity self-monitoring in patients with age-related macular degeneration. Eye (Lond). 2019;33(10):1584–1589. doi:10.1038/s41433-019-0455-6. (PMC)
  2. Islam M, Sansome SG, Das R, Lukic M, Chong NV, Teo KYC, et al. Smartphone-based remote monitoring of vision in macular disease enables early detection of worsening pathology and need for intravitreal therapy. BMJ Health Care Inform. 2021;28:e100310. (PubMed)
  3. Faes L, Islam M, Bachmann LM, Lienhard KR, Schmid MK, Sim DA. False alarms and the positive predictive value of smartphone-based hyperacuity home monitoring for the progression of macular disease: a prospective cohort study. Eye (Lond). 2021;35(11):3035–3040. doi:10.1038/s41433-020-01356-2. (PMC)
  4. Hogg RE, Sivaprasad S, Wickens R, et al. Home-Monitoring Vision Tests to Detect Active Neovascular Age-Related Macular Degeneration. JAMA Ophthalmol. 2024;142(6):512–520. doi:10.1001/jamaophthalmol.2024.0918 (JAMA Network)
  5. Scott AT, et al. The utility of iCare HOME tonometry for detection of therapy-related intraocular pressure changes in glaucoma and ocular hypertension. Ophthalmol Glaucoma. 2022. (PubMed)
  6. Micheletti E, Mansouri K, Dick HB, Hoffmann EM, Mackert MJ, Weinreb RN, Szurman P; EYEMATE-SC Study Group. Long-term safety and performance of a suprachoroidal pressure sensor system: results of the EYEMATE-SC trial follow-up study. Ophthalmology. 2025;132:775–784. doi:10.1016/j.ophtha.2025.01.021. (PubMed)
  7. Wei Y, Zhang Y, Chen Z, Chong JIT, Lee CCH, Karunaratne IK, et al. A novel contact lens sensor system for continuous intraocular pressure monitoring: evaluation of accuracy in human eyes. Ophthalmol Sci. 2025;5(5):100826. doi:10.1016/j.xops.2025.100826. (PubMed)
  8. Kinateder M, Gualtieri J, Dunn MJ, Jarosz W, Yang XD, Cooper EA. Using an augmented reality device as a distance-based vision aid—promise and limitations. Optom Vis Sci. 2018;95(9):727–737. doi:10.1097/OPX.0000000000001232. (PubMed)
  9. Ortiz C, Bernardez-Vilaboa R, Povedano-Montero FJ, Álvaro-Rubio MP, Cedrún-Sánchez JE. Evaluation of an augmented reality-based visual aid for people with peripheral visual field loss. Photonics. 2025;12(3):262. doi:10.3390/photonics12030262. (MDPI)
  10. Miller A, et al. The usefulness of a wearable electronic vision enhancement system for people with age-related macular degeneration: a randomized crossover trial. Transl Vis Sci Technol. 2025;14(9):8. doi:10.1167/tvst.14.9.8. (PubMed)
  11. Greenfield JA, Deiner M, Nguyen A, Wollstein G, Damato B, Backus BT, Wu M, Schuman JS, Ou Y. Virtual Reality Oculokinetic Perimetry Test Reproducibility and Relationship to Conventional Perimetry and OCT. Ophthalmol Sci. 2021 Dec 21;2(1):100105. doi: 10.1016/j.xops.2021.100105. (PubMed)
  12. Kong GYX, Dirani M, Tiang J, Prea SM, Bedggood P, Vingrys AJ. Melbourne Rapid Fields Online Perimeter Home Visual Field Study for Glaucoma: 3-Month Results. Ophthalmol Glaucoma. 2025 Nov 17:S2589-4196(25)00240-6. doi: 10.1016/j.ogla.2025.10.008. (PubMed)

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