Preventing avoidable blindness through smart home-monitoring of vision

Eyecatcher is an innovative new vision home-monitoring device. It allows glaucoma patients to assess their vision at home, and to automatically share the results with a clinician, via the net.


Catalyst R2

Lead Organisation

City, University of London




Managing Complaints of Ageing

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About the project

Visual field loss is the primary symptom of glaucoma: a chronic, incurable eye condition that effects 2% of people aged over 40 years (and 10% of people over 75), and which is the 2nd leading cause of irreversible blindness worldwide. Visual field loss is also a key symptom of various genetic and neurological disorders (incl. strokes). Being able to detect and monitor visual field loss is crucial for not just diagnosing such conditions, but also for monitoring patients in order to determine if/when the patient needs a change in treatment (e.g., eye-drops, surgery, drugs, various rehabilitation regimens). If glaucoma patients could assess their own visual fields at home, then assessments could be performed more frequently, cheaply, and conveniently, and cases of irreversible blindness due to delayed or missed appointments could be avoided.

Eyecatcher® v3 is a device for measuring visual field loss (“static threshold perimetry”), designed to be used by eye patients at home, unsupervised (“home monitoring”).

The front-end technology consists of the Eyecatcher® software, an android smartphone, a wireless response button, and a pair of precisely calibrated smartglasses. The smartglasses act as a digital display. All computations, power, and data storage are provided by the smartphone, making the glasses light and comfortable to wear. The android phone also allows test results to be automatically uploaded to a secure cloud server, via an integrated SIM card. Results can also be forwarded to leading Electronic Medical Record systems, such as those used by NHS England and NHS Scotland, for review by a clinician.

Eyecatcher has been under extensive development for the past 8 years, and numerous peer-reviewed papers have been published, demonstrating its accuracy and efficacy across a range of potential use-cases. See for details.


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