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Aurelie Calabrese, carlos aguilar, Eric Castet; A Vision Enhancement System to help AMD patients with Face Recognition . Invest. Ophthalmol. Vis. Sci. 2017;58(8):4711.
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© ARVO (1962-2015); The Authors (2016-present)
A new visual aid, using gaze-contingent visual enhancement, and primarily intended to help reading with central field loss, was recently designed and tested with simulated scotoma (Aguilar et al. 2016). Here, we present a validation of this system carried out with AMD patients during a face recognition task.
15 individuals with binocular central field loss from AMD (mean age = 79 ± 7, mean acuity = 0.66 ± 0.16) were recruited and tested on a face pairing task. On each trial, a test face was surrounded by 8 reference faces, among which, only one matched the test face. Participants were asked to explore the screen until they can report which reference face matched the test face. During the visual enhancement condition and at any moment while exploring the screen, a simple button press would allow the participant to magnify the fixated face (located at the PRL, thanks to an eye-tracker collecting gaze position in real-time). The enhanced face would be enlarged to fit the entire screen until the participant would decide to revert to normal viewing by releasing the button. During the natural exploration condition, participants also performed the pairing task but without the visual aid. Response time and accuracy were analyzed with mixed effect models to: 1- compare the performance with and without visual aid; 2- estimate any speed-accuracy tradeoff.
On average, the percentage of correct response for the natural exploration condition was 45%. This value was significantly increased to 64% with visual enhancement (p<0.001). For the large majority of our participants (73%), this improvement was accompanied by very little increase in response time, showing relatively little speed-accuracy tradeoff.
Without visual enhancement, participants performed below the 50% chance level, confirming their struggle for face recognition and the need to use efficient visual aids. Our system significantly improved face identification accuracy by 19%, proving to be helpful under lab conditions. The small speed-accuracy tradeoff experienced by the majority of our participants provides a strong argument towards real life use efficiency of the system. Future steps to make this visual aid suitable for daily use will include its implementation in a portable and affordable device.
This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.
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