Background: With a large portion of older adults living longer, the number of individuals diagnosed with low vision is increasing. The use of optical coherence tomography/scanning laser ophthalmoscope (OCT/SLO) to diagnose retinal disease has become common place in the last 10 years, yet currently there are no OCT/SLO databases for pathological vision. Our aim is to develop a clinical database of individuals who have drusen (i.e., lipid deposits found under the retina), or have been diagnosed with age-related macular degeneration (AMD), with information as to how the structure of the diseased retina changes over time, as well as measures of visual and cognitive functional performance.
Methods: Fundus photographs and retinal scans will be taken using the same model of optos OCT/SLO located in three test sites (MAB-Mackay Rehabilitation Centre, School of Optometry Clinic at the University of Montreal, and the Lighthouse Institute, New York, USA). For each individual entry in the database, demographic and diagnosis information will be available. All OCT/SLO images will be graded according to the Age-related Eye Disease Study standard, in addition to number and size of drusen, severity of geographic atrophy, severity of pigment mottling and presence of choroidal neovascularization. Retinal topography and Raster scans from the OCT/SLO will provide a cross-sectional look at affected retinas. Fixation stability will be recorded using the SLO function, and present four different tasks that are designed to reproduce typical tasks of daily vision, with each task lasting for 10 seconds. The tasks are cross fixation, face recognition, visual search, and reading. These tasks in addition to the retinal scans will be used to determine the eccentricity of a preferred retinal locus from the anatomical fovea, and can be used as an outcome measure for clinical interventions in visually impaired patients.
Results: The database will be available to professors training eye-care practitioners and rehabilitation specialists as a teaching tool. Students will be able to familiarize themselves with the retina and a variety of AMD-related pathologies before they start working with patients. The database will also be accessible by researchers interested in studying AMD from basic science to epidemiology, to investigate how drusen and AMD impact visual and cognitive functional performance.
Conclusions: The common infrastructure is easily accessible to all VHRN members on request. The database will also be accessible online in 2018 (see http://cvl.concordia.ca for more information).
Background: The perceptions surrounding assistive technology have been shown to be increasingly stigmatizing in older adult populations. This stigmatization can lead individuals to the abandonment of the assistive device. Until now, the methods of identifying or predicting the stigma surrounding assistive technology has mostly been qualitative in nature. Here we present a novel quantitate and qualitative research study that uses neuro-cognitive (psychophysics and EEG) and eye tracking technology, in addition to a new questionnaire to investigate the stigma associated with assistive devices. Therefore, this approach plays a major role in understanding and predicting the neural and physiological correlates associated to stigma.
Methods: Thirty-four older adults (>50 years) took part in the study. To determine the psychophysiological predictors of stigma surrounding assistive technologies, we monitored brain activity using EEG, heart rate and eye movements using an eye-tracker while participants viewed a series of images containing either an older or younger individual in different social scenarios (e.g., talking to doctor, at coffee shop). In each scenario, the individual uses either no assistive device, a low stigmatizing device (e.g., iPad), or a high stigmatizing device (e.g., electronic magnifier).
Results: Here we present preliminary analysis of the eye movement data. Analysis shows that in comparison to images that contained a low stigmatizing device, in images that contain high stigmatizing devices, the latency to fixate the device is shorter, first fixation duration is longer, and the total number of fixations on the device are higher. The environment that the devices is used in has no effect on eye movement metrics.
Conclusions: Although the sample size is small, and based on a healthy older-adult population, these initial observations would indicate that latency to fixate and first fixation duration are predictors of stigma associated with assistive devices. Future research should expand this prediction to those actively using assistive devices, and how the measures predict abandonment over time.
Background: Visual salience computed using algorithmic procedures have been shown to predict eye-movements in a number of contexts. However, despite calls to incorporate computationally-defined visual salience metrics as a means of assessing the effectiveness of advertisements, few studies have incorporated these techniques in a marketing context. The present study sought to determine the impact of visual salience and knowledge of a brand on eye-movement patterns and buying preferences.
Methods: Participants (N=38) were presented with 54 pairs of products presented on the left and right sides of a blank white screen. For each pair, one product was a known North American product, such as Fresca?, and one was an unknown British product of the same category, such as Irn Bru?. Participants were asked to select which product they would prefer to buy while their eye movements were recorded. Salience was computed using Itti & Koch’s [2001] computational model of bottom-up salience. Products were defined as highly salient if the majority of the first five predicted fixations were in the region of the product.
Results: Results showed that participants were much more likely to prefer to buy known products, and tentative evidence suggests that participants had longer total dwell times when looking at unknown products. Salience appears to have had little or no effect on preference for a product, nor did it predict total dwell time or time to first fixation. There also appears to be no interaction between knowledge of a product and visual salience on any of the measures analyzed.
Conclusions: The results indicate that product salience may not be a useful predictor of attention under the constraints of the present experiment. Future studies could use a different operational definition of visual salience which might be more predictive of visual attention. Furthermore, a more fine-grained analysis of product familiarity based on survey data may reveal patterns obscured by the definitional constraints of the present study.
