More and more people suffer from age-related eye conditions, e.g. Macular Degeneration. One of the problems experienced by these people is navigation. A strategy shown by many juvenile visually impaired persons (VIPs) is using auditory information for navigation. Therefore, it is important to train age-related VIPs to use auditory information for navigation. Hence the serious game HearHere was developed to train the focused auditory attention of age-related VIPs enhancing the use of auditory information for navigation, available as an application for tablets. Players of the game are instructed to navigate virtually as quickly as possible to a specific sound, requiring focused auditory attention. In an experimental study, the effectiveness of the game on improving focused auditory attention was examined. Forty participants were included, all students of the University of Groningen with normal or corrected-to-normal vision. By including sighted participants, we could investigate whether someone who was used to rely on its vision could improve its focused auditory attention after playing HearHere. As a control, participants played a digital version of Sudoku. The order of playing the games was counterbalanced. Participants were asked to perform a dichotic listening task before playing any game, after playing the first game and after playing the second game. It was found that participants improved significantly more in their performance on the dichotic listening task after having played HearHere (p<.001) than after playing Sudoku (p=.040). This means the game indeed improves focused auditory attention, a skill necessary to navigate on sounds. In conclusion, we recommend the game to become part of the orientation and mobility program, offering age-related VIPs the opportunity to practice the use of auditory information for navigation. Currently, we are working on a version that is suitable for actual use.
The finding of poor lighting conditions in nursing homes in combination with a high prevalence of visual problems (with cataract found to be the most common age related pathology), stretches the need of enhanced awareness of eye care by professional caregivers.
Purpose: To establish age-related, normal limits of monocular and binocular spatial vision under photopic and mesopic conditions. Methods: Photopic and mesopic visual acuity (VA) and contrast thresholds (CTs) were measured with both positive and negative contrast optotypes under binocular and monocular viewing conditions using the Acuity-Plus (AP) test. The experiments were carried out on participants (age range from 10 to 86 years), who met pre-established, normal sight criteria. Mean and ± 2.5σ limits were calculated within each 5-year subgroup. A biologically meaningful model was then fitted to predict mean values and upper and lower threshold limits for VA and CT as a function of age. The best-fit model parameters describe normal aging of spatial vision for each of the 16 experimental conditions investigated. Results: Out of the 382 participants recruited for this study, 285 participants passed the selection criteria for normal aging. Log transforms were applied to ensure approximate normal distributions. Outliers were also removed for each of the 16 stimulus conditions investigated based on the ±2.5σ limit criterion. VA, CTs and the overall variability were found to be age-invariant up to ~50 years in the photopic condition. A lower, age-invariant limit of ~30 years was more appropriate for the mesopic range with a gradual, but accelerating increase in both mean thresholds and intersubject variability above this age. Binocular thresholds were smaller and much less variable when compared to the thresholds measured in either eye. Results with negative contrast optotypes were significantly better than the corresponding results measured with positive contrast (p < 0.004). Conclusions: This project has established the expected age limits of spatial vision for monocular and binocular viewing under photopic and high mesopic lighting with both positive and negative contrast optotypes using a single test, which can be implemented either in the clinic or in an occupational setting.
Receiving the first “Rijbewijs” is always an exciting moment for any teenager, but, this also comes with considerable risks. In the Netherlands, the fatality rate of young novice drivers is five times higher than that of drivers between the ages of 30 and 59 years. These risks are mainly because of age-related factors and lack of experience which manifests in inadequate higher-order skills required for hazard perception and successful interventions to react to risks on the road. Although risk assessment and driving attitude is included in the drivers’ training and examination process, the accident statistics show that it only has limited influence on the development factors such as attitudes, motivations, lifestyles, self-assessment and risk acceptance that play a significant role in post-licensing driving. This negatively impacts traffic safety. “How could novice drivers receive critical feedback on their driving behaviour and traffic safety? ” is, therefore, an important question. Due to major advancements in domains such as ICT, sensors, big data, and Artificial Intelligence (AI), in-vehicle data is being extensively used for monitoring driver behaviour, driving style identification and driver modelling. However, use of such techniques in pre-license driver training and assessment has not been extensively explored. EIDETIC aims at developing a novel approach by fusing multiple data sources such as in-vehicle sensors/data (to trace the vehicle trajectory), eye-tracking glasses (to monitor viewing behaviour) and cameras (to monitor the surroundings) for providing quantifiable and understandable feedback to novice drivers. Furthermore, this new knowledge could also support driving instructors and examiners in ensuring safe drivers. This project will also generate necessary knowledge that would serve as a foundation for facilitating the transition to the training and assessment for drivers of automated vehicles.
