NSF Award
2335647
The broader impact/commercial potential of this I-Corps project is the development of training software for autistic children. Currently, almost 3% of children are diagnosed with autism and only one-third receive the mental health services they need. All autistic children have difficulties transitioning between different activities and environments, creating stressful situations for them and their caregivers. The proposed technology creates customizable software solutions, including academic materials and curriculum aids, for teachers, caregivers, and parents. Current software solutions do not meet their needs because they are “one size fits all” and do not allow customization. The proposed solution combines children’s love for technology with parents’ insights about their interests to provide them with the personalized therapy and education they need. User experiences to train visual perception and transitions based on each child’s interests and needs will employ amusement as the context for learning. This will engage children’s attention and motivation, and may allow users to transfer learning from a software environment to their everyday tasks, supporting therapists, teachers, and parents.<br/><br/>This I-Corps project is based on the development of software interventions for autistic children. The proposed technology is designed to provide vision therapy to train visual acuity, and will include visual schedules to help autistic children and teenagers communicate and gain independence in their daily lives. The digital image processing methodology and software was built upon previous experience in brain circuits, visual perception and learning in humans, and mouse models of autism. Users identify target figures immersed in photographic naturalistic backgrounds depicting city and nature landscapes. The goal is to help autistic children train their visual acuity in identifying letters, words, numbers, shapes, and objects. It is particularly challenging for autistic children to shift between tasks and behaviors. Results using this approach show that with practice, individuals can learn to identify target figures more efficiently and to allocate attention to elements that are relevant for the task at hand. The proposed software requires identifying different figures in different visual scenes to help users train cognitive flexibility and transitions, alternating between different targets of attention. With practice, the proposed software may help train attentional skills and transitions between tasks and behaviors, and will include academic materials and curriculum aids as educational support.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
