Development

In recent years there has been great interest in implementing object recognition frame work on mobile phones. This has stemmed from the fact the advances in object recognition algorithm and mobile phone capabilities have built a congenial ecosystem. Application developers on mobile platforms are trying to utilize the object recognition technology to build better human computer interfaces. This approach is in the nascent phase and proper application framework is required. In this thesis, we propose a framework to overcome design challenges and provide an evaluation methodology to assess the system performance. We use the emerging Android mobile platform to implement and test the framework. We performed a case study using the proposal and reported the test result. This assessment will help developers make wise decisions about their application design. Furthermore, the Android API developers could use this information to provide better interfaces to the third party developers. The design and evaluation methodology could be extended to other mobile platforms for a wider consumer base.

The education of profoundly intellectually disabled individuals requires identifying motivators to help them learn basic tasks and skills. When these individuals also suffer from Autism Spectrum Disorder, one promising method of therapy, multisensory therapy, has been shown to relax patients, facilitating the educational process. Relaxation drastically minimizes maladaptive behaviors such as repetitive movement (stereotypy) and self-injury, allowing the participant to learn efficiently. In this study, a multi-axis measure was developed to determine behavioral differences between an experimental group that underwent the therapy and a control group that performed a functional task in their classroom. Stereotypic behaviors were significantly reduced and gaze focus was enhanced within the therapy. The significance of these effects carried over when participants were returned to their classroom.