No abstract

In this paper, we collect electrical signals emitted from the brain during its normal function, specifically from a single electrode placed over the frontal lobe of the brain, to provide an interface for communication without any physical movement. The systems intended audience includes stroke victims and people with paralysis and other advanced neurologic impairments. The presented MindLogger system is a practical, cost-effective, and noninvasive solution that enables people to select letters, compile words, and create sentences by employing only their electroencephalogram (EEG) activity, alongside existing capabilities in mobile computing.

This paper explores non-intrusive, engaging, and cost effective mobile health methods to detect and monitor changes in visual acuity caused by diabetic retinopathy (linked to diabetes) and macular degeneration (linked to aging). These prevalent conditions can both lead to blindness if undetected early in their gradual progression. By leveraging mobile computing platforms and sensor technology, a serious game for use by patients at risk for these debilitating conditions is provided to monitor and to alert of any changes in vision in advance of clinical visits. The interface engages users in reading street signs within view, while the software determines the accuracy of the readings and the distance of the signs from the user, and then uses that information to track any changes in the persons vision over time.