Elderly drivers have a higher fatality rate per mile driven than any group other than males under 25. Relative to those younger drivers, whose accidents are often due to inexperience or risky behaviors, accidents that involve elderly drivers are frequently related to inattention or slowed responses, especially in individuals experiencing side effects from medications or who have chronic health conditions that might affect performance. Given the rapidly increasing proportion of elderly drivers in the population, the issue of motor vehicle accidents in this group is becoming a major public health concern and an important topic for research directed towards better understanding of its causes and at minimizing its consequences. This project aims to develop an enabling technology that will help to fill a crucial current void in knowledge about the brain function of elderly drivers. In particular, progress in the development of methods for brain function monitoring during human-computer interaction has led to the creation of sensitive, highly automated, EEC-based methods suitable for measuring neurophysiologic signals of cognition in adult subjects operating complex, computer-based systems. This project will attempt to generalize such methods to enable brain function monitoring in elderly subjects during simulated driving. Phase I will determine the scientific and technical feasibility of the proposed system. In particular, leveraging our success in other recent projects, we plan to evaluate key remaining scientific and signal processing issues related to use of such methods in the elderly, and to design a prototype measurement device that would be implemented and tested in Phase II. The proposed system would enable cost-effective large scale research studies of how an elderly person's attention is engaged and maintained during different types of driving scenarios, and the patterns of neurophysiologic activity most likely to be associated with accidents or unstable performance. The same underlying signal processing technology could be used to evaluate and refine therapeutic interventions aimed to improve attention and alertness during driving. Given the important role that the ability to operate a motor vehicle often plays in helping seniors to maintain independence and a high quality of life, there is likely to be a significant market for such technology. ? ? ?
