Wireless sensor network research is being performed to address medical applications. In particular, a common vision found in the research arena is to provide sensing and wireless communication for assisted living facilities to improve lifestyle, to improve health care, and to support long term medical studies. Our research work is solving WSN problems for real-time response, data association, reliability and dependability, security and privacy, and analysis via programs that determine circadian rhythms. The work is taking an end-to-end view from collecting the data (via dust-like motes) to its analysis and use by doctors. As part of this research we are building (and have partly constructed) a WSN-based medical testbed.
The medical testbed focuses on continuous, automatic monitoring of physiological, environmental and activity data for residents in independent and assisted-living facilities. It employs a Wireless Sensor Network (WSN) which is an enabling technology for medical applications in this type of environment. For example, the WSN could detect epileptic seizures or strokes and provide smart homecare by collecting biometric and environmental data for analysis. If an event is detected, it may also provide real-time assistance by notifying emergency healthcare providers and family members. Our proposed WSN system will integrate heterogeneous devices as sensors, actuators and a body network. Some body network systems will be wearable on the patient and some will be placed inside the living space. Also, the multi-hop backbone of the new testbed will connect other traditional systems, such as PDAs, PCs, and databases. The databases will be used for long-term archiving and data mining. We will also be able to connect to large clusters for backend processing, e.g., to execute time consuming circadian rhythm programs.
This talk will describe our research problems, research ideas and the dust to doctor system being developed. It will also describe various collaborations that we have with the UVA medical school, with a medical security project at UVA, and Harvard.