- Fuzzy temporal reasoning
- Syndromic surveillance
- Grid-enabling the MedLEE medical natural language processor
- Home diabetes monitoring via mobile phones
My dissertation research focused primarily on Remote Display Protocols (RDPs), fallings into two main areas of study:
- Remote patient education in a telemedicine environment
- Benchmarking and optimization of RDPs in suboptimal network environments
Remote Display Protocols allow graphical displays to be virtualized and sent across a network to a client device, while applications and windowing commands are executed on the server. Using this protocol, the client sends user input to the server, and the server returns screen updates to the client.
The remote patient education project is studying the feasiblity of remotely training the older adult population of the IDEATel project to use their Home Telemedicine Units (HTUs). We are investigating the use of Remote Control Protocols, a type of RDP, as a teaching tool. We have designed and implemented an architecture called REmote Patient Education in a Telemedicine Environment (REPETE). Using REPETE, we are adapting best practices for teaching technology to older adults to the remote training paradigm and evaluating the remote training architecture and method.
Through the use of remote training we hope to improve the availability, timeliness, and effectiveness of computer education in this population.
This research, conducted in conjunction with the Network Computing Lab, has been focused on using the Slowmotion Benchmarking technique to measure RDP performance in order to optimize the performance of these RDPs and to inform the design of new RDPs, such as THINC.
These measurements have also been used to demonstrate the viability of using RDPs in a variety clinical settings, ranging from electronic medical record (EMR) access on the desktop to mobile wireless Radiology PACS workstations.