II-NEW: miSense: Platform for Medical Sensing Applications

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This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).Given the U.S. demographic trends (aging population, increasing prevalence of chronic diseases), nursing staff shortages, and decreasing hospital capacities, it is no surprise that the U.S. healthcare system faces immense challenges on a daily basis. Multiple studies have shown that the use of inefficient tools in the patient care process is one of the root causes behind overcrowded and inefficient hospitals. Thereby, tools that automate the patient monitoring process will greatly improve the quality and effectiveness of health care. While these needs are widely accepted, a multitude of problems confront technology developers. First, a multi-stage infrastructure, including sensing devices, wired and wireless networks, and back-end servers, is necessary to generate medically relevant results. Second, healthcare providers have understandably little time and patience to work with untested technologies and engineering prototypes. Finally, healthcare facilities and research with human subjects present unique technical, administrative, and ethical challenges that few technologists have encountered.This project will address these challenges through the development of miSense, an end-to-end platform for medical sensing applications. miSense includes all hardware and software components to design, develop, and deploy compelling sensing applications in the healthcare field, including open-platform devices (miTags) for connecting medical sensors, a wireless mesh network (miNet) for delivering data, and servers (miStore, miView) to store, analyze, and display patient data. Furthermore, the project will develop three medical sensing applications (miLabs) and deploy them in the JHU Emergency Department, the JHU Children's Center and the University of Maryland Trauma Center. miSense will revolutionize medical sensing applications and healthcare, as the TinyOS project revolutionized sensor networks and their applications to the sciences. Finally, this project will offer opportunities for transdisciplinary learning between computer scientists, physicians, nursing professionals, undergraduates, and high school students through involvement in the project and joint course development.