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Advancement: PIMAP: A Patient Monitoring Framework in the Clinic

Speaker Name: 
Sam Mansfield
Speaker Title: 
PhD Candidate (Advisor: Katia Obraczka)
Speaker Organization: 
Computer Science and Engineering
Start Time: 
Monday, September 16, 2019 - 10:00am
End Time: 
Monday, September 16, 2019 - 12:00pm
Engineering 2, Room 399
Professor Katia Obraczka
We present PIMAP, a system architecture for continuous patient monitoring with a specific focus on preventing pressure injuries (a.k.a. bed sores). Pressure injuries are classified as "never events'', meaning they should never occur in healthcare facilities and yet in the U.S. they affect 2.5 million patients a year at a cost of $2.5 billion. In addition the majority of patients affected are the most vulnerable, the elderly and/or physically disabled. 
There are many proposed solutions to prevent pressure injuries, the most promising are patient monitoring based, such as monitoring the pressure of the patient against a mattress, monitoring the motion of the patient, and measuring the health of the patient's skin. Patient monitoring has the advantage that data can be automatically collected and analyzed without healthcare intervention, providing additional insights that would otherwise have to be calculated manually or ignored.
Through the identification of the most promising techniques and through anecdotal evidence from our collaboration with UCSF we found a lack of a reliable way to collect new medical device data. There is no current system that is able to: (1) seamlessly, reliably, and persistently  acquire patient monitoring data from various medical devices, (2) analyze acquired data, and (3) present the results to healthcare personnel in an efficient and user-friendly fashion. Instead there are many one-off solutions that will only work with a specific medical device or overly complicated systems that have too many dependencies.
From this motivation we present PIMAP (Pressure Injury Monitoring And Prevention), a system architecture that presents a standard to collect medical device data, store it and analyze it in the Cloud, in a secure and private manner. The architecture abstracts the system so that researchers can focus their efforts on specifics, such as the device or analysis without having to redesign the entire system. PIMAP is a research tool that will be released Open Source with the aim for future researchers to use and improve it.