Smart Hemodynamic Monitoring System for Critical Care Air Transport Team (CCATT)

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8650-08-C-6808
Agency Tracking Number: O052-H15-3047
Amount: $749,670.00
Phase: Phase II
Program: SBIR
Awards Year: 2007
Solicitation Year: 2005
Solicitation Topic Code: OSD05-H15
Solicitation Number: 2005.2
Small Business Information
9500 Innovation Drive, Manassas, VA, 20110
DUNS: 945837219
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 John Sevick
 Sr. Software Engineer
 (703) 368-6107
Business Contact
 Christine Sigety
Title: Business Management
Phone: (703) 368-6107
Research Institution
Physiologic monitors are an essential tool in the care of critically injured military and civilian patients. Typical signals monitored include cardiac rate and rhythm, end-tidal CO2, respiration rate, pulse oximetry, and non-invasive blood pressure. Today’s monitors have functional deficiencies including: unintuitive, cluttered, and primitive displays; alarms based only on single, instantaneous measurements; inability to record and subsequently utilize other patient information such as injury severity and previous treatments; lack of leveraging advances in consumer off-the-shelf (COTS) computing products that have enabled military systems to process more data at reduced costs Addressing deficiencies is hampered by manufacturer’s closed, proprietary communication and data formats In Phase I, Progeny Systems Corporation built and demonstrated a completely functional, prototype patient monitor based on COTS technology that not only collects, displays, and alerts on standard hemodynamic signals, but also includes multi-signal rules considering current and predicted measurements, electronic Patient Care Recording (ePCR), and innovative displays. In Phase II and in conjunction with two leading medical schools, Progeny will build and deploy rugged patient monitors in civilian ambulatory services and ICUs for investigational studies into improved patient monitoring, including off-line data mining of recorded data to correlate standard and novel signal measurements to patient outcome.

* information listed above is at the time of submission.

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