CAMBRIDGE, MA – Charles River Analytics Inc., developer of intelligent systems solutions, has partnered with Assured Information Security, Tozny, and the University of Washington to further develop our Health and Injury Prediction and Prevention using Complex Reasoning and Analytic Techniques Integrated on a Cellphone App (HIPPOCRATIC App). Under DARPA’s Warfighter Analytics using Smartphones for Health (WASH) program, HIPPOCRATIC App detects signals that provide early indications of illness and injury, leading to a better prognosis.
“Our HIPPOCRATIC App marks a revolutionary breakthrough in healthcare delivery for both Warfighters and civilians,” said Dr. Bethany Bracken, Principal Scientist at Charles River and Principal Investigator on the effort. “HIPPOCRATIC App makes early detection effective, accessible, cost-effective, and convenient.”
HIPPOCRATIC App can help health care workers diagnose illness early on, making sure they don’t return to duty too soon and infect those around them.
If left undetected, infectious diseases can spread quickly through a population, endangering Warfighters and their missions, as well as the general population. HIPPOCRATIC App can help diagnose illness sooner, preventing Warfighters from returning to duty too soon and infecting those around them. Our app also detects injuries. For example, if HIPPOCRATIC App senses a large jolt that may indicate a fall, the system begins monitoring for associated symptoms of traumatic brain injury, such as a change in gait, using integrated smartphone sensors.
“We are proud to work with a talented team to build this app,” continued Dr. Bracken. “We’re excited to demonstrate the right way to protect end-user information and privacy when applying advanced analytics. We will protect the privacy of user data using TozStore, an end-to-end encryption toolkit developed by Tozny.”
HIPPOCRATIC App lies at the intersection of multiple expertise areas at Charles River Analytics, including machine learning, human/physiological sensing, decision support tools, and healthcare support and training.
This material is based upon work supported by United States Air Force and DARPA under Contract No. FA8750-18-C-0056. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of United States Air Force and DARPA. Distribution Statement “A” (Approved for Public Release, Distribution Unlimited).