Behavior Mining: your smartphone knows you better

Currently, understanding and assessing the readiness of the warfighter is complex, intrusive, done relatively infrequently, and relies heavily on self-reporting. Readiness is determined through medical intervention with the help of advanced equipment, such as electrocardiographs (EKGs) and otherspecialized medical devices that are too expensive and cumbersome to employ continuously without supervision in non-controlled environments. On the other hand, currently 92% of adults in the United States own a cell phone, which could be used as the basis for continuous, passive health and readiness assessment.  The WASH program will use data collected from cellphone sensors to enable novel algorithms that conduct passive, continuous, real-time assessment of the warfighter.

DARPA’s WASH [Warfighter Analytics using Smartphones for Health] will extract physiological signals, which may be weak and noisy, that are embedded in the data obtained through existing mobile device sensors (e.g., accelerometer, screen, microphone). Such extraction and analysis, done on a continuous basis, will be used to determine current health status and identify latent or developing health disorders. WASH will develop algorithms and techniques for identifying both known indicators of physiological problems (such as disease, illness, and/or injury) and deviations from the warfighter’s micro-behaviors that could indicate such problems.

Excerpt from Warfighter Analytics using Smartphones for Health (WASH)
Solicitation Number: DARPA-SN-17-4, May, 2, 2018

See also Modeling and discovering human behavior from smartphone sensing life-log data for identification purpose

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