DARPA's 'Biometrics-At-A-Distance' Knows You By Heart

Biometrics-at-a-distance is DARPA's way of picking you out in a crowd - you know, just in case they needed to - from a distance, without your knowledge. The idea is to use sensors to collect biometric identification systems like your identifiable heart beat from further way than is typical in your doctor's office.

OBJECTIVE: Demonstrate the ability to collect, localize, and evaluate physiological signals (e.g., heart rate) at distances greater than 10 meters, non-line-of-sight, and through solid objects (walls, rock, concrete, etc.).

DESCRIPTION: There is a need to remotely detect, collect, and evaluate physiological signals of interest. Applications and concepts-of-operations (CONOPs) that would benefit from this capability include, but are not limited to: building-clearing, warfighter health monitoring or battle damage assessment and triage, situational awareness and assessment. Existing micro-impulse radar (MIR) and ultra-wideband (UWB) technologies have the capability of detecting heartbeat and respiration at distances up to 8 meters (1) but are limited in at greater distances and in challenging environments, such as penetration through thick or multiple walls, concrete, and RF-noisy environments. For example, in a building that has experienced a catastrophic event (fire, earthquake, etc.), the detection of survivors and assessment of their medical condition, in addition to their location to within 1 meter accuracy, would improve the likelihood of recovery of personnel and their survivability. Additionally in a crowded environment it is highly challenging to uniquely identify persons based on collection of physiological signatures, such as electrocardiograms (ECGs). It is possible that high-frequency ECGs or other signals could improve the confidence level in unique identification. Approaches using “on body” sensors that transmit signals to remote locations will NOT be considered.

PHASE I: Demonstrate through simulation and basic proof-of-concept experiment the feasibility of a technology that can record human vital signs at distances greater than 10 meters, using non-line-of-sight and non-invasive or non-contact methods. Should be able to uniquely identify 10 subjects with >95% confidence inside a building or similar structure. Deliverable will be a paper study with detailed physics and link­ margin analysis, and if possible a proof-of-concept experiment. The Technology Readiness Level (TRL) at the end of Phase1 should strive to be 2-3.

PHASE II: Using surrogate signals, demonstrate the capability to detect, localize, and discriminate ten sources of surrogate physiological signals. Assess the limits of the capabilities using physics-based modeling and proof-of-concept experiments to prove your predictions. Compare the captured signal quality to the quality of signals acquired by contact methods. The Technology Readiness Level (TRL) at the end of Phase2 should strive to be 4-5.

PHASE III: Commercial applications for this technology include use by disaster response search and rescue teams, fire and rescue, police and hostage rescue. Military applications include: building-clearing, warfighter health monitoring or battle damage assessment and triage, situational awareness and assessment.

Science fiction fans have been ready for this development for several generations. In his Hugo award-winning 1967 novel Lord of Light, Roger Zelazny describes a robotic snake that can pick up EEG readings from up to a mile away:

...he's dreamed up some other little jewels, too, to serve the will of the gods ... like a mechanical cobra capable of registering encephalogram readings from a mile away, when it rears and spreads its fan. It can pick one man out of a crowd, regardless of the body he wears.
(Read more about Zelazny's mechanical cobra)

A few years earlier, Philip K. Dick described a cephalotropic dart in his 1964 novel Lies, Inc.:

...a more complex analytical device showed the cigarillo to be a homeostatic cephalotropic dart.

"Whose Alpha-wave pattern?" Theodoric Ferry asked Dosker.

"Yours," Dosker said tonelessly.
(Read more about PKD's cephalotropic dart)

From DARPA via Wired.

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Index of related articles:

Automated Biometric Identification System (ABIS)
Automated Fingerprint Identification System (AFIS)
Behavioral Biometric Characteristic
Biological Biometric Characteristic
Biometrics
Biometric Data
Biometrics Algorithm
Biometric Match
Biometric Match Threshold
Biometric Sample
Biometric System
Capture
Common Biometric Exchange File Format (CBEFF)
Challenge Response
Closed-set Identification
Covert Sampling
Feature Extraction
Live Biometric Capture
Liveness Detection
Non-cooperative User
One-to-many
One-to-One
Open-set Identification
Overt Collection
Speaker Recognition
Spoofing
Template
Threshold
True Accept Rate
True Reject Rate
Uncooperative User
Verification

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