ECG to identify individuals

Authors:
Steven A. Israel;John M. Irvine;Andrew Cheng;Mark D. Wiederhold;Brenda K. Wiederhold
Affiliations:
SAIC, 4001 Fairfax Drive, Suite 450, Arlington, VA 22203, USA;SAIC, 20 Burlington Mall Road, Burlington, MA 01803, USA;SAIC, 20 Burlington Mall Road, Burlington, MA 01803, USA;SAIC, 10260 Campus Point Drive, San Diego, CA 92121, USA;Virtual Reality Medical Center, 6160 Cornerstone Drive, San Diego, CA 92121, USA
Venue:
Pattern Recognition
Year:
2005

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Abstract

The electrocardiogram (ECG also called EKG) trace expresses cardiac features that are unique to an individual. The ECG processing followed a logical series of experiments with quantifiable metrics. Data filters were designed based upon the observed noise sources. Fiducial points were identified on the filtered data and extracted digitally for each heartbeat. From the fiducial points, stable features were computed that characterize the uniqueness of an individual. The tests show that the extracted features are independent of sensor location, invariant to the individual's state of anxiety, and unique to an individual.