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Proceedings Paper

Robust human identification using ecg: eigenpulse revisited
Author(s): Daniel Jang; Suzanne Wendelken; John M. Irvine
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Paper Abstract

Biometrics, such as fingerprint, iris scan, and face recognition, offer methods for identifying individuals based on a unique physiological measurement. Recent studies indicate that a person's electrocardiogram (ECG) may also provide a unique biometric signature. Several methods for processing ECG data have appeared in the literature and most approaches rest on an initial detection and segmentation of the heartbeats. Various sources of noise, such as sensor noise, poor sensor placement, or muscle movements, can degrade the ECG signal and introduce errors into the heartbeat segmentation. This paper presents a screening technique for assessing the quality of each segmented heartbeat. Using this technique, a higher quality signal can be extracted to support the identification task. We demonstrate the benefits of this quality screening using a principal component technique known as eigenpulse. The analysis demonstrated the improvement in performance attributable to the quality screening.

Paper Details

Date Published: 14 April 2010
PDF: 12 pages
Proc. SPIE 7667, Biometric Technology for Human Identification VII, 76670M (14 April 2010); doi: 10.1117/12.850619
Show Author Affiliations
Daniel Jang, Scitor Corp. (United States)
Suzanne Wendelken, The Charles Stark Draper Lab., Inc. (United States)
John M. Irvine, The Charles Stark Draper Lab., Inc. (United States)


Published in SPIE Proceedings Vol. 7667:
Biometric Technology for Human Identification VII
B. V. K. Vijaya Kumar; Salil Prabhakar; Arun A. Ross, Editor(s)

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