14 April 2010 Robust human identification using ecg: eigenpulse revisited
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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.
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Daniel Jang, Daniel Jang, Suzanne Wendelken, Suzanne Wendelken, John M. Irvine, John M. Irvine, } "Robust human identification using ecg: eigenpulse revisited", Proc. SPIE 7667, Biometric Technology for Human Identification VII, 76670M (14 April 2010); doi: 10.1117/12.850619; https://doi.org/10.1117/12.850619
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