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A Study into the Feasibility of Biometric Identification Through ECG

Abstract

This research proposes the idea that an electrocardiogram (ECG) is unique

among individuals. A group of 84 individuals was considered and classified using

two classification techniques, Linear Discriminant Analysis and a Feed Forward

Neural Network. These classifiers are used to identify uniqueness in an individual’s

ECG in both the time and frequency domain. This research found that we can

classify this set of data with a 93% accuracy.

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