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A Study into the Feasibility of Biometric Identification Through ECG
- Cordes, Kyle
- Advisor(s): Guthaus, Matthew
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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