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Abstract [en]
In this paper a new approach in human identification is investigated, For this purpose, a standard 12-lead electrocardiogram (ECG) recorded during rest is used. Selected features extracted from the ECG are used to identify a person in a predetermined group. Multivariate analysis is used for the identification task. Experiments show that it is possible to identify a person by features extracted from one lead only. Hence, only three electrodes have to be attached on the person to be identified. This makes the method applicable without too much effort.
Keywords
data fusion, electrocardiogram (ECG), feature extraction, human identification, multivariate analysis
National Category
Computer Sciences
Research subject
Computer and Systems Science
Identifiers
urn:nbn:se:oru:diva-16067 (URN)000169439600022 ()
2011-06-222011-06-222018-01-12Bibliographically approved