ECG slope features for Biometric Authentication

Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/20703

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DC Field	Value	Language
dc.contributor.author	Safie S.I	-
dc.contributor.author	(UniKL MITEC)	-
dc.date.accessioned	2018-12-26T07:53:59Z	-
dc.date.available	2018-12-26T07:53:59Z	-
dc.date.issued	2018-12-26	-
dc.identifier.uri	http://ir.unikl.edu.my/jspui/handle/123456789/20703	-
dc.description.abstract	This paper presents a new feature extraction technique, based on the slope of Electrocardiograms (ECG), for biometric authentication. An algorithm has been developed based on the concept of amplitude comparison between a triangle wave and the ECG signal. The proposed algorithm performance has been evaluated by comparing the Receiver Operating Characteristic (ROC) curve for various triangular wave settings. 1000 ECGs recorded from 100 students have been used in this work. Different techniques in producing triangular waves to extract the ECG features have been presented in this paper. It is shows in this paper that the authentication performance increases 50% when the features are extracted separately from the peaks of P to R and from the peaks of R to T.	en_US
dc.subject	Electrocardiogram slope	en_US
dc.subject	Biometric authentication	en_US
dc.subject	Receiver Operating Characteristic	en_US
dc.title	ECG slope features for Biometric Authentication	en_US
dc.conference.name	2018 IEEE 5th International Conference on Smart Instrumentation, Measurement and Application (ICSIMA 2018)	en_US
dc.conference.year	2018	en_US
Appears in Collections:	Conference Paper

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