@article{
 title = {A novel biometric authentication approach using electrocardiogram signals},
 type = {article},
 year = {2013},
 identifiers = {[object Object]},
 pages = {4259-4262},
 id = {6672cef2-1893-33b5-8750-7f8c711b1d5e},
 created = {2015-04-30T11:14:04.000Z},
 file_attached = {true},
 profile_id = {5e73f9af-1f10-3a70-a285-d3fbb699efe2},
 group_id = {e134fb94-8118-3ebe-b82d-bfbf0a8ae633},
 last_modified = {2015-04-30T11:46:48.000Z},
 read = {false},
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 abstract = {In this work, we present a novel biometric authentication approach based on combination of AC/DCT features, MFCC features, and QRS beat information of the ECG signals. The proposed approach is tested on a subset of 30 subjects selected from the PTB database. This subset consists of 13 healthy and 17 non-healthy subjects who have two ECG records. The proposed biometric authentication approach achieves average frame recognition rate of %97.31 on the selected subset. Our experimental results imply that the frame recognition rate of the proposed authentication approach is better than that of ACDCT and MFCC based biometric authentication systems, individually.},
 bibtype = {article},
 author = {Gurkan, Hakan and Guz, Umit and Yarman, B. S.},
 journal = {Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS}
}

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