Name
Abstract | ||
|---|---|---|
Physiological measures are widely studied from a medical point of view. Most applications lie in the field of diagnosis of heart attacks, as regards the ECG, or the detection of epileptic events, in the case of the EEG. In the last ten years, these signals are being investigated also from a biometric point of view, in order to exploit the discriminative capability provided by these measures in recognizing individuals. The present work proposes a multimodal biometric recognition system based on the fusion of the first lead (i) of the electrocardiogram (ECG) with six different bands of the electroencephalogram (EEG). The proposed approach is based on the extraction of fiducial features (peaks) from the ECG combined with spectrum features of the EEG. A dataset has been created, by composing the signals of two well-known databases. The results, reported by means of EER values, AUC values and ROC curves, show good recognition performances. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/s11042-016-3796-1 | Multimedia Tools Appl. |
Keywords | Field | DocType |
EEG signal,ECG signal,Biometric,Multimodal system,Physiological measures | Receiver operating characteristic,Computer science,Software,Artificial intelligence,Discriminative model,Electroencephalography,Computer vision,Fiducial marker,Recognition system,Pattern recognition,Speech recognition,Exploit,Biometrics | Journal |
Volume | Issue | ISSN |
76 | 4 | 1380-7501 |
Citations | PageRank | References |
7 | 0.52 | 15 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Silvio Barra | 1 | 62 | 11.59 |
| Andrea Casanova | 2 | 40 | 5.58 |
| Matteo Fraschini | 3 | 48 | 8.40 |
| M. Nappi | 4 | 947 | 85.18 |