EEG/ECG signal fusion aimed at biometric recognition


The recognition of individuals based on behavioral and biological characteristics has made important strides over the past few years. Growing interest has been recently devoted to the study of physiological measures, which include the electrical activity of brain (EEG) and heart (ECG). Even if the use of multimodal approaches overcome several limitations of traditional uni-modal biometric systems, the simultaneous use of EEG and ECG characteristics has been scarcely investigated. In this paper, we present a set of preliminary results derived by the investigation of a biometric system based on the fusion of simple features simultaneously extracted from EEG and ECG signals. The reported results show high performance both from uni-modal approach (higher performance being EER = 11.17 and EER = 3.83 for EEG and ECG respectively) and fusion (EER = 2.94). However, caution should be considered in the interpretation of the reported results mainly beacuse the analysis was performed on a limited set of subjects.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Volume 9281, 2015, Pages 35-42 18th International Conference on Image Analysis and Processing, ICIAP 2015 BioFor, CTMR, RHEUMA, ISCA, MADiMa, SBMI, and QoEM; Genoa; Italy; 7 September 2015 through 8 September 2015; Code 141059
Silvio Barra
Silvio Barra
Assistant Professor

Assistant Professor @ University of Naples