Biometric Authentication Using Noisy Electrocardiograms Acquired by Mobile Sensors

• Published in: IEEE access Vol. 4; pp. 1266 - 1273
• Main Authors: Choi, Hyun-Soo, Lee, Byunghan, Yoon, Sungroh
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Authentication; Band-pass filters; Bandpass filters; Biomedical signal processing; Biometric; Biometrics; BMD101; CardioChip; Electrocardiogram; Electrocardiography; Noise cancellation; Radial basis function; Sensors; Signal quality; Support vector machines; Testing time; Wearable technology; Wireless sensor networks; Biometric; electrocardiogram; BMD101; CardioChip; authentication
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2016.2548519

Electrocardiogram (ECG) signals from mobile sensors are expected to increase the availability of authentication in the emerging wearable device industry. However, mobile sensors provide a relatively lower quality signal than the conventional medical devices. This paper proposes a practical authentication procedure for ECG signals that collected via one-chip-solution mobile sensors. We designed a cascading bandpass filter for noise cancellation and suggest eight fiducial features. For classification-based authentication, we use the radial basis function kernel-based support vector machine showing the best performance among nine classifiers through experimental comparisons. In spite of noisy ECG signals in mobile sensors, we achieved 4.61% of the equal error rate (EER) on a single heartbeat, and 1.87% of EER on 15 s testing time on 175 subjects, which is a reasonable result and supports the usability of low-cost ECGs for biometric authentication.