Self-organizing maps
Large-Scale Evaluation of Multimodal Biometric Authentication Using State-of-the-Art Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition
An introduction to biometric recognition
IEEE Transactions on Circuits and Systems for Video Technology
Human identity verification based on Mel frequency analysis of digital heart sounds
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
Fighting coercion attacks in key generation using skin conductance
USENIX Security'10 Proceedings of the 19th USENIX conference on Security
Enhancing the privacy of electronic passports
International Journal of Information Technology and Management
Quality-driven wavelet based PCG signal coding for wireless cardiac patient monitoring
Proceedings of the 1st International Conference on Wireless Technologies for Humanitarian Relief
Gait verification using knee acceleration signals
Expert Systems with Applications: An International Journal
Optimum heart sound signal selection based on the cyclostationary property
Computers in Biology and Medicine
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In this paper, we propose a novel biometric method based on heart sound signals. The biometric system comprises an electronic stethoscope, a computer equipped with a sound card and the software application. Our approach consists of a robust feature extraction scheme which is based on cepstral analysis with a specified configuration, combined with Gaussian mixture modeling. Experiments have been conducted to determine the relationship between various parameters in our proposed scheme. It has been demonstrated that heart sounds should be processed within segments of 0.5s and using the full resolution in frequency domain. Also, higher order cepstral coefficients that carry information on the excitation proved to be useful. A preliminary test of 128 heart sounds from 128 participants was collected to evaluate the uniqueness of the heart sounds. The HTK toolkit produces a 99% recognition rate with only one mismatch. Next, a more comprehensive test consisting almost 1000 heart sounds collected from 10 individuals over a period of 2 months yields a promising matching accuracy of 96% using the proposed feature and classification algorithm. A real-time heart sound authentication system is then built and can be used in two modes: to identify a particular individual or to verify an individual's claimed identity.