Performance evaluation of heart sounds biometric systems on an open dataset

Recently, many systems and approaches that employ heart sounds as physiological traits for biometric recognition have been investigated. However, those systems are often tested on small, diverse and closed datasets, making it difficult to compare their performance. In this paper, we present HSCT-11, an open dataset containing data collected from 206 people that can be used for performance evaluation of heart sounds biometric systems, and we use it to benchmark two such systems. The most performing one shows an Equal Error Rate of 13.66 % on this database, a result that will be the baseline for all the future evaluations made using this dataset.