A Human Identification System based on Heart Sounds and Gaussian Mixture Models

摘要：

In this paper, we propose a novel biometric method based on the Heart sounds and the Gaussian Mixture Model (GMM). Heart sounds are trained by GMM to build an identification system. The MFCC Feature extraction algorithm is studied and GMM model is built. The optimal parameters are achieved by varying experimental parameters. The system has an accurate recognition rate up to 100％ under the experimental conditions. The results show that the system based on GMM has a better performance than the system based on Vector Quantization (VQ).

关键词： Biometric Heart sounds Mel Frequency Cepstrum Coefficient (MFCC) Gaussian Mixture Model (GMM)

作者: Zhidong Zhao Qinqin Shen

作者单位: College of Electronics and Information Hang Zhou DianZi University Hangzhou, China College of Communication Engineering Hang Zhou DianZi University Hangzhou, China

会议类型: 国际会议

会议名称: 2011 4th International Conference on Biomedical Engineering and Informatics(第四届生物医学工程与信息学国际会议 BMEI 2011)

会议地点: 上海

会议语种:英文

页码: 595-599

在线出版日期: 2011-10-15（万方平台首次上网日期，不代表论文的发表时间）