基于高斯混合模型的心音信号识别

为了准确区别各种心音信号, 获得更理想的心音识别效果, 提出一种基于高斯混合模型(GMM)的心音信号识别模型. 首先采用小波变换对原始心音信号进行去噪处理, 消除噪声对心音信号特征提取的干扰； 然后对心音信号进行特征提取, 并采用高斯模型构建心音信号分类和识别模型； 最后采用心音信号数据对模型的性能进行验证. 结果表明, 该模型的心音信号平均识别率超过95%, 且心音信号识别结果优于其他模型.

Heart Sound Signal Recognition Based on Gauss Mixture Model

In order to distinguish different kinds of heart sound signals accurately and obtain better recognition effect, we proposed a heart soundsignal recognition model based on Gauss mixture model. Firstly, wavelet transform was used to denoise original heart sound signal, [JP+1]and the interference of noise to feature extraction of heart sound signal was eliminated. Secondly, heart sound signal was extracted while model of classification and recognition of heart
sound signal was constructed by using Gauss model. Finally, the performance of the model was verified by using heart sound signal data. The results show that the average recognition rate of heart sound signal for the proposed model is more than 95%, and recognition result of heart sound signal is superior to other models.