Fetal ECG Extraction Based on Different Kernel Functions of SVM

摘要：

In this paper, we have applied the support vector machine (SVM) in the fetal ECG extraction. The fetal ECG is obtained by subtracting the estimated maternal ECG from the abdominal signal. We evaluate the performance of three types of kernel function in the SVM: linear kernel, polynomial kernel and KBF kernel. The visual quality of the extracted fetal ECG shows that linear kernel fails to suppress the maternal component completely. The RBF kernel achieves a better extent than polynomial kernel but takes longer time to complete the calculation. Also, the polynomial method is implemented much conveniently as it contains less parameter than the RBF method.

关键词： support vector machine SVM kernel function fetal ECG extraction

作者: Zining Ding Feng Wang Ping Zhou

作者单位: School of Biological Science & Medical Engineering Southeast University Nanjing,China

会议类型: 国际会议

会议名称: 2011 3rd IEEE International Conference on Computer Research and Development(ICCRD 2011)(2011第三届计算机研究与发展国际会议)

会议地点: 上海

会议语种:英文

页码: 205-208

在线出版日期: 2011-03-11（万方平台首次上网日期，不代表论文的发表时间）