Investigation Performance on Electrocardiogram Signal Processing Based on an Advanced Algorithm Combining Wavelet Packet
The Electrocardiogram (ECG) is essential for the clinical diagnosis of cardiovascular disease. An advanced algorithm combining wavelet packet transformation (WPT) and Hilbert Huang transform (HHT) is presented for processing ECG (Electrocardiography) sign
- PDF / 656,585 Bytes
- 10 Pages / 439.37 x 666.142 pts Page_size
- 49 Downloads / 182 Views
Investigation Performance on Electrocardiogram Signal Processing based on an Advanced Algorithm Combining Wavelet Packet Transform (WPT) and Hilbert-Huang Transform (HHT)* Jin Bo, Xuewen Cao, Yuqing Wan, Yuanyu Yu, Pun Sio Hang, Peng Un Mak and Mang I Vai
Abstract The Electrocardiogram (ECG) is essential for the clinical diagnosis of cardiovascular disease. An advanced algorithm combining wavelet packet transformation (WPT) and Hilbert Huang transform (HHT) is presented for processing ECG (Electrocardiography) signal in this paper. First the WPT can resolve the ECG signal into a group of signals with narrow band. Then, the Empirical Mode Decomposition (EMD) process of Hilbert-Huang Transform (HHT) is applied on the narrow band signals. The unrelated IMFs of ECG signal are removed from result through a screening process. Finally, the Hilbert transform is employed to achieve the Hilbert spectrum and marginal spectrum. The results show the
The work was financially supported by The Science and Technology Development Fund of Macau under Grant 014/2007/A1, Grant 063/2009/A, and Grant 024/2009/A1, the National Natural Science Foundation of China under Grant 61201397 and University of Macau RG069/ 07-08S/MPU/FST. J. Bo (&) X. Cao Y. Yu P. S. Hang P. U. Mak M. IVai Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macau e-mail: [email protected] Y. Wan Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Taipa, Macau P. S. Hang M. IVai State Key Laboratory of Analog and Mixed-Signal VLSI, University of Macau, Taipa, Macau
S. Li et al. (eds.), Frontier and Future Development of Information Technology in Medicine and Education, Lecture Notes in Electrical Engineering 269, DOI: 10.1007/978-94-007-7618-0_94, Springer Science+Business Media Dordrecht 2014
959
960
J. Bo et al.
effective performance of the algorithm combining WPT and HHT in reducing ECG noise and time–frequency analysis. By comparing with the original HHT, the proposed algorithm has the better performance on ECG signal processing. Keywords ECG
WPT EMD HHT
94.1 Introduction The Electrocardiogram (ECG) is a typical case of biomedical signal and can interpret the electrical activities over a period of time. The Electrocardiogram (ECG) detected and recorded by surface electrodes is essential for the clinical diagnosis of cardiovascular disease. Time series data sampled from biomedical signals are often considered linear and stationary arising from physical processes. But biomedical signals are considered nonlinear and nonstationary when signals are related to dynamic biological system. Due to nonlinear and nonstationary property of ECG signals, an adaptive processing method is required. Time–frequency analysis is to describe a signal energy density in time and frequency domains simultaneously [1]. There are several common time–frequency analytic techniques such as Gabor-Wigner Transform, Wigner Distribution Function (WDF), S
Data Loading...
