Na Pan
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Na Pan has a total of 3 co-authors. Here are the top co-authors by number of shared publications:
- Mang I. Vai
University of Macau
1 shared publication - Peng Un Mak
Department of Electrical and Computer Engineering, University of Macau, Macau 999078, China
1 shared publication - Siohang Pun
State Key Laboratory of Analog and Mixed-Signal VLSI, University of Macau, Macau, Macau SAR, China
1 shared publication
Latest Publications
- 1 October 2007
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 177-180
Accurate Removal of Baseline Wander in ECG Using Empirical Mode Decomposition
The removal of baseline wander (BW) is a very important step in the pre-processing stage of electrocardiogram (ECG). Thus, a method for accurate removing the baseline wander (BW) in ECG on the basis of empirical mode decomposition (EMD) is proposed in this paper. We briefly described the principles and characteristics of the EMD in Section II. To validate the proposed method, the recording from MIT/BIH database is used. In this paper, the traditional median filter is also applied to remove BW in ECG for comparison with our EMD method. Our experimental results show that the performance of EMD method is very good and accurate in removing BW in ECG.
- 1 October 2007
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 177-180
Accurate Removal of Baseline Wander in ECG Using Empirical Mode Decomposition
The removal of baseline wander (BW) is a very important step in the pre-processing stage of electrocardiogram (ECG). Thus, a method for accurate removing the baseline wander (BW) in ECG on the basis of empirical mode decomposition (EMD) is proposed in this paper. We briefly described the principles and characteristics of the EMD in Section II. To validate the proposed method, the recording from MIT/BIH database is used. In this paper, the traditional median filter is also applied to remove BW in ECG for comparison with our EMD method. Our experimental results show that the performance of EMD method is very good and accurate in removing BW in ECG.