Efficient Extraction and Reconstruction of Foetal Electrocardiogram By Block Sparse Bayesian Learning |
Author(s): |
| S. Y. Pattar , BMSCE, Bangalore; Akbar Ahamad, BMSCE |
Keywords: |
| Electroencephalogram (EEG), Sparsity, Centering, Whitening, Bandpass Filtering, Reconstruction, Kurtosis, Negentrophy General terms: Foetal Electrocardiogram (FECG), Telemedicine, Independent Component Analysis (ICA), Block Sparse Bayesian Learning (BSBL), Compressed Sensing (CS) |
Abstract |
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Tele-monitoring of foetal ECG (FECG) is very important in Telemedicine. DesigningTele-monitoring system with low energy consumption is a major challenge. Compressing or Reconstructing FECG which is a non-sparse signal with strong noise contamination is not an easy task. Majority of times Compressed Sensing (CS) techniques fails to compress/reconstruct FECG so there exists a strong need for other advanced techniques, we propose Block Sparse Bayesian Learning(BSBL) which can reconstruct FECG by exploiting its Sparsity. |
Other Details |
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Paper ID: IJSRDV3I70079 Published in: Volume : 3, Issue : 7 Publication Date: 01/10/2015 Page(s): 291-293 |
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