Block-Sparsity Based Compressed Sensing for Multichannel ECG Reconstruction
Multichannel electrocardiogram (MECG) provides significant information for the detection of cardiovascular diseases. Compressed sensing (CS) is a simultaneous sensing and reconstruction technique from a few compressed measurements with low level of distortion. CS promises to lower energy consumption of sensing nodes for wireless body area network (WBAN) in continuous ECG monitoring. In this paper, we propose an energy efficient novel block-sparsity based compressed sensing for MECG reconstruction which exploits both spatial and temporal correlations in the wavelet domain effectively. Experimental results show that the proposed method achieve MECG data compression and reconstruction better than others.
KeywordsMultichannel ECG Compressed Sensing Block-sparsity Wireless Body Area Network Energy efficient sensing
Authors would like to thank “Visvesvaraya PhD Scheme for Electronics and IT” (Grant No. MLA/MUM/GA/10(37)B dt. 15/01/2018), Ministry of Electronics and Information Technology (MeitY), Government of India for providing financial support to setup necessary infrastructure besides contingency funds for carrying out this research.
- 5.Mamaghanian, H., Ansaloni, G., Atienza, D., Vandergheynst, P.: Power-efficient joint compressed sensing of multi-lead ECG signals. In: 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4409–4412, May 2014Google Scholar
- 8.Polania, L.F., Carrillo, R.E., Blanco-Velasco, M., Barner, K.E.: Compressed sensing based method for ECG compression. In: 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 761–764, May 2011Google Scholar
- 13.Surawicz, B., Knilans, T.: Chous Electrocardiography in Clinical Practice, 6th edn. Elsevier, Philadelphia (2008)Google Scholar