Improving Joint Recovery Of Multi-channel ECG Signals In Compressed Sensing-based Telemonitoring Systems Through Multiscale Weighting | 60196
Journal of Clinical & Experimental Pathology
Like us on:
Our Group organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.
Computational complexity and power consumption are prominent issues in wireless telemonitoring applications involving
physiological signals. Compressed sensing (CS) has emerged as a promising framework to address these challenges
because of its energy-efficient data reduction procedure. In this work, a CS-based approach is studied for joint compression/
reconstruction of multichannel electrocardiogram (MECG) signals. Weighted mixed-norm minimization (WMNM)-based
joint sparse recovery algorithm is proposed, which can successfully recover the signals from all the channels simultaneously
by exploiting the inter-channel correlations. The proposed algorithm is based on a multi-scale weighting approach, which
utilizes multi-scale signal information. Under this strategy, weights are designed based on the diagnostic information contents
of each wavelet sub-band/scale. Such a weighting approach emphasizes wavelet sub-bands having high diagnostic importance
during joint CS reconstruction. Coefficients in non-diagnostic sub-bands are deemphasized simultaneously, resulting in a
sparser solution. The proposed method helps achieve superior reconstruction quality with a lower number of measurements.
Reduction in the required number of measurements directly translates into higher compression efficiency, resulting in low
energy consumption in CS-based remote ECG monitoring systems.
Anurag Singh is currently a PhD Research Scholar in the Department of Electronics and Electrical Engineering, IIT Guwahati, India. He has received his BTech (2009) from IET Rohilkhand University, Bareilly and MTech (Dec 2011) from Indian Institute of Information Technology, Design & Manufacturing Jabalpur in Electronics and Communication Engineering. His research interests include biomedical signal processing, multirate signal processing, compressed sensing and sparse representation.