Sparse sensing matrix based compressed sensing in low-power ECG sensor nodes

Marchioni, A.; Mangia, M.; Pareschi, F.; Rovatti, R.; Setti, G.

doi:10.1109/BIOCAS.2017.8325155

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Compressed Sensing (CS) is an acquisition technique able to reduce the operating cost (e.g., energy requirements) of a signal processing system thanks to its capability of simultaneously sampling and compressing an input waveform. Here we focus on Electrocardiogram (ECG) signals acquired by means of a custom designed acquisition board that exploits CS as early-digital compression stage. We show that when CS acquisition sequences are sparse ternary, i.e., with symbols {-1, 0, +1} and designed to maximize their rakeness, it is possible to achieve a reduction in the energy required for ECG signal compression by a factor between 25 and 30 with respect to the standard acquisition with independent and identically distributed random sequences.

Titolo:	Sparse sensing matrix based compressed sensing in low-power ECG sensor nodes
Autori:	Marchioni A. Mangia M. PARESCHI, FABIO Rovatti R. SETTI, GIANLUCA mostra contributor esterni nascondi contributor esterni
Data di pubblicazione:	2017
Abstract:	Compressed Sensing (CS) is an acquisition technique able to reduce the operating cost (e.g., ener...gy requirements) of a signal processing system thanks to its capability of simultaneously sampling and compressing an input waveform. Here we focus on Electrocardiogram (ECG) signals acquired by means of a custom designed acquisition board that exploits CS as early-digital compression stage. We show that when CS acquisition sequences are sparse ternary, i.e., with symbols {-1, 0, +1} and designed to maximize their rakeness, it is possible to achieve a reduction in the energy required for ECG signal compression by a factor between 25 and 30 with respect to the standard acquisition with independent and identically distributed random sequences.
ISBN:	978-1-5090-5803-7
Appare nelle tipologie:	4.1 Contributo in Atti di convegno

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