Paper Info
Title
Quantifying the benefits of compressed sensing on a WBSN-based real-time biosignal monitor.
Abstract
Technology scaling enables today the design of ultra-low power wearable biosensors for continuous vital signal monitoring or wellness applications. Wireless Body Sensor Networks (WBSN) integrate wearable sensing nodes for an accurate measurement of the desired physiological parameter, e.g. Electrocardiogram (ECG), and a personal gateway for the collection and processing of the data. The diffusion of smartphones enables their use as advanced personal gateways, with the ability to provide user interaction features, connectivity and real-time feedback to the user. Both the sensing node(s) and the smartphone are battery powered and resource-constrained devices, hence energy efficiency is one of the key design goals. In this work, we explore the use of compression techniques to improve the efficiency of a wireless ECG wearable monitor. In the presented system, the wearable node is used for bio-signal acquisition, pre-processing and compression, while a smartphone is used for real-time signal reconstruction. The system aims at medical-grade signal quality and the impact of lossy compression is tested on real signals acquired by the node and its effects are evaluated on systemlevel energy consumption. We analyze performance/energy tradeoffs considering online data compression on the wearable device and real-time reconstruction on the smartphone. Our results show that Compressed Sensing pays off only when the SNR requirement is below 20 dB due to the non-ideal sparsity of ECG signal. We propose a hybrid compression scheme based on CS and under-quantization to address these limitations.
Year
Venue
Keywords
2016
DATE
biomedical telemetry,biosensors,body sensor networks,compressed sensing,data compression,electrocardiography,medical signal processing,patient monitoring,signal reconstruction,smart phones,telemedicine,SNR requirement,WBSN-based real-time biosignal monitor,advanced personal gateways,battery powered devices,biosignal acquisition,compressed sensing,compression techniques,continuous vital signal monitoring,data collection,data processing,electrocardiogram,energy efficiency,hybrid compression scheme,lossy compression,medical-grade signal quality,nonideal sparsity,online data compression,performance-energy tradeoffs,personal gateway,physiological parameter,real-time feedback,real-time signal reconstruction,resource-constrained devices,smartphones,system-level energy consumption,ultralow power wearable biosensors,user interaction features,wearable sensing nodes,wellness applications,wireless ECG wearable monitor,wireless body sensor networks
Field
DocType
ISSN
Lossy compression,Wearable computer,Efficient energy use,Computer science,Real-time computing,Data compression,Biosignal,Wireless sensor network,Compressed sensing,Signal reconstruction
Conference
1530-1591
Citations 
PageRank 
References 
2
0.36
13
Authors
5
Name
Order
Citations
PageRank
Daniele Bortolotti1757.13
Bojan Milosevic2777.37
Andrea Bartolini345751.90
Elisabetta Farella443350.45
Luca Benini5131161188.49