NDLI: Abnormal ECG signal detection based on compressed sampling in Wearable ECG sensor

Content Provider	IEEE Xplore Digital Library
Author	Hao Ding Hong Sun Kun-mean Hou
Copyright Year	2011
Description	Author affiliation: LIMOS Laboratory UMR 6158 CNRS, University of Blaise Pascal, Clermont-Ferrand II, France (Kun-mean Hou) \|\| School of Electronic Information, Wuhan University, Wuhan, China (Hao Ding; Hong Sun)
Abstract	Nowadays to diagnose cardiac arrhythmias Holter device is used to record 1 or 2 ECG leads during 24 or 48h. Power consumption limitations determine that the amount of data needs to be diminished without damaging the quality of information. To get a solution, we introduce a novel method based on Compressed Sensing (CS) technique to the Wearable ECG sensor (WES). The main principle underlying this framework is to sample analog signals at sub-Nyquist rate at the analog-digital converters (ADCs) and to classify directly compressed measurement into normal and abnormal state. Those compressed measurements which imply a risk of cardiac anomaly will be stored in a multimedia flash memory card or be transferred to the terminal of the network for a cardiologist to make an off-line diagnosis of cardiac arrhythmias using the reconstructed signals from the compressed measurements. In this paper we propose a scheme to directly classify compressed ECG samples into normal or abnormal states, thus avoiding reconstruction of the entire signal to perform this task. Our algorithm takes advantage of estimating parameters directly from the compressed measurements; thereby eliminating the reconstruct stage and reducing the computational complexity in WES. Direct cardiac arrhythmia detection based on CS reduces 34% energy consumption and 90% storage in WES for the reconstructed performance of 41dB.
Starting Page	1
Ending Page	5
File Size	649032
Page Count	5
File Format	PDF
ISBN	9781457710094
e-ISBN	9781457710100
e-ISBN	9781457710087
DOI	10.1109/WCSP.2011.6096677
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-11-09
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Heart rate Cardiac arrhythmia Electrocardiography (ECG) Energy measurement System on Chip (SoC) Electrocardiography Compressed Sensing (CS) Wearable ECG sensor Compressed sensing Wavelet coefficients
Content Type	Text
Resource Type	Article

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