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ECG Quality Assessment Based on Image Processing Techniques

[+] Author Affiliations
Henian Xia, Xiaopeng Zhao, Hairong Qi

The University of Tennessee, Knoxville, TN

Paper No. DSCC2012-MOVIC2012-8591, pp. 553-560; 8 pages
doi:10.1115/DSCC2012-MOVIC2012-8591
From:
  • ASME 2012 5th Annual Dynamic Systems and Control Conference joint with the JSME 2012 11th Motion and Vibration Conference
  • Volume 1: Adaptive Control; Advanced Vehicle Propulsion Systems; Aerospace Systems; Autonomous Systems; Battery Modeling; Biochemical Systems; Control Over Networks; Control Systems Design; Cooperative and Decentralized Control; Dynamic System Modeling; Dynamical Modeling and Diagnostics in Biomedical Systems; Dynamics and Control in Medicine and Biology; Estimation and Fault Detection; Estimation and Fault Detection for Vehicle Applications; Fluid Power Systems; Human Assistive Systems and Wearable Robots; Human-in-the-Loop Systems; Intelligent Transportation Systems; Learning Control
  • Fort Lauderdale, Florida, USA, October 17–19, 2012
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-4529-5
  • Copyright © 2012 by ASME

abstract

This work is motivated by the Physionet/Computing in Cardiology Challenge 2011, “Improving the quality of ECGs collected using mobile phones”. The advancement of cell phone technology makes it possible to collect, analyze, and transmit vital physiological signals in real time, promising to a new era of tele-health care. However, noises and artifacts can lead to false readings and thus misdiagnosis. Unlike common methods based on time series analysis techniques, we analyze the quality of the 12-lead ECG using image processing techniques. Various image patterns are used as features to distinguish between low- and high-quality signals. When tested on a data set from the Physionet Challenge 2011, the analyses yield up to 94.36% accuracy. The work here provides an interesting alternative for ECG quality evaluation. The technique will have particular use for ECGs scanned from paper recordings.

Copyright © 2012 by ASME

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