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A piecewise geometric analysis method for real-time ambulatory ECG detection

Issue title: Papers from the 3rd International Conference on Biomedical Engineering and Technology (iCBEB 2014), 25–28 September 2014, Beijing, China

Subtitle:

Guest editors: Edward J. Ciaccio

Article type: Research Article

Authors: Zhou, H.-Y.a; b | Li, J.a; b; * | Zuo, D.-C.b | Hou, K.-M.c | Vaulx, C. dec

Affiliations: [a] School of Electrical and Information Engineering, HuBei University of Automotive Technology, Shiyan, HuBei, China | [b] School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang, China | [c] LIMOS Laboratory CNRS UMR, University of Blaise Pascal, Clermont-Ferrand, France

Correspondence: [*] Corresponding author: Jian Li, School of Electrical and Information Engineering, HuBei University of Automotive Technology, N.167, CheCheng West Road, Shiyan, HuBei 442002, China. Tel.: +86 719 823 8200; Fax: +86 719 8239071; E-mail:lijian@ftcl.hit.edu.cn

Keywords: Ubiquitous cardiac care, ambulatory ECG, piecewise geometric analysis, QRS complex detection

DOI: 10.3233/THC-150970

Journal: Technology and Health Care, vol. 23, no. s2, pp. S335-S342, 2015

Published: 2015
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Abstract

BACKGROUND: As one of the pervasive healthcare services, Ubiquitous cardiac care (UCC) systems should have at least two significant characteristics: real-time detection capability for cardiac arrhythmia events and a small resource requirement for its computation and storage.

PURPOSE: Due to the strict-constrained system support and ambulatory signal quality in the out-of-hospital pervasive healthcare applications, a dedicated real-time AED (Ambulatory Electrocardiograph Detection) algorithm has been implemented.

METHODOLOGY: By adopting the piecewise geometric analysis method, this algorithm can provide a real-time continuous detection capability for QRS complexes, which consists of three main functional modules: the Data preparation; the R-wave vertex discovery; and the QRS complex recognition. Currently, this algorithm has been applied on an on-line UCC application system at the hospital for more than 30 patients.

RESULT: The performance evaluation has been made not only on the standard MIT-BIH cardiac arrhythmia database but also on the clinical testing. The experiential results explore this algorithm has in average sensitivity of 99.37% and specificity of 99.72%.

CONCLUSION: This AED algorithm has minimal beat detection latency and a less computation consumption, which make it meet the requirements of ubiquitous cardiac care applications.

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