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Detection of body position changes from the ECG using a Laplacian noise model

Författare

Summary, in English

Body position changes (BPCs) are manifested as shifts in the electrical axis of the heart, which may lead to ST changes in the ECG, misclassified as ischemic events. This paper presents a novel BPC detector based on a Laplacian noise model. It is assumed that a BPC can be modelled as a step-like change in the two coefficient series that result from the Karhunen-Loeve transform of the QRS complex and the ST-T segment. The generalized likelihood ratio test is explored for detection, where the statistical parameters of the Laplacian model are subject to estimation. Two databases are studied: one for assessing detection performance in healthy subjects who perform BPCs, and another for assessing the false alarm rate in ECGs recorded during percutaneous transluminal coronary angiography. The resulting probability of detection (P-D) and probability of false alarm (P-F) are 0.94 and 0.00, respectively, whereas the false alarm rate in ischemic recordings is 1 event/h. The proposed detector outperforms an existing detector based on the Gaussian noise model which achieved a P-D/P-F of 0.90/0.01 and a false alarm rate of 2 events/h. Analysis of the log-likelihood function for the Gaussian and Laplacian noise models show that latter model is more adequate. (C) 2014 Published by Elsevier Ltd.

Publiceringsår

2014

Språk

Engelska

Sidor

189-196

Publikation/Tidskrift/Serie

Biomedical Signal Processing and Control

Volym

14

Dokumenttyp

Artikel i tidskrift

Förlag

Elsevier

Ämne

  • Medical Engineering

Nyckelord

  • Postural changes
  • Laplacian noise
  • Detection theory
  • Ischemia detection

Status

Published

ISBN/ISSN/Övrigt

  • ISSN: 1746-8094