Fetal Heart Rate Deceleration Detection Using a Discrete Cosine Transform Implementation of Singular Spectrum Analysis

P. A. Warrick; D. Precup; E. F. Hamilton; R. E. Kearney

doi:10.1055/s-0038-1625406

Methods of Information in Medicine, Table of Contents

Methods Inf Med 2007; 46(02): 196-201
DOI: 10.1055/s-0038-1625406

Original Article

Schattauer GmbH

Fetal Heart Rate Deceleration Detection Using a Discrete Cosine Transform Implementation of Singular Spectrum Analysis

P. A. Warrick

¹Biomedical Engineering Department, McGill University, Montréal, Québec, Canada

⁴LMS Medical Systems, Inc., Montréal, Québec, Canada

,

D. Precup

²School of Computer Science, McGill University, Montréal, Québec, Canada

,

E. F. Hamilton

³Department of Obstetrics and Gynecology, McGill University, Montréal, Québec, Canada

⁴LMS Medical Systems, Inc., Montréal, Québec, Canada

,

R. E. Kearney

¹Biomedical Engineering Department, McGill University, Montréal, Québec, Canada

› Author Affiliations

Abstract

Summary

Objectives : To develop a singular-spectrum analysis (SSA) based change-point detection algorithm applicable to fetal heart rate (FHR) monitoring to improve the detection of deceleration events.

Methods : We present a method for decomposing a signal into near-orthogonal components via the discrete cosine transform (DCT) and apply this in a novel online manner to change-point detection based on SSA. The SSA technique forms models of the underlying signal that can be compared over time; models that are sufficiently different indicate signal change points. To adapt the algorithm to deceleration detection where many successive similar change events can occur, we modify the standard SSA algorithm to hold the reference model constant under such conditions, an approach that we term “base-hold SSA”. The algorithm is applied to a database of 15 FHR tracings that have been preprocessed to locate candidate decelerations and is compared to the markings of an expert obstetrician.

Results : Of the 528 true and 1285 false decelerations presented to the algorithm, the base-hold approach improved on standard SSA, reducing the number of missed decelerations from 64 to 49 (21.9%) while maintaining the same reduction in false-positives (278).

Conclusions : The standard SSA assumption that changes are infrequent does not apply to FHR analysis where decelerations can occur successively and in close proximity; our base-hold SSA modification improves detection of these types of event series.

Keywords

Signal processing - computer-assisted models - statistical decision support techniques - fetal heart rate - obstetrics

Full Text

References

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