Paper
30 May 2001 Using statistical distances to detect changes in the normal behavior of ECG-Holter signals
Julio Cesar Bastos de Figueiredo, Sergio Shiguemi Furuie
Author Affiliations +
Abstract
One of the main problems in the study of complex systems is to define a good metric that can distinguish between different dynamical behaviors in a nonlinear system. In this work we describe a method to detect different types of behaviors in a long term ECG-Holter using short portions of the Holter signal. This method is based on the calculation of the statistical distance between two distributions in a phase-space of a dynamical system. A short portion of an ECG-Holter signal with normal behavior is used to reconstruct the trajectory of an attractor in low dimensional phase-space. The points in this trajectory are interpreted as statistical distributions in the phase-space and assumed to represent the normal dynamical behavior of the ECG recording in this space. A fast algorithm is then used to compute the statistical distance between this attractor and all other attractors that are built using a sliding temporal window over the signal. For normal cases the distance stayed almost constant and below a threshold. For cases with abnormal transients, on the abnormal portion of ECG, the distance increased consistently with morphological changes.
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Julio Cesar Bastos de Figueiredo and Sergio Shiguemi Furuie "Using statistical distances to detect changes in the normal behavior of ECG-Holter signals", Proc. SPIE 4325, Medical Imaging 2001: Ultrasonic Imaging and Signal Processing, (30 May 2001); https://doi.org/10.1117/12.428236
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KEYWORDS
Electrocardiography

Signal detection

Dynamical systems

Complex systems

Probability theory

Databases

Signal analyzers

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