Analysis of physiological signals using state space correlation entropy

Analysis of physiological signals using state space correlation entropy

In this letter, the authors propose a new entropy measure for analysis of time series. This measure is termed as the state space correlation entropy (SSCE). The state space reconstruction is used to evaluate the embedding vectors of a time series. The SSCE is computed from the probability of the cor...

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Bibliographic Details
Main Authors: Rajesh Kumar Tripathy, Suman Deb, Samarendra Dandapat
Format: Article
Language:English
Published: Wiley 2016-11-01
Series:Healthcare Technology Letters
Subjects:
medical disorders
electrocardiography
electroencephalography
speech
medical signal processing
speech processing
entropy
state-space methods
correlation methods
time series
signal reconstruction
support vector machines
signal classification
physiological signals
state space correlation entropy
SSCE
state space reconstruction
synthetic valued signals
real valued signals
SVM classifier
support vector machine
sample entropy
permutation entropy
shockable ventricular arrhythmia
ECG
EEG
Online Access:https://digital-library.theiet.org/content/journals/10.1049/htl.2016.0065

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https://digital-library.theiet.org/content/journals/10.1049/htl.2016.0065

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