Stochastic complexity measures for physiological signal analysis

被引：193

作者：

Rezek, IA ^{[1
]}

Roberts, SJ ^{[1
]}

机构：

[1] Univ London Imperial Coll Sci Technol & Med, Dept Elect & Elect Engn, London SW7 2BT, England

来源：

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING | 1998年 / 45卷 / 09期

关键词：

approximate entropy; autoregressive (AR) model order; spectral entropy (SE); state-space embedding; stochastic complexity;

D O I：

10.1109/10.709563

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Traditional feature extraction methods describe signals in terms of amplitude and frequency. This paper takes a paradigm shift and investigates four stochastic-complexity features. Their advantages are demonstrated on synthetic and physiological signals; the latter recorded during periods of Cheyne-Stokes respiration, anesthesia, sleep, and motor-cortex investigation.

引用

页码：1186 / 1191

页数：6

共 12 条

[1] EXTRACTING QUALITATIVE DYNAMICS FROM EXPERIMENTAL-DATA [J].

BROOMHEAD, DS ;

KING, GP .

PHYSICA D, 1986, 20 (2-3) :217-236

[2]

ELSNER JB, 1996, SINGULAR SPECTRUM AN

[3]

Hilborn RC, 1994, CHAOS NONLINEAR DYNA

[4] EEG ANALYSIS BASED ON TIME DOMAIN PROPERTIES [J].

HJORTH, B .

ELECTROENCEPHALOGRAPHY AND CLINICAL NEUROPHYSIOLOGY, 1970, 29 (03) :306-&

[5] SPECTRUM ANALYSIS - A MODERN PERSPECTIVE [J].

KAY, SM ;

MARPLE, SL .

PROCEEDINGS OF THE IEEE, 1981, 69 (11) :1380-1419

[6]

KRKIC M, 1996, P I EL ENG AI METH B

[7]

Marple S. L, 1987, Digital Spectral Analysis

[8]

PAJAN JJ, 1997, P I EL ENG VIS IM SI, V144, P116

[9] A review of parametric modelling techniques for EEG analysis [J].

Pardey, J ;

Roberts, S ;

Tarassenko, L .

MEDICAL ENGINEERING & PHYSICS, 1996, 18 (01) :2-11

[10] DIFFERENTIATION BETWEEN FINGER, TOE AND TONGUE MOVEMENT IN MAN BASED ON 40 HZ EEG [J].

PFURTSCHELLER, G ;

FLOTZINGER, D ;

NEUPER, C .

ELECTROENCEPHALOGRAPHY AND CLINICAL NEUROPHYSIOLOGY, 1994, 90 (06) :456-460

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