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Titolo:
EVOLUTIONARY MAXIMUM-ENTROPY SPECTRAL ESTIMATION AND HEART-RATE-VARIABILITY ANALYSIS
Autore:
SHAH SI; CHAPARRO LF; ELJAROUDI A; FURMAN JM;
Indirizzi:
UNIV PITTSBURGH,DEPT ELECT ENGN,348 BENEDUM HALL PITTSBURGH PA 15261 UNIV PITTSBURGH,DEPT OTOLARYNGOL PITTSBURGH PA 15261
Titolo Testata:
Multidimensional systems and signal processing
fascicolo: 4, volume: 9, anno: 1998,
pagine: 453 - 458
SICI:
0923-6082(1998)9:4<453:EMSEAH>2.0.ZU;2-W
Fonte:
ISI
Lingua:
ENG
Soggetto:
NONSTATIONARY;
Keywords:
NONSTATIONARY TIME SERIES; EVOLUTIONARY SPECTRAL THEORY; SPECTRAL ANALYSIS OF HEART RATE VARIABILITY; CARDIOVASCULAR TIME SERIES;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
CompuMath Citation Index
Science Citation Index Expanded
Science Citation Index Expanded
Citazioni:
11
Recensione:
Indirizzi per estratti:
Citazione:
S.I. Shah et al., "EVOLUTIONARY MAXIMUM-ENTROPY SPECTRAL ESTIMATION AND HEART-RATE-VARIABILITY ANALYSIS", Multidimensional systems and signal processing, 9(4), 1998, pp. 453-458

Abstract

Spectral analysis has been used extensively in heart rate variability(HRV) studies. The spectral content of HRV signals is useful in assessing the status of the autonomic nervous system. Although most of the HRV studies assume stationarity, the statistics of HRV signals change with time due to transients caused by physiological phenomena. Therefore, the use of time-frequency analysis to estimate the time-dependent spectrum of these non-stationary signals is of great importance. Recently, the spectrogram, the Wigner distribution, and the evolutionary periodogram have been used to analyze HRV signals. In this paper, we propose the application of the evolutionary maximum entropy (EME) spectral analysis to HRV signals. The EME spectral analysis is based on the maximum entropy method for stationary processes and the evolutionary spectral theory. It consists in finding an EME spectrum that matches theFourier coefficients of the evolutionary spectrum. The spectral parameters are efficiently calculated by means of the Levinson algorithm. The EME spectral estimator provides very good time-frequency resolution, sidelobe reduction and parametric modeling of the evolutionary spectrum. With the help of real HRV signals we show the superior performance of the EME over the earlier methods.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 12/07/20 alle ore 12:11:12