Empirical mode decomposition to assess baroreflex gain from spontaneous variability during exercise in humans.

V. Magagnin, T. Bassani, D. Lucini, M. Pagani, E. G. Caiani, S. Cerutti, A. Porta

Research output: Contribution to journalArticle

Abstract

Estimation of the baroreflex gain has become an important tool in clinical practice in order to assess cardiac autonomic system control. Spectral analysis and sequence analysis techniques based on the spontaneous variability of systolic arterial pressure and heart period have been proposed to evaluate the baroreflex gain. These analyses can be significantly altered by the presence of nonstationarities. Recently, the empirical mode decomposition (EMD), a signal processing technique particularly suitable for nonstationary series, has been proposed as a new tool for data analysis. The aim of this study is to propose EMD-based approaches to the evaluation of the baroreflex gain to account for the possible presence of nonstationarities of systolic arterial pressure and heart period series.

Fingerprint

Baroreflex
Decomposition
Arterial Pressure
Spectrum analysis
Blood Pressure
Signal processing
Control systems
Sequence Analysis

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

Cite this

@article{a22b6f4c703c427994c2fde8cdfff522,
title = "Empirical mode decomposition to assess baroreflex gain from spontaneous variability during exercise in humans.",
abstract = "Estimation of the baroreflex gain has become an important tool in clinical practice in order to assess cardiac autonomic system control. Spectral analysis and sequence analysis techniques based on the spontaneous variability of systolic arterial pressure and heart period have been proposed to evaluate the baroreflex gain. These analyses can be significantly altered by the presence of nonstationarities. Recently, the empirical mode decomposition (EMD), a signal processing technique particularly suitable for nonstationary series, has been proposed as a new tool for data analysis. The aim of this study is to propose EMD-based approaches to the evaluation of the baroreflex gain to account for the possible presence of nonstationarities of systolic arterial pressure and heart period series.",
author = "V. Magagnin and T. Bassani and D. Lucini and M. Pagani and Caiani, {E. G.} and S. Cerutti and A. Porta",
year = "2009",
language = "English",
pages = "2236--2239",
journal = "Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference",
issn = "1557-170X",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - JOUR

T1 - Empirical mode decomposition to assess baroreflex gain from spontaneous variability during exercise in humans.

AU - Magagnin, V.

AU - Bassani, T.

AU - Lucini, D.

AU - Pagani, M.

AU - Caiani, E. G.

AU - Cerutti, S.

AU - Porta, A.

PY - 2009

Y1 - 2009

N2 - Estimation of the baroreflex gain has become an important tool in clinical practice in order to assess cardiac autonomic system control. Spectral analysis and sequence analysis techniques based on the spontaneous variability of systolic arterial pressure and heart period have been proposed to evaluate the baroreflex gain. These analyses can be significantly altered by the presence of nonstationarities. Recently, the empirical mode decomposition (EMD), a signal processing technique particularly suitable for nonstationary series, has been proposed as a new tool for data analysis. The aim of this study is to propose EMD-based approaches to the evaluation of the baroreflex gain to account for the possible presence of nonstationarities of systolic arterial pressure and heart period series.

AB - Estimation of the baroreflex gain has become an important tool in clinical practice in order to assess cardiac autonomic system control. Spectral analysis and sequence analysis techniques based on the spontaneous variability of systolic arterial pressure and heart period have been proposed to evaluate the baroreflex gain. These analyses can be significantly altered by the presence of nonstationarities. Recently, the empirical mode decomposition (EMD), a signal processing technique particularly suitable for nonstationary series, has been proposed as a new tool for data analysis. The aim of this study is to propose EMD-based approaches to the evaluation of the baroreflex gain to account for the possible presence of nonstationarities of systolic arterial pressure and heart period series.

UR - http://www.scopus.com/inward/record.url?scp=84903875575&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84903875575&partnerID=8YFLogxK

M3 - Article

C2 - 19965155

SP - 2236

EP - 2239

JO - Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference

JF - Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference

SN - 1557-170X

ER -