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.

ASJC Scopus subject areas

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

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