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用于心血管变异性分析的多模态信号处理

Multimodal signal processing for the analysis of cardiovascular variability.

作者信息

Porta Alberto, Aletti Federico, Vallais Frederic, Baselli Giuseppe

机构信息

Department of Technologies for Health, Galeazzi Orthopaedic Institute, University of Milan, 20161 Milan, Italy.

出版信息

Philos Trans A Math Phys Eng Sci. 2009 Jan 28;367(1887):391-409. doi: 10.1098/rsta.2008.0229.

Abstract

Cardiovascular (CV) variability as a primary vital sign carrying information about CV regulation systems is reviewed by pointing out the role of the main rhythms and the various control and functional systems involved. The high complexity of the addressed phenomena fosters a multimodal approach that relies on data analysis models and deals with the ongoing interactions of many signals at a time. The importance of closed-loop identification and causal analysis is remarked upon and basic properties, application conditions and methods are recalled. The need of further integration of CV signals relevant to peripheral and systemic haemodynamics, respiratory mechanics, neural afferent and efferent pathways is also stressed.

摘要

通过指出主要节律以及所涉及的各种控制和功能系统的作用,对作为携带心血管调节系统信息的主要生命体征的心血管(CV)变异性进行了综述。所涉及现象的高度复杂性促进了一种多模态方法,该方法依赖于数据分析模型,并同时处理许多信号之间正在进行的相互作用。阐述了闭环识别和因果分析的重要性,并回顾了其基本特性、应用条件和方法。还强调了进一步整合与外周和全身血流动力学、呼吸力学、神经传入和传出途径相关的心血管信号的必要性。

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