Suppr超能文献

在撤机试验中评估心肺相互作用的信息流。

Information flow to assess cardiorespiratory interactions in patients on weaning trials.

作者信息

Vallverdú M, Tibaduisa O, Clariá F, Hoyer D, Giraldo B, Benito S, Caminal P

机构信息

Dep. ESAII, Centre for Biomedical Engineering Research, Technical University of Catalonia, Barcelona, Gargallo, 5, 08028 Barcelona, Spain.

出版信息

Conf Proc IEEE Eng Med Biol Soc. 2006;2006:1462-5. doi: 10.1109/IEMBS.2006.260390.

Abstract

Nonlinear processes of the autonomic nervous system (ANS) can produce breath-to-breath variability in the pattern of breathing. In order to provide assess to these nonlinear processes, nonlinear statistical dependencies between heart rate variability and respiratory pattern variability are analyzed. In this way, auto-mutual information and cross-mutual information concepts are applied. This information flow analysis is presented as a short-term non linear analysis method to investigate the information flow interactions in patients on weaning trials. 78 patients from mechanical ventilation were studied: Group A of 28 patients that failed to maintain spontaneous breathing and were reconnected; Group B of 50 patients with successful trials. The results show lower complexity with an increase of information flow in group A than in group B. Furthermore, a more (weakly) coupled nonlinear oscillator behavior is observed in the series of group A than in B.

摘要

自主神经系统(ANS)的非线性过程可在呼吸模式中产生逐次呼吸变异性。为了评估这些非线性过程,分析了心率变异性与呼吸模式变异性之间的非线性统计依赖性。通过这种方式,应用了自互信息和交叉互信息概念。这种信息流分析作为一种短期非线性分析方法,用于研究撤机试验患者的信息流相互作用。对78例机械通气患者进行了研究:A组28例患者未能维持自主呼吸并重新连接呼吸机;B组50例患者撤机成功。结果显示,A组的复杂性低于B组,且信息流增加。此外,与B组相比,在A组系列中观察到更(弱)耦合的非线性振荡器行为。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验