Nonlinear Analysis of Heart Rate Variability

心率变异性的非线性分析

• 批准号: 7260352
• 负责人: CHI-SANG POON
• 金额: $ 38.4万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-01 至 2009-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7260352
• 关键词: Accounting; Attention; Autonomic Dysfunction; Cardiac; Cessation of life; Clinical; Clinical Trials; Communities; Complex; Computational Technique; Computer Simulation; Congestive; Congestive Heart Failure; Data; Data Set; Detection; Development; Discipline; Discrimination; Disease; Face; Health; Heart; Heart Rate; Heart failure; Measurement; Modeling; Noise; Non-linear Models; Nonlinear Dynamics; Patients; Phase; Physiological; Population; Predictive Value; Regulation; Research; Science; Series; Signal Transduction; Study models; Sudden Death; System; Systems Theory; Techniques; Technology; Testing; Time; Titrations; Work; base; clinical application; computerized tools; interest; mortality; novel; outcome forecast; research clinical testing; theories

DESCRIPTION (provided by applicant): Heart rate variability (HRV) has received increasing attention as a simple noninvasive marker of cardiac-autonomic dysfunction, and recent clinical trials have shown that decreased HRV is a strong predictor of poor prognosis in patients with congestive heart failure (CHF). Despite such clinical interests, the mechanism of HRV remains poorly understood. Moreover, conventional HRV analysis based on ordinary statistical or nonlinear dynamics techniques are hampered by a general difficulty of these techniques in differentiating the deterministic components of HRV from the attendant stochastic components that obscure the underlying mechanism. To overcome these hurdles, this BCST project will build upon recent breakthoughs in nonlinear systems theory that allow reliable analysis of HRV. Aim 1 of the project will develop analytical techniques based on advanced nonlinear systems identification approaches that allow reliable quantitative assessment of the chaotic components of HRV in the face of attendant measurement noise and physiologic noise components. These enabling technologies will be made available to the biomedical community in the form of a comprehensive computational tool kit for general research applications. Aim 2 of the project will apply these analytical techniques to a thorough reappraisal of the decreased heart-rate chaos in a large population (N > 500) of ambulatory CHF patients from an established clinical trial (UK-HEART) and to the clinical evaluation of decreased heart-rate chaos as a predictor of death and mode of death in these patients followed over a six-year period. The results from Aims 1-2 will provide strong analytical and experimental bases for the development (in Aim 3) of a computational model of cardiac-autonomic regulation that accounts for the varying deterministic and stochastic components of HRV in health and in CHF. These clinical and modeling studies in turn will showcase the proposed analytical techniques thereby paving the way for their application to other complex biomedical modeling and analysis problems in general.

描述（由申请人提供）：心率可变性（HRV）作为心脏自主功能障碍的简单无创标志物已受到越来越多的关注，并且最近的临床试验表明，HRV的降低是对充血性心力衰竭患者预后不良的有力预测指标（CHF）。尽管存在如此临床利益，但HRV的机制仍然知之甚少。此外，基于普通统计或非线性动力学技术的常规HRV分析受到这些技术在区分HRV的确定性组件与掩盖潜在机制的随之而来的随机组件方面的一般难度来阻碍。为了克服这些障碍，这个BCST项目将基于非线性系统理论的最新突破，该理论允许对HRV的可靠分析。该项目的目标1将基于先进的非线性系统识别方法开发分析技术，这些方法可以在面对随之测量的噪声和生理噪声组件的情况下对HRV的混乱组件进行可靠的定量评估。这些支持技术将以全面的计算工具套件的形式提供给生物医学界的一般研究应用程序。该项目的AIM 2将对来自既定的临床试验（英国Heart）的众多人口（n> 500）患者的心率降低（n> 500）的心率降低（n> 500）的彻底重新评估，并将这些分析技术应用于心率下降（n> 500）和对临床评估。在六年的时间内，这些患者的死亡和死亡方式的预测减少了心率混乱。 AIMS 1-2的结果将为心脏自主调节的计算模型的开发（在AIM 3中）提供强大的分析和实验基础，该计算模型解释了HRV在健康和CHF中HRV的确定性和随机成分的不同。这些临床和建模研究反过来将展示提出的分析技术，从而为其在其他复杂的生物医学建模和分析问题上的应用铺平道路。