Nonlinear Analysis of Heart Rate Variability

心率变异性的非线性分析

• 批准号: 7455251
• 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 2011-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7455251
• 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）：心率变异性（HRV）作为心脏自主神经功能障碍的简单无创标志物越来越受到关注，最近的临床试验表明，HRV 降低是充血性心力衰竭（CHF）患者预后不良的有力预测因子。尽管有这样的临床兴趣，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传统 HRV 分析受到这些技术在区分 HRV 的确定性成分与掩盖潜在机制的伴随随机成分方面的普遍困难的阻碍。为了克服这些障碍，该 BCST 项目将建立在非线性系统理论的最新突破之上，以实现可靠的 HRV 分析。该项目的目标 1 将开发基于先进非线性系统识别方法的分析技术，在面对伴随的测量噪声和生理噪声分量时，能够对 HRV 的混沌分量进行可靠的定量评估。这些支持技术将以用于一般研究应用的综合计算工具包的形式提供给生物医学界。该项目的目标 2 将应用这些分析技术，对来自一项既定临床试验 (UK-HEART) 的大量 (N > 500) 流动性 CHF 患者的心率混乱程度降低进行彻底重新评估，并对心率混乱程度降低作为这些患者的死亡和死亡模式的预测指标进行为期六年的临床评估。目标 1-2 的结果将为心脏自主调节计算模型的开发（目标 3）提供强有力的分析和实验基础，该模型解释了健康和 CHF 中 HRV 的不同确定性和随机成分。这些临床和建模研究反过来将展示所提出的分析技术，从而为它们应用于其他复杂的生物医学建模和分析问题铺平道路。