SCALING ANALYSIS OF PARKINSONIAN TREMOR
SCALING ANALYSIS OF PARKINSONIAN TREMOR
批准号:
7366531
负责人:
JEFFREY M HAUSDORFF
金额:
$0.81万
依托单位国家:
美国
项目类别:
财政年份:
2006
资助国家:
美国
项目状态:
已结题
起止时间:
2006-03-01 至 2007-02-28
中文摘要
该子项目是利用NIH/NCRR资助的中心赠款提供的资源的许多研究子项目之一。子项目和研究者(PI)可能从另一个NIH来源获得主要资金,因此可以在其他CRISP条目中表示。所列机构为中心,不一定是研究者所在机构。帕金森病患者表现出特征性震颤,在谐波频率处显示出具有宽峰的傅立叶频谱。频域中的这种类型的谐波结构可能是由于两类机制:非线性振荡过程或多个独立振荡模式的叠加。宽峰值谱通常指示信号是具有可变周期的半周期性的。这些“噪声”波动可能具有内在的顺序,可以使用缩放分析进行量化。我们开发了一种方法来提取的相关性(标度)性能的周期性动力学的多模态振荡,以区分非线性振荡和叠加的各个模式的振荡。该方法是基于我们的发现,在一个单一的振荡器的波动周期的时间相关性的信息内容包含在一个有限的频带中的功率谱,允许通过带通滤波的模式分解。我们对非线性振荡的模拟表明,每个“谐波”模式具有相同的标度特性。相比之下,当该方法应用于帕金森病患者的震颤记录时,前两种振荡模式会产生不同的缩放模式,这表明这些模式可能不是最初假设的简单谐波。在后续工作中,我们正在开发另一种方法来研究震颤频谱中多个峰值的起源,通过分析不同模式之间的同步。这些方法和研究结果对帕金森震颤的生理建模及其鉴别诊断以及其他生理时间序列的研究具有一定的意义。
英文摘要
This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Patients with Parkinson's disease exhibit characteristic tremor, showing a Fourier spectrum with broad peaks at harmonic frequencies. This type of harmonic structure in the frequency domain may be due to two classes of mechanisms: a nonlinear oscillatory process or the superposition of multiple independent modes of oscillation. A broad peak spectrum generally indicates that the signal is semi-periodic with a variable period. These "noisy" fluctuations may possess intrinsic order that can be quantified using scaling analysis. We developed a method to extract the correlation (scaling) properties in the periodic dynamics of multi-modal oscillations, in order to distinguish between a nonlinear oscillation and a superposition of individual modes of oscillations. The method is based on our finding that the information content of the temporal correlations in the fluctuating period of a single oscillator is contained in a finite frequency band in the power spectrum, allowing for decomposition of modes by bandpass filtering. Our simulations for a nonlinear oscillation show that each of the "harmonic" modes possesses the same scaling properties. In contrast, when the method is applied to tremor records from patients with Parkinson's disease, the first two modes of oscillations yield different scaling patterns, suggesting that these modes may not be simple harmonics, as might be initially assumed. In follow-up work, we are developing another method to study the origin of the multiple peaks in the frequency spectrum of tremor, by analyzing the synchronization between different modes. These methods and findings have implications for physiologic modeling of Parkinsonian tremor and its differential diagnosis, as well as for the study of other physiologic time series.
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