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Statistical physics approaches to un...

Hu, Kun.

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Statistical physics approaches to understanding physiological fluctuations.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Statistical physics approaches to understanding physiological fluctuations./
作者:	Hu, Kun.
面頁冊數:	150 p.
附註:	Source: Dissertation Abstracts International, Volume: 66-10, Section: B, page: 5447.
Contained By:	Dissertation Abstracts International66-10B.
標題:	Physics, General. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3193066
ISBN:	0542373912

Statistical physics approaches to understanding physiological fluctuations.
Hu, Kun.

Statistical physics approaches to understanding physiological fluctuations. - 150 p.

Source: Dissertation Abstracts International, Volume: 66-10, Section: B, page: 5447.

Thesis (Ph.D.)--Boston University, 2005.

This dissertation investigates the influences of the circadian pacemaker on the temporal structures of fluctuations in the human heartbeat and other related physiological signals. The scale-invariant properties of these physiological fluctuations are demonstrated to possess significant circadian rhythms. These findings are relevant in understanding the daily patterns of adverse cardiac events reported by epidemiological studies.

ISBN: 0542373912Subjects--Topical Terms:

1018488
Physics, General.

Statistical physics approaches to understanding physiological fluctuations.
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245 1 0 $a Statistical physics approaches to understanding physiological fluctuations.
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500 $a Source: Dissertation Abstracts International, Volume: 66-10, Section: B, page: 5447.
500 $a Major Professor: H. Eugene Stanley.
502 $a Thesis (Ph.D.)--Boston University, 2005.
520 $a This dissertation investigates the influences of the circadian pacemaker on the temporal structures of fluctuations in the human heartbeat and other related physiological signals. The scale-invariant properties of these physiological fluctuations are demonstrated to possess significant circadian rhythms. These findings are relevant in understanding the daily patterns of adverse cardiac events reported by epidemiological studies.
520 $a Part I of this dissertation introduces the daily pattern in the onset of adverse cardiac events, the circadian pacemaker, and experimental methods of assessing the circadian influences. This part also reviews scale-invariant properties of physiological fluctuations, and scaling analyses that are used to access long-range correlations (an important scale-invariant property).
520 $a Part II focuses on the effects of trends and nonstationarities---the mean value, standard deviation, and correlation function of signals are not invariant over time. In the case that trends and nonstationarities are unrelated to the underlying mechanism of a signal, simulations and analytic derivations are conducted to explore how to quantify accurately the correlations embedded in the noisy signals that have trends and nonstationarities.
520 $a Part III investigates dynamics of human motor activity---a physiological function highly correlated with cardiac dynamics. Results demonstrate that apparently random forearm motion possesses previously unrecognized dynamic patterns. These are characterized by similar distribution forms, long-range correlations, and nonlinear Fourier phase interactions across separate individuals and measurements.
520 $a Part IV reports circadian influences on the dynamic properties of heartbeat fluctuations and activity signals. Correlation properties of heartbeat fluctuations are found to exhibit a significant circadian rhythm that is independent of behavior-related factors including sleep/wake cycles, and random or scheduled events. This circadian rhythm is also unrelated to circadian-mediated effects on the dynamical properties and the mean activity levels. Moreover, the circadian rhythm brings the dynamical and correlation properties of heartbeat fluctuation at 9-11 AM---a well known window of cardiac vulnerability---closer to the behavior of a random walk. Since a random walk is associated with a random process without any underlying feedback control, this finding suggests that the circadian pacemaker may be contributing to the epidemiologically observed increase of cardiac risk in vulnerable patients at 9-11 AM.
590 $a School code: 0017.
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