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The automatic nervous system, ventricular repolarisation and risk of sudden cardiac failureLu, Fei January 1995 (has links)
No description available.
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Risk stratification of patients after myocardial infarction and patients with cardiomyopathies by non-invasive electrocardiographic methodsGang, Yi January 1999 (has links)
No description available.
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Automated identification of abnormal patterns in the intrapartum cardiotocogramCazares, Shelley Marie January 2002 (has links)
No description available.
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The QT and related intervals, physiological pacing and the performance of the 'QT-Responsive' (TX) pacemakerFananapazir, Lameh January 1986 (has links)
No description available.
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Hierarchical structure in human heart rate variability. / 人類心率變化中的層次結構 / Hierarchical structure in human heart rate variability. / Ren lei xin lü bian hua zhong de ceng ci jie gouJanuary 2005 (has links)
Zhang Cheungyao = 人類心率變化中的層次結構 / 張程遙. / Thesis submitted in: November 2004. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (leaves 75-77). / Text in English; abstracts in English and Chinese. / Zhang Cheungyao = Ren lei xin lü bian hua zhong de ceng ci jie gou / Zhang Chengyao. / Table of Contents --- p.1 / List of Figures --- p.6 / List of Tables --- p.7 / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- What is human heart rate variability? --- p.1 / Chapter 1.2 --- Review of previous work --- p.2 / Chapter 1.3 --- Outline of the thesis --- p.6 / Chapter 2 --- Basic statistical properties of human heartbeat data --- p.8 / Chapter 2.1 --- Data analyzed --- p.8 / Chapter 2.2 --- Results and conclusion --- p.11 / Chapter 3 --- Further analysis of heartbeat interval data --- p.20 / Chapter 3.1 --- The method of analysis --- p.20 / Chapter 3.2 --- Characteristic parameters for the multifractality of HRV --- p.22 / Chapter 4 --- Results and discussion --- p.24 / Chapter 4.1 --- Existence of hierarchical structure in human HRV --- p.24 / Chapter 4.2 --- Characteristic parameters and potential application --- p.32 / Chapter 5 --- A cardiac dynamical model --- p.51 / Chapter 5.1 --- Description of the model --- p.51 / Chapter 5.2 --- Review of some interesting results --- p.59 / Chapter 5.3 --- Numerical methods --- p.61 / Chapter 6 --- Results and discussion --- p.62 / Chapter 6.1 --- Output for our simulation --- p.62 / Chapter 6.2 --- Probability density function and structure functions --- p.65 / Chapter 7 --- Conclusion --- p.73 / Bibliography --- p.75
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A normal-mixture model with random-effects for RR-interval data /Ketchum, Jessica McKinney, January 2006 (has links)
Thesis (Ph. D.)--Virginia Commonwealth University, 2006. / Prepared for: Dept. of Biostatistics. Bibliography: leaves 189-198. Also available online via the Internet.
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Discrepancy between training, competition and laboratory measures of maximum heart rate in NCAA division 2 distance runnersSemin, K, Stahlnecker, AC, Heelan, K, Brown, GA, Shaw, BS, Shaw, I 21 November 2008 (has links)
A percentage of either measured or predicted maximum heart
rate is commonly used to prescribe and measure exercise intensity.
However, maximum heart rate in athletes may be greater
during competition or training than during laboratory exercise
testing. Thus, the aim of the present investigation was to determine
if endurance-trained runners train and compete at or above
laboratory measures of ‘maximum’ heart rate. Maximum heart
rates were measured utilising a treadmill graded exercise test
(GXT) in a laboratory setting using 10 female and 10 male
National Collegiate Athletic Association (NCAA) division 2
cross-country and distance event track athletes. Maximum training
and competition heart rates were measured during a highintensity
interval training day (TR HR) and during competition
(COMP HR) at an NCAA meet. TR HR (207 ± 5.0 b·min-1;
means ± SEM) and COMP HR (206 ± 4 b·min-1) were significantly
(p < 0.05) higher than maximum heart rates obtained
during the GXT (194 ± 2 b·min-1). The heart rate at the ventilatory
threshold measured in the laboratory occurred at 83.3 ±
2.5% of the heart rate at VO2 max with no differences between
the men and women. However, the heart rate at the ventilatory
threshold measured in the laboratory was only 77% of the
maximal COMP HR or TR HR. In order to optimize traininginduced
adaptation, training intensity for NCAA division 2
distance event runners should not be based on laboratory assessment
of maximum heart rate, but instead on maximum heart
rate obtained either during training or during competition.
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Silicon CMOS IC implementation of heart rate extractionChen, Mingqi January 2006 (has links)
Thesis (M.S.)--University of Hawaii at Manoa, 2006. / Includes bibliographical references (leaves 95-98). / 105 leaves, bound ill. 29 cm
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Visualisation and pattern recognition of heart rate variability / Ben Raymond.Raymond, Ben January 1999 (has links)
Errata tipped in before title page. / Bibliography: p. 173-194. / xv, 194 p. : ill. (some col.) ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Considers various signal processing aspects of heart rate variability analysis; in particular, those of data visualisation and classification. / Thesis (Ph.D.)--University of Adelaide, Depts. of Electrical and Electronic Engineering and Applied Mathematics, 1999
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Visualisation and pattern recognition of heart rate variability /Raymond, Ben. January 1999 (has links) (PDF)
Thesis (Ph.D.)--University of Adelaide, Depts. of Electrical and Electronic Engineering and Applied Mathematics, 1999. / Errata tipped in before title page. Bibliography: p. 173-194.
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