Dissertations / Theses on the topic 'Heart Rate Variability'
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Uhlig, Stefan. "Heart Rate Variability." Doctoral thesis, Universitätsbibliothek Chemnitz, 2018. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-233101.
Full textSattar, Nedal Abdul. "Heart rate variability in man." Thesis, University of Edinburgh, 1989. http://hdl.handle.net/1842/30723.
Full textKurths, Jürgen, A. Voss, Annette Witt, P. Saparin, H. J. Kleiner, and N. Wessel. "Quantitative analysis of heart rate variability." Universität Potsdam, 1994. http://opus.kobv.de/ubp/volltexte/2007/1347/.
Full textMigeotte, Pierre-François. "Heart rate variability :applications in microgravity." Doctoral thesis, Universite Libre de Bruxelles, 2003. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/211257.
Full textBerndtsson, Andreas. "Heart Rate Variability Biofeedback for Android." Thesis, KTH, Medicinsk teknik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-136687.
Full textHeart rate variability (HRV) är variationerna i tid mellan två efterföljande hjärtslag, och återspeglar autonomiska nervsystemets funktion. HRV är en tydlig markör for många sjukdomar, men det är också välkänt att HRV kan påverkas medvetet trots att det styrs av autonomiska nervsystemet. Andning är en viktig påverkande faktor av HRV och denna egenskap utnyttjas i HRV biofeedback, som är en teknik som syftar till att öka HRV. Typiska system för HRV biofeedback mäter variationerna i hjärtfrekvens och visar upp informationen på en display, vilket låter användaren ta kontroll över denna parameter och öka HRV. I denna uppsats presenteras ett program för biofeedback av HRV. Mjukvaran har implementerats för Android och körs på en surfplatta för att skapa ett biofeedbacksystem som är portabelt och där tillgängligheten är hög, till skillnad från de flesta andra biofeedback system som är beroende av en dator. Programmet som utvecklats har visat sig vara fullt funktionellt i realtid och visar upp pålitliga parametrar för användaren. En förstudie har även utförts för att utvärdera effekterna vid användning av programmet. Dessa mätningar indikerar att biofeedbackträning med den föreslagna lösningen ökar HRV efter användning. En mer omfattande studie med fler personer bör dock genomföras för att ge en tydligare bild av effekterna av träning med detta program.
Heathers, James. "Methodological improvements in heart rate variability." Thesis, The University of Sydney, 2014. http://hdl.handle.net/2123/13106.
Full textLitster, Caroline Elizabeth. "Heart rate, heart rate variability, electrodermal activity and the differentiation-of-deception /." Title page, table of contents and abstract only, 2002. http://web4.library.adelaide.edu.au/theses/09SSPS/09sspsl7769.pdf.
Full textZapanta, Laurence (Laurence F. ). "Heart rate variability in mice with coronary heart disease." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/34118.
Full textIncludes bibliographical references (leaves 69-71).
Heart rate variability (HRV), the beat-to-beat fluctuation of the heart rate, is a non-invasive test that measures the autonomic regulation of the heart. Assessment of HRV has been shown to predict the risk of mortality in patients after an acute myocardial infarction. Recently, the Krieger lab at MIT developed genetically engineered double knockout (dKO) mice that develop coronary artery disease accompanied by spontaneous myocardial infarctions and die at a very young age. This thesis investigated whether HRV could function as a prognostic indicator in the dKO mouse. A novel method for estimating physiological state of the mouse from the electrocardiogram using an innovative activity index was developed in order to compare HRV variables at different times while controlling for physiologic state. Traditional time and frequency domain variables were used to assess the prognostic power of HRV. Results have shown that none of the HRV variables were helpful in predicting mortality in the dKO mice. Mean heart rate showed some prognostic power, but it was not consistent in all the dKO mice. Finally, the activity index developed in this thesis provided a reliable metric for activity in mice as validated by a camera with motion detection.
by Laurence Zapanta.
S.M.
Dodds, Kirsty Lyn. "Heart to Heart: Exploring Heart Rate Variability in Insomnia Patient Subtypes." Thesis, The University of Sydney, 2017. http://hdl.handle.net/2123/17262.
Full textZemánek, Ladislav. "Analýza variability srdečního rytmu pomocí entropie." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2013. http://www.nusl.cz/ntk/nusl-220014.
Full textAlghoul, Karim. "Heart Rate Variability Extraction from Video Signals." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/33003.
Full textThapa, Rinku. "Heart Rate Variability in Autism Spectrum Disorder." Thesis, University of Sydney, 2020. https://hdl.handle.net/2123/22968.
Full textPersson, Anna. "Heart rate variability for driver sleepiness assessment." Thesis, Linköpings universitet, Institutionen för medicinsk teknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157187.
Full textWilliams, Elizabeth A. "Caregiving Burden and Heart Rate Variability: Differences by Race and Gender." Case Western Reserve University School of Graduate Studies / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=case1586291354640556.
Full textMuskett, Ashley. "Improving Anxiety Assessment in Autism: A Potential Use for Heart Rate Variability and Heart Rate." Thesis, Virginia Tech, 2018. http://hdl.handle.net/10919/82233.
Full textMaster of Science
Anxiety is an area of documented challenge for people with Autism Spectrum Disorder (ASD). Despite this, some studies state that those with ASD and language deficits have lower reported anxiety than those without language deficits. This effect may be due to the complicated task of appropriately evaluating anxiety in those with compromised language. Using biomarkers of anxiety, such as reduced Heart Rate Variability (HRV) and increased Heart Rate (HR), may improve anxiety assessment but more research is necessary. Specifically, it would be helpful to understand if the relationship between HRV/HR and anxiety is moderated by language abilities in children with ASD, and whether HRV/HR can discriminate between anxiety and other emotions, like anger, in children with ASD. This study examined the relationship between baseline HRV/HR, language ability, and different emotional states (i.e., anxiety and anger) in a sample of 23 children with ASD. It was hypothesized that receptive language would moderate the relationship between decreased HRV/increased HR and increased anxiety but not the relationship between decreased HRV/increased HR and increased anger. Multiple regression analyses indicated that HRV and HR were not significant predictors of anxiety or anger, and language was not a significant moderator. Future studies may wish to take new approaches to determining the role of language in the relationship between HRV/HR and anxiety.
Ho, Ian-ian, and 何欣欣. "Heart rate variability and outcome in acute stroke." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B46938242.
Full textClifford, Gari D. "Signal processing methods for heart rate variability analysis." Thesis, University of Oxford, 2002. http://ora.ox.ac.uk/objects/uuid:5129701f-1d40-425a-99a3-59a05e8c1b23.
Full textChannell, Rachel Marie. "The Associations of Extraversion and Heart Rate Variability." BYU ScholarsArchive, 2021. https://scholarsarchive.byu.edu/etd/9001.
Full textBoone, Louvonia Rose. "Heart rate variability as a predictor of hypotension." [New Haven, Conn. : s.n.], 2008. http://ymtdl.med.yale.edu/theses/available/etd-11212008-110758/.
Full textLucas, Angela K. "Effects of pediatric adiposity on heart rate variability /." Available online. Click here, 2009. http://services.lib.mtu.edu/etd/THESIS/2009/BiologicalSci/lucas/thesis.pdf.
Full textRaymond, Ben. "Visualisation and pattern recognition of heart rate variability /." Title page, contents and abstract only, 1999. http://web4.library.adelaide.edu.au/theses/09PH/09phr268.pdf.
Full textBrouse, Chris J. "Monitoring nociception during general anesthesia with heart rate variability." Thesis, University of British Columbia, 2015. http://hdl.handle.net/2429/52851.
Full textApplied Science, Faculty of
Electrical and Computer Engineering, Department of
Graduate
Acquarone, Isabel Jimenez. "Heart rate variability : a means to assess equine temperament." Thesis, Imperial College London, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.540659.
Full textMainardi, Amelia. "Heart Rate Variability and Oxytocin: Measures of Parasympathetic Control." Scholarship @ Claremont, 2014. http://scholarship.claremont.edu/scripps_theses/435.
Full textShafqat, Kamran. "Heart rate variability analysis in patients undergoing local anaesthesia." Thesis, City University London, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.518040.
Full textPuente, Eduardo Tejera. "Heart Rate Variability Analysis During Normal and Hypertensive Pregnancy." Doctoral thesis, Faculdade de Farmácia da Universidade do Porto, 2009. http://hdl.handle.net/10216/53927.
Full textBoman, Kajsa. "Heart rate variability : A possible measure of subjective wellbeing?" Thesis, Högskolan i Skövde, Institutionen för biovetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-15911.
Full textMinnis, James Michael. "Nutrition and athletic performance: implications of heart rate variability." Kansas State University, 2015. http://hdl.handle.net/2097/20344.
Full textDepartment of Human Nutrition
Mark Haub
The purpose of this review is to examine the role of heart rate variability (HRV) as a predictor of athletic readiness and performance and assess whether nutrition strategies can be implemented to create favorable HRV indices with the goal of improving athletic readiness and performance. The balance between training and recovery is crucial for reaching an optimal adaptation and avoiding overtraining, allowing for improved readiness to train and compete. The measurement of HRV is non-invasive and is used primarily to quantify physical and mental stress in athletes by monitoring the effects of the autonomic nervous system on the heart. Current data suggests a relationship between resting parasympathetic tone, via time and frequency domains, and athletic performance. Parasympathetic modulated HRV indices have been associated with performance metrics such as peripheral work capacity, aerobic power, running and sprint performance, swimming performance, weight lifting performance, anaerobic capacity, strength, and enhanced mental focus/skill execution. The use of nutrition to help enhance sports performance is becoming more common. Evidence-based sports nutrition provides fuel for training/competition, assists in maximizing training adaptations, enhances recovery, improves mental focus, and aids in injury prevention and recovery. The use of nutrition strategies to influence HRV is novel and current evidence is scarce in regards to nutritional effects on HRV, specifically in athletes. Current research suggests that achieving energy balance and decreasing body fat in overweight/obese individuals has positive effects on the vagal component of HRV indices. Proper hydration, fruit and vegetable intake, a moderate carbohydrate diet, omega-3 fatty acid supplementation/intake also seem to have positive effects on HRV indices. Certain individual supplements have been studied in regards to HRV including casein hydrolysate, amaranth oil, and bovine colostrum. Caffeine seems to have the opposite effect on HRV indices, increasing sympathetic modulation while decreasing parasympathetic modulation. Much more research needs to be done in regard to potential nutritional influences on HRV so that sport dietitians feel confident in the methods currently used to assess athlete readiness and determining what types of nutrition strategies may be used to further improve the performance of an athlete.
Shah, Siddharth S. "Robust Heart Rate Variability Analysis using Gaussian Process Regression." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1293737259.
Full textPace, Diane Todd. "Effect of postmenopausal hormone replacement on heart rate variability." View the abstract Download the full-text PDF version, 1998. http://etd.utmem.edu/ABSTRACTS/1998-003-pace-index.html.
Full textTitle from title page screen (viewed on October 17 2008). Research advisor: Kay F. Engelhardt. Document formatted into pages (xi, 162 p. : ill.). Vita. Abstract. Includes bibliographical references (p.162).
McMillan, Diana Elizabeth. "Heart rate variability during sleep in fibromyalgia and insomnia /." Thesis, Connect to this title online; UW restricted, 2001. http://hdl.handle.net/1773/7183.
Full textPuente, Eduardo Tejera. "Heart Rate Variability Analysis During Normal and Hypertensive Pregnancy." Tese, Faculdade de Farmácia da Universidade do Porto, 2009. http://hdl.handle.net/10216/53927.
Full textPlewa, Luke Joseph. "Sudden Cardiac Arrest Prediction through Heart Rate Variability Analysis." DigitalCommons@CalPoly, 2015. https://digitalcommons.calpoly.edu/theses/1449.
Full textDixon, Paul David. "Stability and variability of physiological control determined from heart rate variability in infants." Thesis, Imperial College London, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.368644.
Full textMelchor, Rodríguez Angel. "Contributions to heart rate variability and respiratory rate analysis through video imaging techniques." Doctoral thesis, Universitat Politècnica de Catalunya, 2019. http://hdl.handle.net/10803/665983.
Full textEn la presente tesis doctoral se proponen una serie de métodos los cuales tienen como objetivo general la evaluación sin contacto de la variabilidad de la frecuencia cardíaca y la frecuencia respiratoria mediante imagen de video. La propuesta de esta técnica ha surgido en los últimos años como una alternativa a los sistemas de medida tradicionales, los cuales evalúan estos y otros parámetros fisiológicos a través de contacto directo con el cuerpo de la persona. Debido a esta condición, los sistemas tradicionales podrían ocasionar algunas complicaciones en personas que presentan una piel sensible o frágil, tal como los recién nacidos o pacientes con lesiones por quemaduras. Además, aunque la técnica de imagen de video podría ser una excelente alternativa, como en los casos mencionados previamente, ésta también tiene como objetivo ser un instrumento de monitorización para la población en general en entornos no clínicos. De hecho, hoy en día, el uso de dispositivos electrónicos tales como las cámaras de video, teléfonos inteligentes, tabletas y otros, empieza a ser parte del seguimiento de un estilo de vida saludable. Así, esta prometedora técnica, la cual podría proporcionar ventajas tales como la medición sin contacto, portabilidad, fácil uso y bajo costo, podría ser utilizada en un futuro cercano como parte de la evaluación del estado de salud de una persona en la vida cotidiana. Por otra parte, a pesar de las ventajas mencionadas, las mediciones adquiridas mediante esta técnica pueden ser afectadas en gran medida por factores tales como el movimiento de la persona, las condiciones de iluminación, las ajustes de la cámara, entre otros. Por tanto, en este trabajo de investigación se lleva a cabo un análisis de la influencia de varios factores y condiciones para obtener una mejor comprensión del alcance y las limitaciones de la técnica. Para este propósito, se han desarrollado e implementado una serie de métodos en los cuales se aplicaron algoritmos de detección facial y seguimiento, así como también técnicas de procesamiento de imágenes y señales. Los resultados obtenidos en cada estudio son evaluados a través de distintos parámetros estadísticos y gráficos con el objetivo de medir el acuerdo entre los métodos propuestos y los sistemas de referencia. En general, el análisis estadístico llevado a cabo muestra un buen nivel de concordancia entre los sistemas de medida. Es importante tener en cuenta la presencia de un impacto en los resultados, en mayor o menor medida, por los factores y condiciones analizados en los distintos estudios. En varios casos, los resultados muestran una mejoría significativa en comparación con los datos reportados en estudios relacionados. Por el contrario, los resultados adquiridos en escenarios con una mayor presencia de artefactos muestran una disminución en el acuerdo de las medidas. Esta técnica sin contacto podría eventualmente convertirse en un instrumento para detectar trastornos físicos o psicológicos en el futuro. No obstante, su uso para este objetivo dependerá del progreso de la técnica en los próximos años, ya que ésta se encuentra aún en fase de investigación y desarrollo. Por lo tanto, mayores mejoras son necesarias para alcanzar la fiabilidad que se consigue con los sistemas de referencia actuales y, particularmente, si se plantea su aplicación en escenarios reales. El desarrollo de algoritmos más robustos es requerido a fin de suprimir, tanto como sea posible, la contribución de artefactos presentes en un entorno real. Por consiguiente, la adquisición de medidas en varios escenarios de la vida real, registros de más larga duración, y el análisis de una mayor cantidad de factores que podrían influir al desempeño de la técnica constituyen algunos de los objetivos para trabajo futuro
Saunders, Roger D. (Roger Dean). "Depression and Heart Rate Variability in Patients with Coronary Artery Disease." Thesis, University of North Texas, 1994. https://digital.library.unt.edu/ark:/67531/metadc278101/.
Full textKeeney, Janice E. "Effects of Heart Rate Variability Biofeedback-assisted Stress Management Training on Pregnant Women and Fetal Heart Rate Measures." Thesis, University of North Texas, 2008. https://digital.library.unt.edu/ark:/67531/metadc9073/.
Full textKeeney, Janice E. Chandler Cynthia K. "Effects of heart rate variability biofeedback-assisted stress management training on pregnant women and fetal heart rate measures." [Denton, Tex.] : University of North Texas, 2008. http://digital.library.unt.edu/permalink/meta-dc-9073.
Full textNewell, Miranda E. "The connection between emotion, brain lateralization, and heart-rate variability /." Download the thesis in PDF, 2005. http://www.lrc.usuhs.mil/dissertations/pdf/Newell2005.pdf.
Full textBallora, Mark. "Data analysis through auditory display : applications in heart rate variability." Thesis, McGill University, 2000. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=35463.
Full textStrachan, Nicole Cecelia. "Baroreceptor sensitivity and heart rate variability in sport related concussions." Thesis, University of British Columbia, 2013. http://hdl.handle.net/2429/45255.
Full textBoardman, Anita. "The feasibility of using heart rate variability to detect distress." Thesis, University of Leicester, 2003. http://hdl.handle.net/2381/30206.
Full textFrändén, Philip. "Neural Correlates of Heart Rate Variability : Threat and Safety Perception." Thesis, Högskolan i Skövde, Institutionen för biovetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-15994.
Full textFox, Sheilagh. "Client Experiences of a Brief Heart Rate Variability Biofeedback Protocol." BYU ScholarsArchive, 2020. https://scholarsarchive.byu.edu/etd/8621.
Full textRitchie, Rolf Armand Mattei. "Don't Worry, Be Mindful: Mindfulness, Perseveration, and Heart Rate Variability." Bowling Green State University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1467665357.
Full textEonta, Alison. "Heart Rate Variability as a Moderator of Trauma Writing Outcomes." VCU Scholars Compass, 2013. http://scholarscompass.vcu.edu/etd/3236.
Full text"Heart rate variability in heart failure." 2002. http://library.cuhk.edu.hk/record=b5891359.
Full textThesis (M.Phil.)--Chinese University of Hong Kong, 2002.
Includes bibliographical references (leaves 119-129).
Abstracts in English and Chinese.
Abstract in English --- p.ii
Abstract in Chinese --- p.v
Glossary --- p.viii
Acknowledgements --- p.x
Publications Arising From this Thesis --- p.xii
List of Tables --- p.xviii
List of Figures --- p.xix
Chapter 1 --- INTRODUCTION --- p.1
Chapter 1.1 --- Definition of Heart Rate Variability --- p.1
Chapter 1.2 --- Physiology --- p.1
Chapter 1.2.1 --- Review of Autonomic Nervous System and Influence of Heart Rate --- p.1
Chapter 1.2.2 --- The Role of Baroreceptors in the Control of Circulation --- p.4
Chapter 1.2.3 --- The Control and Physiological Importance of Heart Rate --- p.7
Chapter 1.2.3.1 --- Normal Heart Rate --- p.7
Chapter 1.2.3.2 --- Autonomic Control of Heart Rate --- p.8
Chapter 1.2.3.2.1 --- Sympathetic Effects --- p.8
Chapter 1.2.3.2.2 --- Vagal Effects --- p.8
Chapter 1.2.3.3 --- Reflexes Influencing Heart Rate --- p.9
Chapter 1.2.3.3.1 --- Baroreceptors --- p.10
Chapter 1.2.3.3.2 --- Chemoreceptors --- p.10
Chapter 1.2.3.3.3 --- Atrial Receptors --- p.11
Chapter 1.2.3.3.4 --- Coronary Chemoreflex --- p.11
Chapter 1.2.3.3.5 --- Other Reflexes --- p.12
Chapter 1.2.3.4 --- Influence of Complex Events on Heart Rate --- p.12
Chapter 1.2.3.4.1 --- Respiratory Influence --- p.12
Chapter 1.2.3.4.2 --- Effects of Decreases in Venous Return --- p.13
Chapter 1.2.3.4.3 --- Exercise --- p.13
Chapter 1.2.3.5 --- Physiological Importance of Heart Rate --- p.14
Chapter 1.3 --- Spectral Analysis of Blood Pressure and Heart Rate Variability in Evaluating Cardiovascular Regulation --- p.14
Chapter 1.4 --- Clinical Relevance --- p.15
Chapter 1.4.1 --- Increased Sympathetic Activity --- p.15
Chapter 1.4.2 --- Reduced Parasympathetic Activity --- p.15
Chapter 1.4.3 --- Low Heart Rate Variability --- p.16
Chapter 1.4.4 --- Depressed Baroreflex Sensitivity --- p.17
Chapter 1.4.5 --- Prognostic Value of Heart Rate Variability in Disease States --- p.17
Chapter 1.4.6 --- Abnormality of Autonomic Nervous System in Heart Failure --- p.17
Chapter 2 --- METHODS FOR ASSESSING HEART RATE VARIABILITY --- p.20
Chapter 2.1 --- Time Domain Analysis of Heart Rate Variability --- p.20
Chapter 2.1.1 --- Statistical Methods --- p.21
Chapter 2.1.2 --- Geometric Methods --- p.22
Chapter 2.2 --- Spectral Analysis of Heart Rate Variability --- p.23
Chapter 2.3 --- "Nonlinear Indices (fractal, entropy, chaos theory)" --- p.27
Chapter 3 --- HEART FAILURE --- p.28
Chapter 3.1 --- Heart Rate Variability in Heart Failure --- p.28
Chapter 3.2 --- Effect of Changes in Respiratory Frequency and Posture on Heart Rate Variability Analysis in Heart Failure --- p.34
Chapter 3.3 --- Effect of Respiratory Rates on Baroreceptor Function in Heart Failure --- p.34
Chapter 3.4 --- Effect of Treatment on Heart Rate Variability in Heart Failure Patients --- p.35
Chapter 4 --- AIMS --- p.39
Chapter 4.1 --- Effect of Changes in Respiratory Frequency and Posture on Heart Rate Variability --- p.39
Chapter 4.2 --- Effect of Slow Breathing --- p.39
Chapter 4.3 --- Effect of Therapeutic Interventions in Chronic Heart Failure --- p.39
Chapter 4.3.1 --- A Comparison of Celiprolol with Metoprolol --- p.39
Chapter 4.3.2 --- A Comparison of Carvedilol with Metoprolol --- p.40
Chapter 5 --- STUDIES --- p.41
Chapter 5.1 --- Impact of Changes in Respiratory Frequency and Posture on Power Spectral Analysis of Heart Rate and Systolic Blood Pressure Variability in Normal Subjects and Patients with Heart Failure --- p.41
Chapter 5.1.1 --- Subjects --- p.41
Chapter 5.1.2 --- Recording Technique and Protocol --- p.42
Chapter 5.1.3 --- Signal Acquisition --- p.42
Chapter 5.1.4 --- Power Spectral Analysis --- p.43
Chapter 5.1.5 --- Statistical Analysis --- p.46
Chapter 5.1.6 --- Results --- p.46
Chapter 5.1.7 --- Discussion --- p.52
Chapter 5.1.8 --- Summary --- p.56
Chapter 5.2 --- Slow Breathing Increases Arterial Baroreflex Sensitivityin Patients with Chronic Heart Failure --- p.57
Chapter 5.2.1 --- Subjects --- p.57
Chapter 5.2.2 --- Assessment of Baroreflex Sensitivity --- p.57
Chapter 5.2.3 --- Statistical Analysis --- p.58
Chapter 5.2.4 --- Results --- p.59
Chapter 5.2.5 --- Discussion --- p.62
Chapter 5.2.6 --- Summary --- p.63
Chapter 5.3 --- β-Blockers in Heart Failure: a Comparison of a Vasodilating β- Blocker with Metoprolol on Heart Rate Variability by 24 Hour ECG Recordings (Time-Domain & Spectral Analysis) --- p.65
Chapter 5.3.1 --- Trial Design --- p.65
Chapter 5.3.2 --- Study Patients --- p.65
Chapter 5.3.3 --- Study Measurements --- p.66
Chapter 5.3.4 --- Statistical Analysis --- p.67
Chapter 5.3.5 --- Results --- p.67
Chapter 5.3.6 --- Discussion --- p.80
Chapter 5.3.7 --- Summary --- p.81
Chapter 5.4 --- Effect of β-Blockade on Baroreceptor and Autonomic Function in Heart Failure-Assessment by Short Term Spectral Analysis --- p.83
Chapter 5.4.1 --- Trial Design and Study Patients --- p.83
Chapter 5.4.2 --- Recording Technique and Protocol --- p.83
Chapter 5.4.3 --- "Signal Acquisition, Power Spectral Analysis and Cross Spectral Analysis" --- p.83
Chapter 5.4.4 --- Reproducibility --- p.84
Chapter 5.4.5 --- Statistical Analysis --- p.84
Chapter 5.4.6 --- Results --- p.84
Chapter 5.4.7 --- Discussion --- p.93
Chapter 5.4.8 --- Summary --- p.97
Chapter 5.5 --- β-Blockade in Heart Failure: A Comparison of Carvedilol with Metoprolol on HRV by 24 hour ECG Recordings (Time-Domain & Spectral Analysis) --- p.98
Chapter 5.5.1 --- Trial Design and Patient Demographics --- p.98
Chapter 5.5.2 --- Study Measurements --- p.98
Chapter 5.5.3 --- Statistical Analysis --- p.99
Chapter 5.5.4 --- Results --- p.99
Chapter 5.5.5 --- Discussion --- p.105
Chapter 5.5.6 --- Conclusions --- p.107
Chapter 5.6 --- Comparison of Carvedilol and Metoprolol on Baroreceptor Gain in Heart Failure by Short Term Spectral Analysis --- p.108
Chapter 5.6.1 --- Study Design --- p.108
Chapter 5.6.2 --- Study Patients --- p.108
Chapter 5.6.3 --- Recording Technique and Protocol --- p.108
Chapter 5.6.4 --- "Signal Acquisition, Power Spectral Analysis and Cross Spectral Analysis" --- p.108
Chapter 5.6.5 --- Statistical Analysis --- p.109
Chapter 5.6.6 --- Results --- p.109
Chapter 5.6.7 --- Discussion --- p.112
Chapter 5.6.8 --- Summary --- p.112
Chapter 6 --- "GENERAL DISCUSSION, LIMITATIONS & CONCLUSIONS" --- p.113
Chapter 6.1 --- Discussion --- p.113
Chapter 6.2 --- Conclusions --- p.117
Chapter 7 --- REFERENCES --- p.119
Huang, Yu-Chen, and 黃于珍. "Clustering Heart Beats Using Heart Rate Variability." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/85524778639002113871.
Full text元智大學
資訊管理學系
96
This study proposes a method to cluster RR Interval time series. First,the distance of any two RR Interval time series is defined based on eight statistic features of Heart Rate Variability (including Mean, SDNN, SDNN Index, SDANN, RMSSD, CV, pNN50 and pNN20). Then, RR Interval time series are clustered based on this distance. Experimental results with various datasets indicate that this method can effectively distinguish different types of RR Interval time series.
Cimponeriu, Laura Elena. "Dynamics of heart rate variability." Thesis, 1999. http://nemertes.lis.upatras.gr/jspui/handle/10889/3191.
Full textBarquero, Pérez Óscar. "Heart rate variability : a fractal analysis." Master's thesis, 2008. http://hdl.handle.net/10216/11023.
Full text