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1
Uhlig, Stefan. "Heart Rate Variability". Doctoral thesis, Universitätsbibliothek Chemnitz, 2018. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-233101.
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Ein gesunder Herzschlag zeichnet sich nicht dadurch aus, dass er besonders regelmäßig ist. Vielmehr sollte ein gesunder Herzschlag, selbst in Phasen augenscheinlicher körperlicher Inaktivität, variabel sein (z.B. Appelhans & Luecken, 2006; Berntson et al., 1997; Shaffer, McCraty, & Zerr, 2014). Historisch gesehen ist dies keine völlig neue Erkenntnis – bereits in der frühen chinesischen und griechischen Medizin konnte dieses Phänomen beobachtet werden (einen schönen Überblick hierzu gibt Billman, 2011). Das Zusammenwirken der sympathischen und parasympathischen Bestandteile des autonomen Nervensystems, welches sich unter anderem in der Herzratenvariabilität (HRV) widerspiegelt, erlaubt uns nicht nur Einblicke in die physiologische Adaptionsfähigkeit, sondern auch in die psychische Flexibilität und Regulationsfähigkeit des Menschen, um so auf sich ständig ändernde Umweltanforderungen angemessen reagieren zu können (z.B. Appelhans & Luecken, 2006; Beauchaine, 2001; ChuDuc, NguyenPhan, & NguyenViet, 2013; Porges, 1995b; Quintana & Heathers, 2014; Riganello, Garbarino, & Sannita, 2012; Shaffer et al., 2014; Stein & Kleiger, 1999; Thayer & Lane, 2000). Mit ganz einfachen Worten: Die Variabilität unseres Herzschlages stellt eine Art Interface dar, welches Auskunft über das Zusammenspiel physiologischer und psychologischer Prozesse gibt.
In der vorliegenden Monografie beschäftige ich mich intensiv mit dem Thema HRV, insbesondere mit der Anwendung und Durchführung von HRV-Kurzzeitmessungen (meistens fünf Minuten) im Kontext (bio-) psychologischer Forschung. Während ich im Rahmen des ersten Kapitels eine komprimierte Einführung in die Thematik und einen Überblick über die nachfolgenden Kapitel gebe, beschäftigt sich Kapitel II mit der Frage, welche methodischen Standards für HRV-Kurzzeitmessungen derzeit vorliegen. Ausgangspunkt hierfür sind vereinzelte Hinweise (z.B. im Rahmen meta-analytischer Bestrebungen) darauf, dass die Erfassung, Darstellung und Interpretation von HRV-Messungen durch ein nicht unerhebliches Maß an Diversität gekennzeichnet ist (z.B. de Vries, 2013; Ellis, Zhu, Koenig, Thayer, & Wang, 2015; Quintana & Heathers, 2014; Tak et al., 2009; Zahn et al., 2016). Ferner fehlen bis heute belastbare Normwerte für die gängigsten HRV-Parameter, die typischerweise in Kurzzeitmessungen berechnet werden können (vgl. Nunan, Sandercock, & Brodie, 2010). Ausgehend von diesen Beobachtungen stellen wir ein systematisches Literaturreview vor. In einem ersten Schritt haben wir aktuelle Standards zur Erhebung und Auswertung von HRV-Messungen identifiziert, auf deren Basis wir ein Klassifikationssystem zur Beurteilung von HRV-Studien erstellt haben. Nachfolgend wurden zwischen 2000 und 2013 publizierte Artikel (N = 457), im Hinblick auf die extrahierten methodischen Standards, überprüft. Unsere Ergebnisse legen das Vorhandensein einer beträchtlichen methodischen Heterogenität und einen Mangel an wichtigen Informationen nahe (z.B. in Bezug auf die Erhebung essentieller Kontrollvariablen oder das Berichten von HRV-Parametern), einhergehend mit der Tatsache, dass sich gängige Empfehlungen und Richtlinien (z.B. Task Force, 1996) nur partiell in der empirischen Praxis wiederfinden. Auf der Grundlage unserer Ergebnisse leiten wir Empfehlungen für weitere Forschung in diesem Bereich ab, wobei sich unsere „Checkliste“ besonders an forschende Psychologen richtet. Abschließend diskutieren wir die Einschränkungen unseres Reviews und unterbreiten Vorschläge, wie sich diese - bisweilen unbefriedigende - Situation verbessern lässt.
Während unserer umfangreichen Literaturrecherche ist uns sehr schnell aufgefallen, dass HRV-Kurzzeitmessungen auf ein breites wissenschaftliches Interesse stoßen, wobei verschiedenste Konzepte und Forschungsfragen mit spezifischen HRV-Mustern in Verbindung gebracht werden (vgl. Beauchaine, 2001; Dong, 2016; Francesco et al., 2012; Makivić, Nikić, & Willis, 2013; Nunan et al., 2010; Pinna et al., 2007; Quintana & Heathers, 2014; Sammito et al., 2015; Sandercock, 2007). Darunter befinden sich sowohl eher eigenschaftsähnliche (z.B. Trait-Angst; Miu, Heilman, & Miclea, 2009; Watkins, Grossman, Krishnan, & Sherwood, 1998) als auch stark situationsabhängige Konstrukte (z.B. akute emotionale Erregung; Lackner, Weiss, Hinghofer-Szalkay, & Papousek, 2013; Papousek, Schulter, & Premsberger, 2002). Während die beiden einflussreichsten Theorien zur HRV, die Polyvagal-Theorie (Porges, 1995b, 2001, 2007) und das Modell der neuroviszeralen Integration (Thayer & Lane, 2000, 2009), einen dispositionellen Charakter der HRV nahelegen, sind zahlreiche Einflussfaktoren bekannt, die unmittelbare Auswirkungen auf das autonome Nervensystem haben (Fatisson, Oswald, & Lalonde, 2016; Valentini & Parati, 2009). Demzufolge haben wir uns die Frage gestellt, wie zeitlich stabil individuelle HRV-Messungen sind (siehe Kapitel III). Da die existierende Literatur hierzu ambivalente Ergebnisse bereithält (Sandercock, 2007; Sandercock, Bromley, & Brodie, 2005) und die zeitliche Stabilität von HRV-Messungen bisher vornehmlich über sehr kurze Zeiträume mit wenigen Messzeitpunkten untersucht wurde (z.B. Cipryan & Litschmannova, 2013; Maestri et al., 2009; Pinna et al., 2007), haben wir eine längsschnittliche Studie mit fünf Messzeitpunkten, verteilt auf ein Jahr, konstruiert (N = 103 Studierende). In Abhängigkeit von der Körperhaltung der Probanden während der Messung (liegend, sitzend, stehend), haben wir nachfolgend die Retest-Reliabilität (absolute und relative Reliabilität; siehe Atkinson & Nevill, 1998; Baumgartner, 1989; Weir, 2005) der gängigsten HRV-Parameter ermittelt. Unsere Ergebnisse deuten auf ein beachtliches Ausmaß an Zufallsschwankungen der HRV-Parameter hin, welches weitgehend unabhängig von der Körperhaltung der Probanden und dem zeitlichen Abstand der Messzeitpunkte ist. Da diese Ergebnisse weitreichende Folgen suggerieren, diskutieren wir diese, unter Berücksichtigung vorhandener Einschränkungen, ausführlich.
Während in Kapitel II und III vornehmlich methodische Fragen im Fokus stehen, stelle ich in Kapitel IV dieser Monografie eine Feldstudie vor. Im Rahmen dieser Studie haben wir die Zusammenhänge zwischen subjektivem Stress, Coping-Strategien, HRV und Schulleistung untersucht. Sowohl die bereits erwähnten Theorien (Porges, 1995b, 2001, 2007, Thayer & Lane, 2000, 2009), als auch eine beträchtliche Anzahl an Forschung, lassen Zusammenhänge zwischen HRV und Stress (z.B. Berntson & Cacioppo, 2004; Chandola, Heraclides, & Kumari, 2010; Krohne, 2017; Michels, Sioen, et al., 2013; Oken, Chamine, & Wakeland, 2015; Porges, 1995a; Pumprla, Howorka, Groves, Chester, & Nolan, 2002) sowie HRV und kognitiver Leistung vermuten (z.B. Duschek, Muckenthaler, Werner, & Reyes del Paso, 2009; Hansen, Johnsen, & Thayer, 2003; Luque-Casado, Perales, Cárdenas, & Sanabria, 2016; Shah et al., 2011). Allerdings fehlt es bislang an Studien, welche die komplexeren Zusammenhänge zwischen all den genannten Konstrukten untersuchen. Dies gilt insbesondere für die Untersuchung von Kindern und Jugendlichen. Um zur Schließung dieser Wissenslücke beizutragen, haben wir Gymnasiasten (N = 72, zwischen zehn und 15 Jahren alt) im Rahmen eine Querschnittstudie zu deren Stresserleben und Bewältigungsstrategien (mittels SSKJ 3-8; Lohaus, Eschenbeck, Kohlmann, & Klein-Heßling, 2006) befragt. Außerdem wurden bei all diesen Schülern HRV und Zeugnisdurchschnittsnoten erhoben. Unsere Ergebnisse unterstreichen die Bedeutung konstruktiver Coping-Strategien zur Vermeidung von physischen und psychischen Stresssymptomen, welche ihrerseits negative Auswirkungen auf die Schulleistung haben. Demgegenüber lassen sich die erwarteten Zusammenhänge zwischen HRV und Stress/Coping (Berntson & Cacioppo, 2004; Dishman et al., 2000; Fabes & Eisenberg, 1997; Lucini, Di Fede, Parati, & Pagani, 2005; Michels, Sioen, et al., 2013; O’Connor, Allen, & Kaszniak, 2002; Porges, 1995a) sowie HRV und kognitiver Leistung (Hansen et al., 2003; Suess, Porges, & Plude, 1994; Thayer, Hansen, Saus-Rose, & Johnsen, 2009) anhand unserer Daten nicht bestätigen. Mögliche Gründe für dieses Befundmuster sowie Anforderungen an zukünftige Studien dieser Art werden abschließend diskutiert.
Schlussendlich (a) fasse ich alle gesammelten Erkenntnisse prägnant zusammen, (b) diskutiere deren Implikationen, (c) stelle deren Beitrag zum wissenschaftlichen Forschungsstand heraus, und (d) gebe einen kurzen Einblick in die jüngsten Entwicklungen der HRV-Forschung (Kapitel V). Außerdem, und damit schließe ich den inhaltlichen Part dieser Monografie ab, möchte ich den Leser an meinen zehn wichtigsten Lernerfahrungen teilhaben lassen.
2
Sattar, Nedal Abdul. "Heart rate variability in man". Thesis, University of Edinburgh, 1989. http://hdl.handle.net/1842/30723.
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Kurths, Jürgen, A. Voss, Annette Witt, P. Saparin, H. J. Kleiner i N. Wessel. "Quantitative analysis of heart rate variability". Universität Potsdam, 1994. http://opus.kobv.de/ubp/volltexte/2007/1347/.
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In the modern industrialized countries every year several hundred thousands of people die due to the sudden cardiac death. The individual risk for this sudden
cardiac death cannot be defined precisely by common available, non-invasive diagnostic tools like Holter-monitoring, highly amplified ECG and traditional linear analysis of heart rate variability (HRV). Therefore, we apply some rather unconventional methods of nonlinear dynamics to analyse the HRV.
Especially, some complexity measures that are basing on symbolic dynamics as well as a new measure, the renormalized entropy, detect some abnormalities in the HRV of several patients who have been classified in the low risk group by traditional methods. A combination of these complexity measures with the parameters in the frequency domain seems to be a promising way to get a more precise definition of the individual risk. These findings have to be validated
by a representative number of patients.
4
Migeotte, 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.
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Berndtsson, Andreas. "Heart Rate Variability Biofeedback for Android". Thesis, KTH, Medicinsk teknik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-136687.
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Heart rate variability (HRV) is the variations in time between consecutive heart beats, and reflects the functioning of the autonomic nervous system. Not only is HRV a good marker for many physiological disorders, but it is well known that HRV can be altered consciously by different approaches even though it is controlled by the autonomic nervous system. Respiration is an important factor in modulating HRV and this property is utilized in HRV biofeedback, which is a method that aims at increasing heart rate variability. HRV biofeedback systems typically measures heart rate variability and display the parameters on a screen, enabling the user to gain control and increase heart rate variations. In this thesis a software for biofeedback of heart rate variability is presented. The software was implemented for Android and runs on a tablet computer to make the biofeedback system portable and more accessible than most other biofeedback systems. The developed software has proven to be fully functional in real-time providing the user with reliable information. A small pilot study on healthy volunteers has also been made to evaluate the effects of the biofeedback training. These measurements give a preliminary indication that biofeedback session with the proposed solution increases HRV. However, a more comprehensive study with a larger population needs to be carried out in order to confidently confirm the positive effects of biofeedback sessions with the software.Heart 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.
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Heathers, James. "Methodological improvements in heart rate variability". Thesis, The University of Sydney, 2014. http://hdl.handle.net/2123/13106.
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Heart rate variability (HRV) refers to the amplitude and period of fluctuations in the heart rate over time. HRV is an accessible, low-cost and straightforward technique for measuring autonomic outflow, but also a complicated epiphenomena of interacting autonomic, circulatory and respiratory factors. Confusion about the meaning of HRV is reflected in the literature establishing basic HRV theory, and in the applied literature which uses HRV as a dependent variable or predictor of psychological outcomes. Here, 2 straightforward issues present themselves: 1) best-case practice for methodological implementation is not being followed, and 2) sample sizes for between-subjects investigations of phenomena where HRV is a dependent variable are underpowered. Specifically addressing the above; 1) an attempt is made to a) understand and codify a best-case practice for methodological control in biobehavioural research, and b) investigate profound but common sources of error in HRV recording; 2) rationale for the development and field testing of a device which allows mass collection of HRV records from experimental participants is outlined. Best-case practice for experimental implementation is recommended: the use of within-subjects data, the consideration of the nature of ‘baseline’ periods against which experimental conditions are compared, and respiratory monitoring within participants to control for occasional or whole-sample artifacts. Current research is not well controlled – theoretical, statistical and practical errors are widely observed. For addressing experimental power, pulse monitoring shows acceptable reliability over time, and the device developed (a smartphone-based pulse rate monitor) shows excellent accuracy in comparison to conventional measurement. A novel solution for correcting pulse to pulse intervals is offered which improves measurement accuracy and performs well in field trials of mass-collected data.
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Litster, 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.
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Zapanta, 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.
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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.Includes 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.
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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.
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Insomnia is one of the most common complaints in medical practice and the sleep disorder of highest prevalence. At least 10% of the worldwide population has chronic insomnia, which has been associated with a range of negative health outcomes. Within the clinical setting, patient subtypes have been defined according to symptomology. More recently insomnia researchers have proposed phenotypes based on total sleep time during overnight polysomnography (PSG). Short-sleeping insomnia patients are purported to be a biologically severe phenotype at higher risk of cardiovascular morbidity, poor mental health, and obesity (compared to healthy controls). Heart rate variability (HRV) is an objective marker that provides insight into autonomic nervous system dynamics. The overarching aim of my research was to explore a large clinical sample of patients with Insomnia Disorder to determine whether differences in HRV exist during sleep in empirically-derived insomnia patient subtypes. The aim of the work presented within Chapter 2 was to identify all previous insomnia-HRV research to determine if HRV was impaired in adult patients with insomnia, and whether treatments altered HRV. A systematic review of five web databases located 22 relevant articles; 17 case-control studies and 5 interventions studies. Results were difficult to synthesise due to incomparable methodology and reporting. There was a high risk of bias in the majority of studies. It was concluded that although HRV impairment in insomnia may be a widely-accepted concept, it is not supported by research nor has it been determined if it varies after treatment or according to patient subtype. The aim of the first empirical study of the thesis (Chapter 3) was to objectively-derive insomnia patient subtypes and evaluate their physiological signals (HRV and electroencephalography [EEG]) during sleep onset. Patients (n = 96) with clinically-diagnosed Insomnia Disorder underwent overnight PSG to determine sleep metrics for cluster analysis using Ward’s method: Total Sleep Time (TST), Wake After Sleep Onset (WASO) and Sleep Onset Latency (SOL). Electrocardiogram (ECG) from the PSG was extracted in the 10 minutes before and after sleep onset. After R-wave detection, the ECG was visually checked and manually corrected as required. Six time and frequency-domain HRV measures were analyzed; heart rate (HR), standard deviation of all N-N intervals (SDNN), root mean square of successive R-R intervals (RMSSD), percentage of successive R-R intervals that differ by > 50 ms (PNN50), high frequency (HF), and low frequency (LF)/HF ratio. Cluster analysis derived two solutions; one comprising two subtypes and another with three subtypes. The two cluster solution consisted of insomnia with short-sleep duration (I-SSD: n = 43) and insomnia with normal objective sleep duration (I-NSD: n = 53). At sleep onset, between-group HRV analysis revealed reduced parasympathetic activity (PNN50 and RMSSD) in the short-sleeping subtype. This was not mirrored by significant increases in HR and/or the LF/HF ratio. These findings suggested that reduced parasympathetic activity during sleep onset might contribute to poor cardiometabolic health outcomes previously reported in short-sleeping insomnia patients. The final component of this thesis was a case-control study (Chapter 4) which examined whether HRV measures differed between insomnia subtypes across the nocturnal period. It was hypothesized that short-sleeping insomnia patients would have impaired HRV compared to normal-sleep duration insomnia patients, consistent with differences observed at sleep onset (Chapter 3). Insomnia patients underwent overnight PSG, which provided sleep metrics for cluster analysis and ECG for HRV analysis. ECG was visually checked for accurate R-wave detection, and manually corrected as required. HRV analysis was performed from lights-off to lights-on (and separately by sleep/wake stage) using time and frequency-domain measures. Differences in HRV measures (HR, SDNN, RMSSD, LF, HF, LF/HF) were tested between the subtypes using General Linear Models controlling for age as a core confounder. Short-sleeping insomnia patients (I-SSD: n = 34; 45.5 ± 10.5 years) and normal-sleep duration insomnia patients (I-NSD: n = 41; 37.6 ± 10.9 years) were included in the HRV analysis. There were no statistically significant nocturnal HRV differences between subtypes after controlling for age. As such, short-sleeping insomnia patients did not have statistically significant reductions in HRV measures representative of parasympathetic activity.«br /» In summary, there was a lack of persistent nocturnal HRV disparities (between empirically-derived insomnia patient subtypes) that extended beyond sleep onset in this large clinical sample of patients with Insomnia Disorder. The central tenet of 24-hour hyperarousal amongst short-sleep duration insomnia patients cannot be supported by the combined findings of these two empirical studies. Post-hoc calculations revealed larger sample sizes would be required to determine a small to medium effect size difference in nocturnal HRV between insomnia patient subtypes. Until this time, the directional relationship between insomnia, heart rate variability, hyperarousal and cardiovascular disease remains unclear in the heterogeneous insomnia population.
10
Zemánek, 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.
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The analysis of HRV is an advanced and noninvasive method which is used to investigate the involuntary nervous system. It is also one of the important parameters of its proper function. Heart rate variability can also be analyzed by entropy, which studies the discrepancy of the RR intervals of the HRV signal and thus can be used to diagnose cardiac diseases
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Alghoul, Karim. "Heart Rate Variability Extraction from Video Signals". Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/33003.
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Heart Rate Variability (HRV) analysis has been garnering attention from researchers due to its wide range of applications. Medical researchers have always been interested in Heart Rate (HR) and HRV analysis, but nowadays, investigators from variety of other fields are also probing the subject. For instance, variation in HR and HRV is connected to emotional arousal. Therefore, knowledge from the fields of affective computing and psychology, can be employed to devise machines that understand the emotional states of humans. Recent advancements in non-contact HR and HRV measurement techniques will likely further boost interest in emotional estimation through . Such measurement methods involve the extraction of the photoplethysmography (PPG) signal from the human's face through a camera. The latest approaches apply Independent Component Analysis (ICA) on the color channels of video recordings to extract a PPG signal. Other investigated methods rely on Eulerian Video Magnification (EVM) to detect subtle changes in skin color associated with PPG.
The effectiveness of the EVM in HR estimation has well been established. However, to the best of our knowledge, EVM has not been successfully employed to extract HRV feature from a video of a human face. In contrast, ICA based methods have been successfully used for HRV analysis. As we demonstrate in this thesis, these two approaches for HRV feature extraction are highly sensitive to noise. Hence, when we evaluated them in indoor settings, we obtained mean absolute error in the range of 0.012 and 28.4.
Therefore, in this thesis, we present two approaches to minimize the error rate when estimating physiological measurements from recorded facial videos using a standard camera. In our first approach which is based on the EVM method, we succeeded in extracting HRV measurements but we could not get rid of high frequency noise, which resulted in a high error percentage for the result of the High frequency (HF) component. Our second proposed approach solved this issue by applying ICA on the red, green and blue (RGB) colors channels and we were able to achieve lower error rates and less noisy signal as compared to previous related works. This was done by using a Buterworth filter with the subject's specific HR range as its Cut-Off.
The methods were tested with 12 subjects from the DISCOVER lab at the University of Ottawa, using artificial lights as the only source of illumination. This made it a challenge for us because artificial light produces HF signals which can interfere with the PPG signal. The final results show that our proposed ICA based method has a mean absolute error (MAE) of 0.006, 0.005, 0.34, 0.57 and 0.419 for the mean HR, mean RR, LF, HF and LF/HF respectively. This approach also shows that these physiological parameters are highly correlated with the results taken from the electrocardiography (ECG).
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Thapa, Rinku. "Heart Rate Variability in Autism Spectrum Disorder". Thesis, University of Sydney, 2020. https://hdl.handle.net/2123/22968.
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Autism Spectrum Disorders (ASD) are a group of pervasive neurodevelopmental disorders characterised by qualitative impairments in social functioning. Studies over the last three decades have revealed relationships between autonomic dysregulation, indexed by decreased Heart Rate Variability (HRV), and cardiovascular risk in children and adults diagnosed with ASD. HRV is an objective marker that provides physiological insight into the Autonomic Nervous System (ANS). Decreases in HRV are purported to be a risk factor for cardiovascular morbidity, mortality, and poor mental health. The overarching objective of this thesis was to explore and compare resting-state HRV parameters between individuals diagnosed with ASD and neurotypical controls. This thesis focuses on empirical work examining the physiological measure of HRV as an index of cardiac autonomic function in adults and children diagnosed with ASD to better understand how HRV may contribute to poor physical, psychological, and social well-being. Chapter 1 of this thesis provides a detailed review of the extant literature surrounding HRV and autonomic functioning in adults and children diagnosis with ASD, compared to neurotypical controls, within which the subsequent empirical studies (Chapter 2 and 3) are couched. Chapter 2 presents an empirical study investigating differences in resting-state HRV parameters between adults diagnosed with ASD, relative to neurotypical adults. The main objective of Chapter 2 was to understand whether participants diagnosed with ASD demonstrate reductions in HRV in comparison to neurotypical individuals. It was proposed that there would be a reduction in HRV in the ASD group, and that this reduction would be particularly evident in HRV measures associated with predominantly parasympathetic activity. Furthermore, we hypothesised that reduced resting-state HRV would be associated with individuals taking psychotropic medication use. Finally, Chapter 2 investigated whether the presence of psychiatric comorbidities in the ASD group was also associated with reductions in HRV. Chapter 3 then examined the role of HRV in a younger cohort of children with ASD, relative to neurotypical children. The core objective of Chapter 3 was to identify whether HRV was reduced in children diagnosed with ASD, and the potential association between psychotropic medication use and HRV in children with ASD. It was hypothesized that children diagnosed with ASD would show decreased HRV compared to neurotypical children. Chapter 4 consolidates the results and present overall implications from the empirical studies presented within the thesis. The cumulative research presented in this thesis suggests that decreased HRV is associated with autonomic dysregulation in ASD. These findings provide additional evidence for the role of autonomic functioning in the pathogenesis of ASD. Moreover, the studies contribute to our understanding of the potential physiological mechanisms that may lead to cardiovascular risks in individuals with ASD. These studies provide support for our hypothesis that a reduction in HRV may contribute to dysregulation in autonomic cardiac control in ASD population.
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Persson, 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.
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Studies have reported that around 20 % of all traffic accidents are caused by a sleepy driver. Sleepy driving has been compared to drunk driving. A sleepy driver is also an issue in the case of automated vehicles in the future. Handing back the control of the vehicle to a sleepy driver is a serious risk. This has increased the need for a sleepiness estimation system that can be used in the car to warn the driver when driving is not recommended. One commonly used method to estimate sleepiness is to study the heart rate variability, HRV, which is said to reflect the activity of the autonomous nervous system, the ANS. The HRV can be expressed through different measures obtained from a signal of RR-intervals. The aim with the thesis is to investigate how well the HRV translates into sleepiness estimation and how the experimental setup might affect the results. In this study, HRV data from 85 sleep deprived drivers was collected together with the drivers’ own ratings of their sleepiness according to the nine graded Karolinska sleepiness scale, KSS. An ANOVA test showed statistical significance for almost all of the used HRV measures when the Driver ID was set as random variable. In order to reduce the number of HRV measures, a feature selection step was performed before training a Support Vector Machine (SVM) used for classification of the data. SVM classifiers are trained to use the input features describing the data to optimize hyperplanes separating the discrete set of classes. Previous research has shown good results in using HRV for sleepiness detection, but common issues are the small data sets used and that most experiments are performed in a simulator instead of at real roads. In some cases, no sleep deprivation is used. The result from the classification in this study is a mean accuracy of around 58-59 %, mean sensitivity of 50-51 %, mean specificity of 75-76 % and mean F1 score of 50-51 % over the three classes ’Alert’, ’Getting sleepy’ and ’Sleepy’. This together with the results of the ANOVA test shows that the HRV measures performed relatively poor when used for classification of the data and that there are large inter-individual differences. This suggests the use of personalized algorithms when developing a sleepiness estimation system and an investigation regarding how other confounding factors could affect the estimation is also motivated.
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Williams, 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.
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Muskett, 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.
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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.Master 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.
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Ho, Ian-ian, i 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.
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Clifford, 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.
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Heart rate variability (HRV), the changes in the beat-to-beat heart rate calculated from the electrocardiogram (ECG), is a key indicator of an individual's cardiovascular condition. Assessment of HRV has been shown to aid clinical diagnosis and intervention strategies. However, the variety of HRV estimation methods and contradictory reports in this field indicate that there is a need for a more rigorous investigation of these methods as aids to clinical evaluation. This thesis investigates the development of appropriate HRV signal processing techniques in the context of pilot studies in two fields of potential application, sleep and head-up tilting (HUT). A novel method for characterising normality in the ECG using both timing information and morphological characteristics is presented. A neural network, used to learn the beat-to-beat variations in ECG waveform morphology, is shown to provide a highly sensitive technique for identifying normal beats. Fast Fourier Transform (FFT) based frequency-domain HRV techniques, which require re-sampling of the inherently unevenly sampled heart beat time-series (RR tachogram) to produce an evenly sampled time series, are then explored using a new method for producing an artificial RR tachogram. Re-sampling is shown to produce a significant error in the estimation of an (entirely specified) artificial RR tachogram. The Lomb periodogram, a method which requires no re-sampling and is applicable to the unevenly sampled nature of the signal is investigated. Experiments demonstrate that the Lomb periodogram is superior to the FFT for evaluating HRV measured by the LF/HF-ratio, a ratio of the low to high frequency power in the RR tachogram within a specified band (0.04-0.4 Hz). The effect of adding artificial ectopic beats in the RR tachogram is then considered and it is shown that ectopic beats significantly alter the spectrum and therefore must be removed or replaced. Replacing ectopic beats by phantom beats is compared to the case of ectopic-realted RR interval removal for the FFT and Lomb methods for varying levels of ectopy. The Lomb periodogram is shown to provide a signficantly better estimate of the LF/HF- ratio under these conditions and is a robust method for measuring the LF/HF-ratio in the presence of (a possibly unknown number of) ectpoic beats or artefacts. The Lomb peridogram and FFT-based techniques are applied to a database of sleep apnoeic and normal subjects. A new method of assessing HRV during sleep is proposed to minimise the confounding effects on HRV of changes due to changing mental activity. Estimation of LF/HF-ratio using the Lomb technique is shown to separate these two patient groups more effectively than with FFT-based techniques. Results are also presented for the application of these methods to controlled (HUT) studies on subjects with syncope, an autonomic nervous system problem, which indicate that the techniques developed in this thesis may provide a method for differentiating between sub-classes of syncope.
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Channell, Rachel Marie. "The Associations of Extraversion and Heart Rate Variability". BYU ScholarsArchive, 2021. https://scholarsarchive.byu.edu/etd/9001.
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Heart rate variability as a measure of cardiovascular health and autonomic activity correlates with psychological resiliency but is not consistently related to trait extraversion, a strong predictor of emotional well-being. This study intends to clarify research findings about trait extraversion and heart rate variability by identifying the context and nature of the relationship between extraversion and physiological responses. As a secondary analysis of data from a study comparing biofeedback and compassionate breathing, extraversion scores were compared with heart rate variability data at three different points including prior to a stressor, during exposure to a stressor, and recovery to a stressor to determine the influence of extraversion on stress reactivity and stress recovery. In our sample population of 80 participants who were mostly young and in good health determined by self-report, the average extraversion score 79.14. Linear regression was used to compare differences at each time point and data was analyzed for significance at p=.05; a post-hoc power analysis revealed β = .81, 1 – β. There were no significant findings between extraversion and heart rate variability at any time point. The results of this study support no relationship between extraversion, health, and stress-resiliency.
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Boone, 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/.
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Lucas, 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.
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Raymond, 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.
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Brouse, Chris J. "Monitoring nociception during general anesthesia with heart rate variability". Thesis, University of British Columbia, 2015. http://hdl.handle.net/2429/52851.
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We have developed a novel real-time cardiorespiratory coherence (CRC) algorithm to monitor nociception during general anesthesia. We have made two novel and significant contributions to the field.
We have developed a novel filter for measuring the respiratory sinus arrhythmia (RSA) in the heart rate variability (HRV) in real-time. The filter uses information from a secondary signal source (a respiration rate derived from a respiration signal) to track the RSA as it moves in time and frequency. It then uses this information to dynamically tune the centre frequency and bandwidth of a band-pass filter to isolate and measure the RSA. This filter is very effective at tracking the RSA in time and frequency, and it may provide the most robust measure of RSA yet devised.
We have integrated multiple signals and algorithms together into an end-to-end software system for robust continuous real-time nociception monitoring during general anesthesia. The software system incorporates not only our novel RSA filter to measure nociception, but also many peripheral algorithms for detecting and rejecting artifacts in the input signals. The input signals required for real-time nociception monitoring can be extremely noisy, and artifacts are a very significant challenge. To our knowledge, no other nociception monitor includes such robust artifact handling using redundant signal channels.
We estimated the sensitivity of our real-time CRC algorithm to nociception and antinociception, and compared it to traditional univariate HRV measures and standard clinical vital signs. Following ethics approval and informed parental consent, data were collected from 48 children receiving general anesthesia during dental surgery. A total of 42 dental dam insertion (nociception) and 57 anesthetic bolus (antinociception) events were noted. A nociception index was created for each HRV algorithm, ranging from 0 (no nociception) to 100 (strong nociception). Dental dam insertion changed the CRC nociception index by an average of 27 [95% CI from 21 to 33] (P < 0.000005), and a bolus dose of anesthetic changed it by an average of -19 [-27 to -12] (P < 0.00003). Real-time CRC was more sensitive to nociception and antinociception than were the traditional measures.Applied Science, Faculty of
Electrical and Computer Engineering, Department of
Graduate
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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.
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Mainardi, Amelia. "Heart Rate Variability and Oxytocin: Measures of Parasympathetic Control". Scholarship @ Claremont, 2014. http://scholarship.claremont.edu/scripps_theses/435.
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A large emphasis has been placed on determining the relationship between neurobiological state and social experience within the field of psychophysiology. Many of these studies have focused on the use of high frequency heart rate variability as a measure of parasympathetic control of autonomic function. Past studies have shown that administered oxytocin is a known effector of heart rate variability and neurobiological state and emphasized its potential to increase heart rate variability and the capacity for social engagement. This effect has been proposed in part to be the result of an interaction of the myelinated vagus with oxytocin. A similar relationship between increased levels of plasma oxytocin corresponding with increased high frequency heart rate variability was expected. This relationship expected to appear strongest in populations with highest levels of oxytocin or better heart health status, specifically in females as compared to males and in the younger population as compared to older. In a comparison of plasma oxytocin with heart rate variability values, plasma oxytocin level was found not to serve as a valid predictor variable. Additional comparisons using stress hormone levels suggest this lack of relationship is not attributable to sympathetic repression of parasympathetic control.
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Shafqat, 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.
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Puente, 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.
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Boman, 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.
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Wellbeing and subjective wellbeing (SWB) has become some the most important goals of our time, both individually and societally. Thus, there is a need for reliable ways to measure SWB, as concerns regarding many current measures have been raised. Due to the interwoven nature of physiology and psychology, heart rate variability (HRV) has the potential to assess psychological processes in a physiological manner. HRV is an attractive measure since it is inexpensive, easy and non-invasive. Hence, the aim is to, from a cognitive neuroscientific standpoint, investigate whether HRV could serve as an objective measure to assess SWB. Most studies demonstrate associations between HRV and SWB, in particular between high frequency (HF)-HRV and positive affect (PA). However, the one study fully matching the theoretical framework only showed an inverse correlation between HRV and negative affect (NA). Plausibly implying that HRV does not serve as a reliable measure of SWB, but may be able to indicate inverse associations with NA, and possibly index certain aspect of SWB such as deactivated PA. The study of the relationship between HRV and SWB is still in its infancy and results are inconsistent. The lack of common standards regarding measurements, implementation details, and variable values, make results difficult to compare and generalize. Further standardizations and research are much needed before accurate conclusions can be drawn.
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Minnis, James Michael. "Nutrition and athletic performance: implications of heart rate variability". Kansas State University, 2015. http://hdl.handle.net/2097/20344.
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Master of ScienceDepartment 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.
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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.
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Pace, 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.
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Thesis (Ph.D)--University of Tennessee Health Science Center, 1998.Title 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).
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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.
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Puente, 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.
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Plewa, Luke Joseph. "Sudden Cardiac Arrest Prediction through Heart Rate Variability Analysis". DigitalCommons@CalPoly, 2015. https://digitalcommons.calpoly.edu/theses/1449.
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The increase in popularity for wearable technologies (see: Apple Watch and Microsoft Band) has opened the door for an Internet of Things solution to healthcare. One of the most prevalent healthcare problems today is the poor survival rate of out-of hospital sudden cardiac arrests (9.5% on 360,000 cases in the USA in 2013). It has been proven that heart rate derived features can give an early indicator of sudden cardiac arrest, and that providing an early warning has the potential to save many lives. Many of these new wearable devices are capable of providing this warning through their heart rate sensors. This thesis paper introduces a prospective dataset of physical activity heart rates collected via Microsoft Band. This dataset is indicative of the heart rates that would be observed in the proposed Internet of Things solution. This dataset is combined with public heart rate datasets to provide a dataset larger than many of the ones used in related works and more indicative of out-of-hospital heart rates. This paper introduces the use of LogitBoost as a classifier for sudden cardiac arrest prediction. Using this technique, a five minute warning of sudden cardiac arrest is provided with 96.36% accuracy and F-score of 0.9375. These results are better than existing solutions that only include in-hospital data.
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Dixon, 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.
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Melchor, 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.
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The present doctoral thesis proposes a series of methods that have as a general objective the non-contact evaluation of heart rate variability (HRV) and respiratory rate (BR) through video imaging. The proposal of this technique has emerged in the last few years as an alternative to the traditional measurement systems, which assess these and other physiological parameters through direct contact with the person’s body. Due to this condition, the traditional systems may cause some complications in people who present a sensitive or fragile skin, such as neonates or patients with burn injuries.
Furthermore, although the video imaging technique could be an excellent alternative, as in the cases mentioned above, it also aims at being a monitoring instrument for the general population in non-clinical environments. In fact, nowadays, the use of electronic devices such as the video cameras, smartphones, tablets and others, it starts being part of a healthy lifestyle. Thus, this promising technique, which could provide advantages such as the contactless measurement, portability, easy use and low-cost, it could be employed in the near future as part of the evaluation of the person’s health status in everyday life.
On the other hand, despite the aforementioned advantages, the measurements obtained by this technique may be greatly affected by factors such as the movement of the person, lighting conditions, camera settings, among others. Hence, an analysis of the influence of various factors and conditions is carried out in this research study in order to obtain a better insight of the scope and limitations of the technique. For this purpose, a series of methods were developed and implemented in which face detection and tracking algorithms are employed, as well as image and signal processing techniques.
The results obtained in each study are evaluated by using various statistical parameters and plots with the aim of measuring the agreement between the proposed methods and the reference systems. In general, the statistical analysis carried out shows a good level of agreement between the measurement systems. It is important to note the presence of an impact on the results, to a greater or lesser extent, by the factors and conditions analyzed in the different studies. In several cases, the results show a significant improvement in comparison with the data reported in related studies. By contrast, the results achieved in scenarios with a greater presence of artifacts show a decrease in the agreement of the measurements.
This contactless technique may eventually become an instrument to detect physical or psychological disorders in the future. Nevertheless, its use for this purpose will depend on the progress of the technique over the coming years, since it is still in the research and development phase. Therefore, more improvements are necessary to reach the reliability achieved by the current reference systems and, particularly, if its application in real-life scenarios is considered. The development of more robust algorithms is required in order to suppress, as much as possible, the contribution of artifacts present in a real environment. Consequently, the acquisition of measurements in several real-life scenarios, longer recordings, and the analysis of more factors that could influence the performance of the technique constitute some objectives for future work.En 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
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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/.
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Depression is an independent risk factor for morbidity and mortality in patients with coronary artery disease (CAD). Altered autonomic nervous system (ANS) activity, a common feature of depression, is also a risk factor for cardiac events in patients with CAD. Heart rate variability (HRV) reflects ANS activity, and reduced HRV predicts morbidity in cardiac populations. The purpose of this study was to determine whether differences in HRV exist between depressed and nondepressed patients with CAD. Twenty-one depressed inpatients, with angiographically documented CAD were retrospectively matched to 21 nondepressed CAD patients by sex, age, and smoking status. Demographic, medical, psychological interview data, and 24-hour ECG recordings were obtained. Depressed subjects had significantly lower HRV, or trends toward lower HRV, than nondepressed subjects, even after controlling for severity of CAD. Subject groups did not differ on left ventricular ejection fraction, history of myocardial infarction, or any other relevant medical variable assessed. These results suggest that depression is associated with decreased HRV in patients with CAD, and may help to explain the increased rates of cardiac events observed in CAD patients with depression.
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Keeney, 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/.
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This study examined effectiveness of heart rate variability (HRV) biofeedback-assisted stress management training in reducing anxiety and stress in pregnant women and the effect of maternal stress management skills practice on fetal heart rate measures in real time. Participants were seven working pregnant women who volunteered in response to recruitment announcements and invitations from cooperating midwives. Reported state and trait anxiety and pregnancy specific stress were measured during five 45- to 50-minute training sessions. Training included bibliotherapy, instruction in the use of emotion-focused stress management techniques, and HRV biofeedback. Subjects used portable biofeedback units for home practice and were encouraged to practice the skills for 20 minutes a day and for short periods of time during stressful life events. At the end of training, fetal heart rate was monitored and concurrent maternal HRV measures were recorded. Repeated measures ANOVA and paired samples t-test analysis of study data revealed no statistically significant reductions in state or trait anxiety measures or in pregnancy specific stress measures. Partial eta squared (n²) and Cohen's d calculations found small to medium effect sizes on the various test scales. Friedman's analysis of variance of biofeedback measures showed a statistically significant decrease in low HRV coherence scores (X2 = 10.53, p = .03) and medium HRV coherence scores (X2 = 11.58, p = .02) and a statistically significant increase in high HRV coherence scores (X2 = 18.16, p = .001). This change is an indication of improved autonomic function. Results of concurrent maternal and fetal HRV recordings were generally inconclusive. A qualitative discussion of individual subject results is included. During follow-up interviews five subjects reported that they felt they were better able to cope with stress at the end of the study than at the beginning, that they used the stress management skills during labor, and that they continue to practice the skills in their daily lives.
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Keeney, 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.
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Newell, 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.
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Ballora, 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.
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This thesis draws from music technology to create novel sonifications of heart rate information that may be of clinical utility to physicians. Current visually-based methods of analysis involve filtering the data, so that by definition some aspects are illuminated at the expense of others, which are decimated. However, earlier research has demonstrated the suitability of the auditory system for following multiple streams of information. With this in mind, sonification may offer a means to display a potentially unlimited number of signal processing operations simultaneously, allowing correlations among various analytical techniques to be observed. This study proposes a flexible listening environment in which a cardiologist or researcher may adjust the rate of playback and relative levels of several parallel sonifications that represent different processing operations. Each sonification "track" is meant to remain perceptually segregated so that the listener may create an optimal audio mix. A distinction is made between parameters that are suited for illustrating information and parameters that carry less perceptual weight, which are employed as stream separators. The proposed sonification model is assessed with a perception test in which participants are asked to identify four different cardiological conditions by auditory and visual displays. The results show a higher degree of accuracy in the identification of obstructive sleep apnea by the auditory displays than by visual displays. The sonification model is then fine-tuned to reflect unambiguously the oscillatory characteristics of sleep apnea that may not be evident from a visual representation. Since the identification of sleep apnea through the heart rate is a current priority in cardiology, it is thus feasible that sonification could become a valuable component in apnea diagnosis.
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Strachan, Nicole Cecelia. "Baroreceptor sensitivity and heart rate variability in sport related concussions". Thesis, University of British Columbia, 2013. http://hdl.handle.net/2429/45255.
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Sports related concussions (SRC) have become a popular topic and more awareness and interest has risen towards this growing type of brain injury. The cardiovascular aspects of a concussion in particular baroreceptor sensitivity and heart rate variability need to be further investigated. Baroreceptor sensitivity (BRS) and heart rate variability (HRV) may be altered due to a biomechanical force to the brain stem, lesions or axonal stretching that occurs after a concussion. If the brain stem is damaged this may cause a disruption to the cardiovascular centers as they are located in the medulla oblongata. Six concussed athletes (5 males and 1 female) with sport- related concussion (age: 17.5± 2 years, BMI: 24 ± 1 kg/m²) and 6 healthy control-subjects (5 males and 1 female; age: 20 ± 2 years, BMI: 22 ± 2 kg/m²) participated by performing two rounds of stand squats at frequencies of 0.1Hz and 0.05Hz for 5 minutes. BRS and HRV are not altered after suffering from a SRC. Although this finding contrasts with the original hypothesis that there would be reduced BRS and abnormal HRV in sports related concussions, the issues of small sample size and marked within subject variability are acknowledged. Another likely possibility explaining the lack of notable differences is that, unlike severe head injury, a SRC is not enough of an injury to damage central control of the cardiovascular centers in the medullar regions of the brain and therefore efferent and afferent signal pathways remain intact and are capable of responding to different stressors maintaining BRS and HRV.
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Boardman, Anita. "The feasibility of using heart rate variability to detect distress". Thesis, University of Leicester, 2003. http://hdl.handle.net/2381/30206.
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The objective of this work is to look at the feasibility of using heart rate variability analysis as a method of improving discrimination between those fetuses suffering distress and those not.;Heart rate variability analysis was applied to data acquired from rats who had undergone asphyxia for set durations of up to 7 minutes. From analysis in both the time and frequency domain, it was possible to clearly identify the occurrence of the injury. Further correlations were made between these results, pH levels and neurological assessments for the different durations of asphyxia. It was found that during and following the injury, the pH and the heart rate decrease as expected, but the overall change in heart rate variability was much more pronounced. Some interesting results were also found for the shorter durations of asphyxia which will be looked at.;Fetal heart rate data was collected before and during labour in normal patients and variability analysis of the heart rate was performed. The acquisition of heart rate data using Doppler ultrasound is discussed and comparisons made between heart rate data acquired non-invasively using Doppler ultrasound and that acquired invasively using the scalp electrode during labour. It was found that providing the ultrasound signals did not suffer greater from noise, a reasonable comparison of beat-to-heat intervals and the time domain measure of heart rate variability was possible. The application of these results is discussed.;In conclusion, it has been found that it is feasible to detect asphyxial distress in rats using the standard deviation of 30 second intervals of heart beats. It has also been possible to collect fetal heart rate data and perform a similar heart rate variability analysis however further work needs to be undertaken to find out if this is predictive of distress in the fetus during labour.
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Frändén, 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.
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The connection between the heart and the brain was coined 150 years ago by Claude Bernard and has since then been an interesting topic of research. Scientists have for many years searched for biomarkers of stress and health to map the current status of the organism. Heart rate variability (HRV) has been presented as an emerging objective and promising marker to achieve just this. HRV refers to the beat-to-beat variations in heart rate (HR) and is thought to be a useful signal in understanding and providing valuable information of the autonomic nervous system (ANS). HRV has also been proposed as a marker of stress and health by sharing neural correlates and functions with several executive functions. This thesis identified several regions, including the ventromedial prefrontal cortex and the amygdala, in which significant associations across several studies were found between threat and safety perception, emotional regulation and HRV. This suggest that HRV may function as an index of the brain mechanism and structures that guide and govern adaptive functions and thus, provide researchers with valuable information regarding the stress and health of an organism. Two major theoretical frameworks, which articulate and explain the role of HRV as an indicator of individuals ability to adapt to environmental changes and cope under stress is presented. HRV can also be used in practice in several ways and a growing and promising field of application is HRV biofeedback.
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Fox, Sheilagh. "Client Experiences of a Brief Heart Rate Variability Biofeedback Protocol". BYU ScholarsArchive, 2020. https://scholarsarchive.byu.edu/etd/8621.
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This study investigated the experiences of clients who completed a brief heart rate variability biofeedback protocol. The purposes of this study were to (1) learn about client experiences of biofeedback because almost no previous research has done so and (2) explore the potential role of common factors in biofeedback. Fifteen clients were interviewed and their data analyzed according to the methods of Consensual Qualitative Research (CQR; Hill, 2012). CQR relies on the use of group consensus to construct representations of participant experiences and categorize themes within the data. The results of the study showed that participants generally experienced the HRVB+ protocol as helpful. They typically expressed that the intervention helped them with their anxiety or stress and that it increased their self-efficacy concerning their ability to manage anxiety or stress. Several domains emerged that captured data about the biofeedback therapist. Though more research is undoubtedly needed, the findings of this study provide some preliminary support for the idea that common factors could play a role in biofeedback interventions.
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Ritchie, 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.
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Eonta, Alison. "Heart Rate Variability as a Moderator of Trauma Writing Outcomes". VCU Scholars Compass, 2013. http://scholarscompass.vcu.edu/etd/3236.
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Writing about personal traumatic experiences is associated with beneficial effects on physical and psychological symptoms compared with writing about emotionally neutral events. However, not everyone benefits from trauma writing to the same extent. The present study hypothesized that the effectiveness of trauma writing may be moderated by emotion regulation, as indexed by respiratory sinus arrhythmia (RSA). Research also shows that greater physiological reactivity is predictive of better trauma writing outcomes. Given the importance of physiological output in emotional processing, response training was developed and found to increase appropriate physiological reactivity. Because higher RSA is thought to indicate a more flexible response style including processing both emotional and physiological cues, it was hypothesized that trauma writers with higher resting RSA who received response training (as opposed to stimulus or no training) would have the best outcomes. It was also predicted that higher resting RSA would be related to lower baseline levels of depression, posttraumatic stress disorder (PTSD), physical illness symptoms, heart rate, and skin conductance. In the current study, participants wrote for 20 minutes on three occasions about a personal traumatic event (n = 113) or a neutral topic (n = 133) and received response training (n = 79), stimulus training (n = 84) or no training (n = 83). Heart rate and skin conductance were recorded in sessions one and three during a 10-minute baseline, 20-minute writing, and 10-minute recovery period. Self-reported trauma symptoms were assessed in each session. At baseline and one month after completing the sessions, participants filled out assessments of depression, PTSD, and physical illness symptoms. As predicted, participants with higher resting RSA who wrote about a trauma had greater reductions in symptoms of PTSD at post-writing session three. Higher resting RSA was also related to lower levels of resting heart rate and skin conductance. No relation was found between RSA and baseline symptoms of depression, PTSD, and physical illness. This study also found no effect of resting RSA as a moderator of response training outcomes.
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"Heart rate variability in heart failure". 2002. http://library.cuhk.edu.hk/record=b5891359.
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by Yeung Yuk-Ching.Thesis (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
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Huang, Yu-Chen, i 黃于珍. "Clustering Heart Beats Using Heart Rate Variability". Thesis, 2008. http://ndltd.ncl.edu.tw/handle/85524778639002113871.
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碩士元智大學
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.
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Cimponeriu, Laura Elena. "Dynamics of heart rate variability". Thesis, 1999. http://nemertes.lis.upatras.gr/jspui/handle/10889/3191.
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Barquero, Pérez Óscar. "Heart rate variability : a fractal analysis". Master's thesis, 2008. http://hdl.handle.net/10216/11023.
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