Dissertations / Theses on the topic 'Heart rate'

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.

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.

Thesis (Ph. D.)--West Virginia University, 2001.
Title from document title page. Document formatted into pages; contains vii, 123 p. : ill. (some col.). Vita. Includes abstract. Includes bibliographical references (p. 59-66).

The objective of this project is to develop a device that can monitor the heart rate and respiration of cetaceans. This would provide a way to quantitatively measure stress and determine the impact of human activity on cetaceans, especially for certain species that have been difficult to monitor in the past. There are many challenges to developing such a device, including determining the appropriate type of sensor, reducing the effect of flow noise, and designing an effective attachment method; this paper primarily focuses on determining the most suitable acoustic transducer. Experiments were conducted to compare various acoustic sensors in detecting heart rate. The electronic stethoscope performed the best in the experiments, but the results showed that other transducers, such as accelerometers and pressure sensors, also performed well and could be successful options with further development. Data processing methods to identify heartbeats and characterize signals are also discussed in this paper. Future work on the project involves subsequent tests to address other design variables as well as replicate experiments on animals.

Despite having the numerous evolved heart rate measuring devices and progress in their development over the years, there always remain the challenges of modern signal processing implementation by a comparatively small size wearable device. This thesis paper presents a wearable reflectance photoplethysmography (PPG) sensor system for measuring the heart rate of a user both in steady and moving states. The size and, power consumption of the device are considered while developing, to ensure an easy deployment of the unit at the measuring site and the ability to power the entire unit with a battery .The selection of both the electronic circuits and signal processing techniques is based on their sensitivity to PPG signals, robustness against noise inducing artifacts and miniaturization of the entire measuring unit. The entire signal chain operates in the discrete-time, which allows the entire signal processing to be implemented in firmware on an embedded microprocessor. The PPG sensor system is implemented on a single PCB that consumes around 7.5mW of power. Benchmarking tests with standard heart rate measuring devices reveal that the developed measurement unit (combination of the PPG sensor system, and inertial measurement unit (IMU) developed in-house at Acreo Swedish ICT, and a battery) is comparable to the devices in detecting heart rate even in motion artifacts environment. This thesis work is carried out in Acreo Swedish ICT, Gothenburg, Sweden in collaboration with MidSweden University, Sundsvall, Department of Electronics Design. This report can be used as ground work for future development of wearable heart rate measuring units at Acreo Swedish ICT.

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.

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.

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.

This thesis presents a comprehensive work on computerised analysis of fetal heart rate (FHR) features, including feature extraction, feature selection, analysis of influencing factors and setting up/validation of a computerised decision support system. Firstly, a novel feature – pattern readjustment – was extracted and tested. Clinical data were used to train a Support Vector Machine (SVM) to detect pattern readjustment. Then, the association of pattern readjustment and adverse labour outcome was investigated. The validation results with clinical experts show that the pattern readjustment can be accurately detected, while the study on labour outcome shows that the feature is related to fetal acidemia at birth. Secondly, Genetic Algorithms were employed as a feature selection method to select a best subset of FHR features and to use them to predict fetal acidemia with linear and nonlinear SVM. The diagnostic power of the classifier output using selected features was tested on the total set of 7,568 cases. As the classifier output increases, there is a consistent increase of the risk of fetal acidemia. Thirdly, an important influencing factor on FHR features - signal loss – was investigated. A bivariate model was built to estimate error based on signal loss. Validation results show that the bivariate model can accurately predict the error generated by signal loss. The influence of signal loss on labour outcome classification was also investigated. Finally, a computerised decision support system to estimate the risk of fetal acidemia was set up based on the above studies. The system was validated using new retrospective data. Validation results show that the system is capable of predicting adverse labour outcome and providing timely decision support. It is the first time an intrapartum computerised FHR decision support system has been built and validated on this size of dataset. With further improvements, such a system could be implemented clinically in the long term.

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.

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.

Thesis (Ph. D.)--West Virginia University, 1999.
Title from document title page. Document formatted into pages; contains x, 166 p. : ill. (some col.) Vita. Includes abstract. Includes bibliographical references (p. 139-162).

Exercising at an appropriate training intensity for individuals is important for improvement of cardiorespiratory fitness. The American College of Sports Medicine (ACSM) has recommended that healthy adults exercise at an intensity of 60-80% maximal heart rate reserve (MHRR). The ventilatory threshold (VT) has also been recommended for use to determine intensity for exercise prescription. The purpose of this study was to compare the heart rate at the VT (VTHR) and at 60-80% MHRR. A secondary purpose was to determine the relationship, if any, between age, gender, height, weight, body mass index, percent body fat, resting heart rate, physical activity status (PAS), smoking history, and rating of perceived exertion (RPE) at 60 and 80% Hrmax and the difference between the VTHR and 60% MHRR. Subjects were 373 apparently healthy or high risk (as defined by ACSM, 2) individuals (209 men, 164 women), ages 19-77 (46.1+12.8 yr.), from the Ball State University Adult Physical Fitness Program who performed a maximal treadmill test between 1992-1994. VT was selected using a computerized V-slope method by the SensorMedics 2900TI Metabolic Measurement Cart. The VTHR (125.2+16.9) was significantly lower than the 60-80% MHRR (133.1+10.8 to 154.5+12.7) (p<0.05). Two hundred and sixty two subjects (70.1%) were below 60% MHRR and 3 subjects (0.8%) were above 80% MHRR at the VTHR. Multiple regression analysis explained 11.2% of the variance in the difference between the VTHR and 60% MHRR using RPE at 60% HR,,,, PAS, and smoking history. For the majority (70.2%) of the adults in this study, the VTHR falls below the traditional THR of 60-80% MHRR. The 60-80% MHRR would appear to be an appropriate exercise training intensity for cardiorespiratory benefit and therefore the %MHRR range alone would seem to be an adequate training intensity. Further study related to the VTHR is warranted to determine its application, if any, to exercise prescription intensity.
School of Physical Education

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.

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).

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.

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.

Background and hypothesis: Standard pharmacological treatment for heart failure improves cardiac remodelling and survival in the setting of chronic heart failure, but is suboptimal in cases of acute heart failure (AHF). Peripartum cardiomyopathy (PPCM), de-novo hypotension (often due to haemorrhagic shock), and Takotsubo cardiomyopathy (TC) are conditions which have acute onset of heart failure, and often present with high mortality rates. In patients treated for these pathologies, a variation in the heart rate is observed and could potentially be used as a target to improve the treatment of AHF. We therefore questioned whether the use of a sinoatrial node inhibitor (ivabradine) to modulate heart rate may improve outcomes in AHF. Objectives and methods: Our objectives were 3-fold: (1) to explore the effect of a standard treatment strategy on heart rate in a South African cohort of PPCM patients after 6 and 12 months follow-up. (2) To explore the effect of ivabradine, a sinoatrial node inhibitor in an established signal transducer and activator of transcription 3 (STAT3) knockout mouse model of PPCM (with 3 consecutive pregnancies). Mice were fed ivabradine for 30 days (10mg/kg/day in drinking water), following the 3rd weaning. Trans-thoracic echocardiograms (TTE) were done at the end of the 3rd weaning, and after 30 days of treatment with ivabradine. Hearts were harvested after the second TTE for histology staining and messenger ribonucleic acid (mRNA) quantitation of transcripts involved in heart failure. (3) To explore the role of the sinoatrial node inhibitor in an ex-vivo model of de-novo AHF due to hypotension, and a newly developed ex-vivo model of TC. In the AHF model, hearts were stabilised before administering Ivabradine (3μM) in a buffer containing high free fatty-acids at a low pressure (to mimic hypotension/ haemorrhage shock conditions). A pressure- sensing balloon in the left ventricle measured heart rate, diastolic and systolic pressure, left ventricular developed pressure, rate pressure products and functional recovery. In the TC model, hearts were stabilised, then given a buffer with high free fatty-acid content and 10 times a physiological dose of adrenaline to mimic the adrenergic response seen in TC. Thereafter, hearts were restored to stabilisation pressure and substrate for recovery. Results: (1) Clinical outcomes indicated that patients on maximum standard therapy improved symptomatically and on the New York Heart Association scale. However, heart rates of PPCM patients remained elevated after 6 months of treatment. (2) In PPCM mice, a treatment with ivabradine was associated with reduced fibrotic infiltration in cardiac tissue and with a decrease in levels of atrial natriuretic peptide and Fibronectin mRNAs. (3) Both hypotensive AHF and TC models showed a tendency toward better cardiac function with ivabradine at the end of the acute phases. This advantage was lost after withdrawal of ivabradine during recovery. Conclusion: In South African women with PPCM treated with standard therapy, heart rate remains elevated, therefore suggesting that these women may benefit from the use of ivabradine as an additional therapy, particularly in patients who may be intolerant to β-blockers. The long-term use of ivabradine in the setting of cardiac dysfunction appears to have beneficial effects on remodelling, as treatment with ivabradine in our mouse PPCM model showed reduced cardiac fibrosis. The ex-vivo models of hypotensive AHF and TC both showed benefit in reducing heart rate during the acute phases, and hold the potential of being an intervention therapy to improve the outcome in patients who are brought to hospital while still in the acute phase.

Forced submergence of redhead ducks (Aythya americana) caused heart rate to fall from 100 ± 3 beats⋅min⁻ ¹ (mean ± s.e.m., N = 12) to a stable rate of 35 ± 4 beats⋅min⁻ ¹ (N = 12) within 5 seconds after submergence. Bradycardia was unaffected by breathing oxygen before the dive or by denervation of the baroreceptors, but was virtually eliminated by local anaesthesia of the narial region. When freely diving on a man-made pond, heart rate of redhead ducks and lesser scaup (A. affinis) two seconds after submergence was positively correlated with the pre-dive rate (r² = 0.71). Breathing oxygen before the dive and denervation of baroreceptors had little effect on this relationship. Chasing to induce submergence caused a slight enhancement of bradycardia, heart rate during the dive being about 10% lower than after a voluntary dive. Local anaesthesia of the narial region inhibited voluntary diving, but heart rates in chase-induced dives after nasal blockade were significantly higher (10-30%) than those obtained from untreated ducks in chase-induced dives. Dive heart rate, at 2-5 seconds submergence, was linearly related to the logarithm of the pre-dive rate for all voluntary and forced dives as well as dabbles. Even the heart rate which occurred 2-5 seconds after being trapped under water as a function of the rate immediately before trapping fitted this relationship. The function was described by the equation Y = -451 + 246 LOG X, where Y = dive (or trapped) and X = pre-dive (or pre-trap) heart rate (r² = 0.98). The relationship was unaltered by β-blockade with propranolol. Data from stimulation of the cut distal ends of vagal and cardiac sympathetic nerves suggest that a similar increase in vagal activity occurs on submergence in all of these dives. The first cardiac interval in voluntary dives represents a lower heart rate, indicating a higher level of vagal activity. When dabbling ducks (Anas platyrhynchos) dabble, heart rate at two seconds submergence is little changed from the pre-dabble rate. When these birds dive, however, heart rate at two seconds submergence is about 250 beats⋅min⁻ ¹, regardless of the pre-dive rate. Bilateral denervation of arterial baroreceptors significantly altered the dive:pre-dive relationship . These results have shown that nasal receptors are responsible for bradycardia in diving ducks when forcibly submerged, but that nasal receptors contribute little to the change in heart rate when ducks dive voluntarily. The results also suggest that there is a psychogenic modulation of the heart rate in voluntary dives which influences the pre-dive rather than the dive heart rate. Finally, dabbling ducks differ from diving ducks in their response to forced and voluntary diving. Chemoreceptors are responsible for the majority of the response in forced dives, and baroreceptors provide primary control in voluntary dives.
Science, Faculty of
Zoology, Department of
Graduate

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.

Includes bibliographical references (p. 231-279).
It is generally accepted that a linear relationship exists between heart rate/ workload and oxygen consumption and that heart rate thus accurately reflects workload and exercise intensity. As such, coaches and athletes commonly use heart rate to prescribe exercise and monitor changes in training status. Some studies have however, indicates that heart rate may not always be an accurate indicator of training status under all conditions, due to the possible influence of other variables. However, as measuring heart rate has been shown to be a reliable, accurate, inexpensive and practical method to monitor changes in training status, the purpose of this study was therefore to further explore ans clarify the heart/ workload relationship under a variety of different trainig and testing conditions.

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.

Mestrado em Engenharia de Computadores e Telemática
Heart rate is a relevant physiological marker used in several areas, namely psychology, as a measure of the anxiety and stress among other states. Typically, the heart rate is calculated from ECG that implies using dedicated equipment with electrodes placed on the human subject which can be considered invasive in many situations i.e. not comfortable or humanly suitable. With the advances in computer vision several works proposed methods to estimate the heart rate from video capturing skin patches of the subjects (e.g. for head, overall face, …). However, although promising results there no conclusive proofs on the accuracy and applicability in more realistic conditions (e.g. outside of the laboratory) namely due to the very controlled scenarios or limited sampling time. In this dissertation we proposed to evaluate the usefulness of heart rate estimation based on video and built upon the state of the art to address more realistic and challenging conditions i.e. less controlled scenarios and evaluate it under larger monitoring sessions (>1 minute). We performed two experiments based on video stimulus where the objective was to measure the HR changes induced by the video. In both scenarios, ECG was used to extract the HR that was used as ground truth. The first scenario was acquired with videos to elicit disgust (25 minutes), the second using smaller videos (<1 minute) using a neutral and “happiness” inducing videos. Our results show that the heart rate estimation is very sensitive to noise and not clear relation on the complete studies was observed in any of the scenarios. However, when studying the relation between the HR estimated from video and from ECG it was clear that both were highly correlated in limited time intervals suggesting that video estimated HR may be worthy to explore. In the process we developed PsyVidLab that besides incorporating the video estimated HR allows synchronous acquisition of video, ECG and some basic image processing modules namely emotion estimation from facial expression.
Devido aos avanços em visão de computador, vários trabalhos propuseram métodos para estimar o ritmo cardíaco utilizando partes da pele do sujeito (testa, face completa, ...). Contudo, embora se tenha obtido resultados promissores não há provas conclusivas acerca da precisão e aplicabilidade em condições mais realistas (fora do laboratório), devido aos senários muito controlados ou tempo de amostragem limitado. Nesta dissertação, propusemo-nos avaliar a utilidade da estimação de ritmo cardíaco por vídeo e contruído no estado da arte para atender a cenários mais realistas e exigentes, isto é, cenários menos controlados e avaliar os resultados em sessões de monitorização mais longos (>1 minuto). Nós efetuamos duas experiencias baseadas vídeo de estímulo onde o objetivo era de medir as alterações de ritmo cardíaco produzidas pelo vídeo. Em ambos os senários, ECG foi utilizado para extrair ritmo cardíaco que foi usado como comparação. O primeiro cenário foi adquirido com vídeos cujo estímulo foi “Nojo” (25 minutos), o segundo cenário usou vídeos mais pequenos (<10minutos) usando um estimulo neutro e de “felicidade”. Os resultados mostram que a estimação do ritmo cardíaco é bastante sensível ao ruido e não é clara a relação no estudo completo. Contudo, quando estudamos a relação entre o ritmo cardíaco estimado por vídeo e por ECG tornou-se claro que ambos eram altamente correlacionados em intervalos de tempo limitados, sugerindo que o ritmo cardíaco estimado por vídeo deve ser explorado. Durante o processo desenvolvemos o PsyVidLab que, para alem de incorporar a estimação de ritmo cardíaco por vídeo, permite a aquisição síncrona de vídeo, ECG, e alguns módulos de processamento de vídeo básicos especificamente estimação de emoção de expressões faciais.

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

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.

博士
國立陽明大學
醫學工程研究所
88
Heart rate is controlled by combined sympathetic and vagal nervous system. The association of sympathovagal balance to the diagnosis and prognosis of some diseases was evidenced. Heart rate variability (HRV) analysis analyzing the beat-to-beat heart rate variation is considered as a noninvasive tool to assess the autonomic activity. Recently, HRV analysis is widely applied to many different physiological and diseased situations and some inconsistent results of assessment for autonomic activity have raised. In this study, a mathematical model was developed to simulate HRV in response to autonomic control and to reveal the mathematical relation between HRV and autonomic activity. It is helpful to improve the interpretation of HRV analysis. We combined the kinetic equations proposed by Warner and Cox in 1962 and the integral pulse frequency modulation model to construct a mathematical model for heart rate modulated by autonomic nerves. To observe the characteristics of this model, we simulate HRV by inputting different oscillating frequencies, oscillating amplitudes and mean levels of autonomic activities in sinusoidal forms. Results revealed that an increased oscillating amplitude of autonomic activity increased HRV. Low-pass filtering effects existed in both nervous systems, and the sympathetic control had a narrow bandwidth than the vagal control. Thus the high frequency power of HRV mainly reflect the vagal modulation. A cardiac aliasing occurs as the oscillating frequency of autonomic activity beyond the half of mean heat rate. An increased mean level of sympathetic activity reduced the HRV induced by the fluctuations of both sympathetic and vagal activities. An increased mean level of vagal activity increased the HRV induced by the fluctuations of sympathetic activity but reduced the HRV induced by the fluctuations of vagal activity. Moreover, the autonomic activity in normal condition was assumed according to some experimental evidences. Then autonomic activities after sympathetic blockade, vagal blockade and during exercise were appropriately set accordingly to simulate HRV in these conditions in which some inconsistent results of assessment for autonomic activity by HRV analysis have raised. Results showed that this model could properly express HRV in these conditions. The alteration of HRV can be explained by the characteristic of this model. We found that the mean heartbeat interval influenced by the mean level of autonomic activities played an important role in measurement of HRV. But it could be neglected frequently in the interpretation of HRV. This model offers a mathematical basis for HRV analysis to improve the assessment of autonomic activity.

As per modern medical Science, doctors measure a pulse of an individual to know the heart strength and to know whether any irregularities in the rhythm of a person’s heart. It helps doctors to get an indication whether the patient has a severe heart condition or other medical problem that means it will just indicate them the condition of one’s heart and make them do further tests to know the conditions of other body parts. The Ayurvedic pulse diagnosis method also says, by palpating on the radial artery, one can know if there are any anomalies in any of the body parts or internal organs like Heart, kidney, spleen, bladder, liver, small intestine, etc., all at once. Both methods tell us the importance of Pulse, and there can be other ways to measure it. Here we tried to measure the pulse visually using image processing. We propose a system to measure pulse by detecting subtle head motion caused by Newtonian reaction to the inflow of blood per beat. It uses video processing techniques to detect head motion along with the apparently invisible inflow of blood per beat. We track the features from the head with the help of KLT tracker and perform principal component analysis (PCA) to decompose their trajectories. The peaks of these trajectories are detected to find the pulse rate.

Exergames combine physical activity and entertainment in an effort to increase people’s motivation to exercise. Multiplayer exergames attempt to include the motivating aspects of group activity by allowing two or more people to play together. In most multiplayer exergames, a player’s in-game performance is limited by her physical abilities. Less fit players are demotivated by repeated losses to more fit opponents, while fitter players face a lack of competition from unfit opponents. This situation makes it difficult for people of disparate physical abilities to play exergames together. This research presents heart rate balancing, a novel player balancing technique to better support engaging experiences in multiplayer exergames. Heart rate balancing bases players’ in-game performance on their effort relative to fitness level rather than their raw power. More specifically, heart rate monitoring is used to set in-game performance based on how closely a person adheres to her target heart rate. Experiments with heart rate balancing show that the technique improves competition between players. A strong correlation was found between people’s perceived effort and their in-game performance with heart rate balancing. The degree to which players noticed the balancing mechanism varied depending on game type. However, heart rate balancing did not interfere with people’s ability to play exergames. These results indicate that the heart rate balancing technique is a promising approach for improving enjoyment and engagement in multiplayer exergames.
Thesis (Ph.D, Computing) -- Queen's University, 2012-09-26 23:38:57.625

碩士
中原大學
醫學工程研究所
86
Health of fetal is the most important concern of pregnant women and gynecologist, On the other hand, fetal ECG (FECG) is an useful indexefor evaluating the fetal''s cardiac electrophysiology. Additionally, the analysis of heart rate variability (HRV) also provides a mean to understand the influence of autonomic function. A new Signal processing method, the thorax-abdomen transfer function, was developed in this laboratory to overcome these drawbacks in FECG extraction. To improve the accuracy in heart rate detection, we use QRS characterization procedure and Singular Value Decomposition (SVD) analysis to surpass the previous difficulties in QRS detection. Finally,the method of spectral analysis is utilized for detection and quantitative description of HRV. Due to the lack of clinical data, we can only provide qualitative but not quantively discussion on the power spectrum of heart rate variation. In the maternal HRV power spectrum, there is high frequency component that reflects the fluctuation of breath. During paced respiration, the high frequency component become clearer and dominated. However, we can''t find the high frequency component in fetal''s HRV spectrum during normal breathing. Additionally, the main frequency of fetal HRV becomes lower during pacing. Autonomic activity can be evaluated by HRV analysis. We hope that by improving the method of data acquisition and evaluated and experiment design, a complete and better fetal autonomic estimation system can be developed in the future.

碩士
國立陽明大學
物理治療暨輔助科技學系
98
Background: In the recent years, marathon exercise was popular around the world, so there were more and more people were interested about this jogging exercise. Because the limitation of human physical endurance was broken through continuously, the trend of regular marathon progressed into “ultra-marathon” in recent years. Ultra-marathon has higher intensity than the regular marathon, and it is relative more loading for physical condition, hence, it may cause many medical problem. In a competition, sudden cardiac death is most serious among medical accident; Besides, the over-training syndrome is most come up. These impairments are directly associated with cardiac and automatic nervous system. In previous studies, heart rate variability was apply in exercise-relative research extensively, but there is few literature focus on such high intensity ultra-marathon exercise. There is lack of enough information and research in Taiwan. We should investigate heart rate variability among the ultra-marathon runner, the result could be the basic information in medical protection for ordinary training and formal competition. Purpose: To investigate the effect of high intensity exercise in human heart rate variability and related parameter between ultra-marathon runners and populations without regular exercise habit. To investigate the effect of the discrepancy of usual training dosage in ultra-marathon runner to human heart rate variability. And to explore the correlation between the ultra-marathon competition performance and automatic nervous system control-related heart rate variability parameter, to explain the correlation between heart rate variability and competition performance. Method: This is a cross-sectional descriptive design study. We recruit twenty three 12-hours ultra-marathon runners and twenty one 24-hours runners to be intense exercise group; 23 sex and age-matched subjects without regular exercise habit to be contrast group. Before the competition, all of the runner should to write the questionnaire and accept 5 minutes continuous electrocardiogram record in sitting position. The electrocardiogram data would be analyzed by automatic computer translation to get heart rate variability parameter. We use paired t test to compare data difference among pre- and post-competition within group; Chi-square test and One-way ANOVA with Turkey post hoc test to detect difference between groups. Significant level was set at α = 0.05. Result: Among total 67 subjects, three groups have significant difference in body weight and BMI about the demographic characteristics (p&lt;0.05). About the pre-competition heart rate variability data shows that resting HR in two runner groups is lower (p&lt;0.001), and the other parameter: Mean, SDNN, LF, VLF are significantly higher than contrast group (p&lt;0.001). About the post-competition heart rate variability data, except HR is significantly higher among two runner groups (p&lt;0.05), the other parameter are all lower than pre-competition. About the over-training issue, the runner who set the weekly training dosage between 61 to 100 kilometer, their heart rate variability and competition performance would be better, the TP and LF show significant difference (p&lt;0.05). The competition performance is moderate correlation with 12-hours runner’s pre-SDNN (R=0.46, P&lt;0.05), and high correlation with 24-hours runner’s pre- and post-HF difference (R=0.78, P&lt;0.05). About the chronic fatigue and over-training, pre-HF is lower than contrast group and post-heart rate variability is lower among two runner groups. Conclusion: After a long term high intensity endurance exercise, the player would present chronic fatigue situation, it would lower the heart rate variability. As the runner has the over-training syndrome, the HF would decline abnormally. There is higher trend in heart rate variability and activity of automatic nerve system if who has appropriate pre-competition training dosage, on the other hand, less or over training dosage would induce adverse effect. Resting SDNN and pre- and post-HF difference could be regard as moderate to high level predictor of competition performance. Long term regular exercise behavior could increase human heart rate variability and activity of sympathetic/ parasympathetic nerve system.

Zhang Cheungyao = 人類心率變化中的層次結構 / 張程遙.
Thesis submitted in: November 2004.
Thesis (M.Phil.)--Chinese University of Hong Kong, 2005.
Includes bibliographical references (leaves 75-77).
Text in English; abstracts in English and Chinese.
Zhang Cheungyao = Ren lei xin lü bian hua zhong de ceng ci jie gou / Zhang Chengyao.
Table of Contents --- p.1
List of Figures --- p.6
List of Tables --- p.7
Chapter 1 --- Introduction --- p.1
Chapter 1.1 --- What is human heart rate variability? --- p.1
Chapter 1.2 --- Review of previous work --- p.2
Chapter 1.3 --- Outline of the thesis --- p.6
Chapter 2 --- Basic statistical properties of human heartbeat data --- p.8
Chapter 2.1 --- Data analyzed --- p.8
Chapter 2.2 --- Results and conclusion --- p.11
Chapter 3 --- Further analysis of heartbeat interval data --- p.20
Chapter 3.1 --- The method of analysis --- p.20
Chapter 3.2 --- Characteristic parameters for the multifractality of HRV --- p.22
Chapter 4 --- Results and discussion --- p.24
Chapter 4.1 --- Existence of hierarchical structure in human HRV --- p.24
Chapter 4.2 --- Characteristic parameters and potential application --- p.32
Chapter 5 --- A cardiac dynamical model --- p.51
Chapter 5.1 --- Description of the model --- p.51
Chapter 5.2 --- Review of some interesting results --- p.59
Chapter 5.3 --- Numerical methods --- p.61
Chapter 6 --- Results and discussion --- p.62
Chapter 6.1 --- Output for our simulation --- p.62
Chapter 6.2 --- Probability density function and structure functions --- p.65
Chapter 7 --- Conclusion --- p.73
Bibliography --- p.75

Dissertation submitted in compliance with the requirements for Masters Degree in Technology in the Department of Electrical Engineering, Technikon Natal, 2000.
The purpose of this study is the development of an affordable computer-based electrocardiogram, heart rate and temperature monitoring system, that would complement those that are available on the market and contribute to the reduction of the shortage of these medical instruments in South African hospitals and clinics. Electrocardiogram (ECG) refers to the graph that results from time versus voltage in a patient's chest. It reflects the rhythmic activity of the heart. For this reason the electrocardiogram has a diagnostic value that can be used by medical personnel to examine the biological (hence, clinical) behavior of the heart. The electrocardiogram can also be used to get the heart rate. This thesis explained how to acquire ECG signals from the patient and also how to achieve a cheaper way of providing galvanic isolation, which is required for sensors that are attached to the human body. It also explains computer interfacing using the parallel port and computer-based processing of these ECG signals to determine the instantaneous value of the heart rate and also to reduce the interference that contaminates these signals. In reducing interference, the performance of traditional IIR notch and adaptive filters, as noise cancelers, has been analyzed and compared. Least Mean Squares (LMS) and Normalized Least Mean Squares (NLMS) algorithms are the two algorithms that were considered in this study for adaptive noise canceling and their performance is evaluated and is compared based on their convergence rate, complexity and noise reduction.
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