Relevant bibliographies by topics / Heart rate

Academic literature on the topic 'Heart rate'

Author: Grafiati
Published: 4 June 2021
Last updated: 30 July 2024

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Journal articles on the topic "Heart rate"

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Ryan, J. M. "Relations between alcohol consumption, heart rate, and heart rate variability in men." Heart 88, no. 6 (December 1, 2002): 641–42. http://dx.doi.org/10.1136/heart.88.6.641.

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Sujatha.E, Sujatha E., and Y. Radha Y.Radha. "Heart Rate Monitoring Using Wireless Sensors." International Journal of Scientific Research 2, no. 12 (June 1, 2012): 206–8. http://dx.doi.org/10.15373/22778179/dec2013/64.

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Aydin, Seda Guzel, Turgay Kaya, and Hasan Guler. "Heart Rate Variability (HRV) Based Feature Extraction for Congestive Heart Failure." International Journal of Computer and Electrical Engineering 8, no. 4 (2016): 272–79. http://dx.doi.org/10.17706/ijcee.2016.8.4.272-279.

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Lantelme, Pierre, Christine Mestre, Michel Lievre, Alain Gressard, and Hugues Milon. "Heart Rate." Hypertension 39, no. 6 (June 2002): 1083–87. http://dx.doi.org/10.1161/01.hyp.0000019132.41066.95.

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Parati, Gianfranco, and Marco Di Rienzo. "Determinants of heart rate and heart rate variability." Journal of Hypertension 21, no. 3 (March 2003): 477–80. http://dx.doi.org/10.1097/00004872-200303000-00007.

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Sacha, Jerzy. "Interaction between Heart Rate and Heart Rate Variability." Annals of Noninvasive Electrocardiology 19, no. 3 (March 6, 2014): 207–16. http://dx.doi.org/10.1111/anec.12148.

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Yip, Amelia M. C., Alexander B. Zhai, and Haissam Haddad. "Heart rate and heart failure." Current Opinion in Cardiology 31, no. 2 (March 2016): 204–8. http://dx.doi.org/10.1097/hco.0000000000000266.

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Reil, Jan-Christian, and Michael Böhm. "Heart rate and heart failure." Current Opinion in Cardiology 28, no. 3 (May 2013): 326–31. http://dx.doi.org/10.1097/hco.0b013e32836043af.

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Heusch, Gerd. "Heart Rate and Heart Failure." Circulation Journal 75, no. 2 (2011): 229–36. http://dx.doi.org/10.1253/circj.cj-10-0925.

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Bidoli, Emilie M. Y., Michael H. Erhard, and Dorothea Döring. "Heart rate and heart rate variability in school dogs." Applied Animal Behaviour Science 248 (March 2022): 105574. http://dx.doi.org/10.1016/j.applanim.2022.105574.

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Dissertations / Theses on the topic "Heart rate"

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Uhlig, Stefan. "Heart Rate Variability." Doctoral thesis, Universitätsbibliothek Chemnitz, 2018. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-233101.

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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.
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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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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.
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Goodie, Jeffrey L. "Transfer of heart rate feedback training to reduce heart rate response to laboratory tasks." Morgantown, W. Va. : [West Virginia University Libraries], 2001. http://etd.wvu.edu/templates/showETD.cfm?recnum=2118.

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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).
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Liaw, Hibisca. "Underwater measurements of heart rate." Thesis, Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/47546.

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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.
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Patancheru, Govardhan Reddy. "Wearable Heart Rate Measuring Unit." Thesis, Mittuniversitetet, Avdelningen för elektronikkonstruktion, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-23351.

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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.
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Sattar, Nedal Abdul. "Heart rate variability in man." Thesis, University of Edinburgh, 1989. http://hdl.handle.net/1842/30723.

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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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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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Kurths, Jürgen, A. Voss, Annette Witt, P. Saparin, H. J. Kleiner, and N. Wessel. "Quantitative analysis of heart rate variability." Universität Potsdam, 1994. http://opus.kobv.de/ubp/volltexte/2007/1347/.

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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.
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Books on the topic "Heart rate"

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Ernst, Gernot. Heart Rate Variability. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-4309-3.

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Marek, Malik, and Camm A. John, eds. Heart rate variability. Armonk, NY: Futura Pub. Co., 1995.

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Feinstein, Nancy. Fetal heart rate auscultation. 2nd ed. Washington, D.C: AWHONN, Association of Women's Health, Obstetric and Neonatal Nurses, 2008.

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Feinstein, Nancy. Fetal heart rate auscultation. [Washington, D.C.]: AWHONN, Association of Women's Health, Obstetric and Neonatal Nurses, 2000.

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Tripathi, Onkar N., Ursula Ravens, and Michael C. Sanguinetti, eds. Heart Rate and Rhythm. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-17575-6.

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Künzel, Wolfgang, ed. Fetal Heart Rate Monitoring. Berlin, Heidelberg: Springer Berlin Heidelberg, 1985. http://dx.doi.org/10.1007/978-3-642-70358-4.

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J, Garite Thomas, and Nageotte Michael P, eds. Fetal heart rate monitoring. 2nd ed. Baltimore: Williams & Wilkins, 1991.

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1949-, Burke Ed, ed. Precision heart rate training. Champaign, IL: Human Kinetics, 1998.

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Tripathi, Onkar N., T. Alexander Quinn, and Ursula Ravens, eds. Heart Rate and Rhythm. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-33588-4.

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Wood, Paul L., and H. Gordon Dobbie. Electronic Fetal Heart Rate Monitoring. London: Macmillan Education UK, 1989. http://dx.doi.org/10.1007/978-1-349-19875-7.

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Book chapters on the topic "Heart rate"

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Orbell, Sheina, Havah Schneider, Sabrina Esbitt, Jeffrey S. Gonzalez, Jeffrey S. Gonzalez, Erica Shreck, Abigail Batchelder, et al. "Heart Rate." In Encyclopedia of Behavioral Medicine, 951–52. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-1005-9_863.

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Rai, Pallavi. "Heart Rate." In Encyclopedia of Evolutionary Psychological Science, 1–7. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-319-16999-6_2995-1.

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Kooyman, Gerald L. "Heart Rate." In Zoophysiology, 67–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-83602-2_6.

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Ginty, Annie T. "Heart Rate." In Encyclopedia of Behavioral Medicine, 1. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4614-6439-6_863-2.

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Ginty, Annie T. "Heart Rate." In Encyclopedia of Behavioral Medicine, 1047–48. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39903-0_863.

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Rai, Pallavi. "Heart Rate." In Encyclopedia of Evolutionary Psychological Science, 3649–55. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-319-19650-3_2995.

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Tavernier, Benoît, and Mathieu Jeanne. "Heart Rate Variability." In Monitoring Technologies in Acute Care Environments, 109–15. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8557-5_13.

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Sosnowski, Maciej. "Heart Rate Variability." In Specialized Aspects of ECG, 97–258. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-880-5_3.

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Casamian-Sorrosal, Domingo. "Heart Rate Variability." In Guide to Canine and Feline Electrocardiography, 231–40. Chichester, UK: John Wiley & Sons, Ltd, 2018. http://dx.doi.org/10.1002/9781119254355.ch16.

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Orbell, Sheina, Havah Schneider, Sabrina Esbitt, Jeffrey S. Gonzalez, Jeffrey S. Gonzalez, Erica Shreck, Abigail Batchelder, et al. "Heart Rate Variability." In Encyclopedia of Behavioral Medicine, 952–53. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-1005-9_805.

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Conference papers on the topic "Heart rate"

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Rowe, Dennis W., John Sibert, and Don Irwin. "Heart rate variability." In the SIGCHI conference. New York, New York, USA: ACM Press, 1998. http://dx.doi.org/10.1145/274644.274709.

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BAUER, AXEL, PETRA BARTHEL, and GEORG SCHMIDT. "HEART RATE TURBULENCE." In Proceedings of the 31st International Congress on Electrocardiology. WORLD SCIENTIFIC, 2005. http://dx.doi.org/10.1142/9789812702234_0049.

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Mann, Aysha, Jadyn Cook, Muneebah Umar, Fardin Khalili, and Amirtahà Taebi. "Heart Rate Monitoring Using Heart Acoustics." In ASME 2022 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/imece2022-96824.

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Abstract Cardiovascular diseases (CVDs) are the leading cause of death in the United States. In many cases, CVDs go unnoticed or are diagnosed late, contributing to the high death rate of such diseases. To address this issue, new methods for the early diagnosis of CVDs should be developed. In many medical conditions, heart rate can play an important role as an early indicator of heart diseases. In this pilot study, a heart rate monitoring method based on cardiovascular-induced sounds is investigated. For this purpose, phonocardiography (PCG) signals are measured noninvasively on the body surface of five healthy subjects (21–24 years) using an electronic stethoscope. In addition, electrocardiography (ECG) was used as a gold-standard method of cardiac monitoring. The PCG signals were then post-processed using custom-built algorithms to estimate the subject heart rate. These estimated heart rates were then compared with the heart rate calculated from the ECG signal using the well-known Pan-Tompkins algorithm. Results showed that the heart rate estimations from the acoustic modalities were consistent with those calculated from the gold-standard ECG.
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Paliwal, Sukriti, C. Vasantha Lakshmi, and C. Patvardhan. "Real time heart rate detection and heart rate variability calculation." In 2016 IEEE Region 10 Humanitarian Technology Conference (R10-HTC). IEEE, 2016. http://dx.doi.org/10.1109/r10-htc.2016.7906818.

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Qiao, Donghao, Farhana Zulkernine, Raihan Masroor, Roshaan Rasool, and Nauman Jaffar. "Measuring Heart Rate and Heart Rate Variability with Smartphone Camera." In 2021 22nd IEEE International Conference on Mobile Data Management (MDM). IEEE, 2021. http://dx.doi.org/10.1109/mdm52706.2021.00049.

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jonckheere, J. De, C. Garabedian, P. Charlier, L. Storme, V. Debarge, and R. Logier. "Influence of averaged fetal heart rate in heart rate variability analysis*." In 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE, 2019. http://dx.doi.org/10.1109/embc.2019.8856803.

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Hoshiyama, Masaki, and Alan Murray. "Analysis of Heart Rate Variability Indices with Slowly Changing Heart Rate." In 2016 Computing in Cardiology Conference. Computing in Cardiology, 2016. http://dx.doi.org/10.22489/cinc.2016.289-243.

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Chen, Jie, Zhuoqing Chang, Qiang Qiu, Xiaobai Li, Guillermo Sapiro, Alex Bronstein, and Matti Pietikainen. "RealSense = real heart rate: Illumination invariant heart rate estimation from videos." In 2016 Sixth International Conference on Image Processing Theory, Tools and Applications (IPTA). IEEE, 2016. http://dx.doi.org/10.1109/ipta.2016.7820970.

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Khairuddin, Muhammad Khairul Nizar Bin, Kazuhiro Nakamoto, Hiroshi Nakamura, Kanya Tanaka, and Shota Nakashima. "Heart Rate and Heart Rate Variability Measuring System by Using Smartphone." In 2017 5th Intl Conf on Applied Computing and Information Technology/4th Intl Conf on Computational Science/Intelligence and Applied Informatics/2nd Intl Conf on Big Data, Cloud Computing, Data Science (ACIT-CSII-BCD). IEEE, 2017. http://dx.doi.org/10.1109/acit-csii-bcd.2017.23.

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Tamura, Y., T. Miyasaka, and J. Shimizu. "Increased heart rate reduced crossbridge formation in beating rat whole heart." In 2012 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI). IEEE, 2012. http://dx.doi.org/10.1109/bhi.2012.6211633.

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Reports on the topic "Heart rate"

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De Jong, Marla J., and David C. Randall. Heart Rate Variability Analysis in the Assessment of Autonomic Function in Heart Failure. Fort Belvoir, VA: Defense Technical Information Center, July 2004. http://dx.doi.org/10.21236/ada425014.

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Sastre, Antonio. Practical Implementations of Real-Time Heart Rate Variability. Fort Belvoir, VA: Defense Technical Information Center, March 2004. http://dx.doi.org/10.21236/ada425939.

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Hagan, R. D., M. J. Buono, S. Singh, and C. G. Blood. Heart Rate Variability and Changes in Blood Volume. Fort Belvoir, VA: Defense Technical Information Center, January 2000. http://dx.doi.org/10.21236/ada389810.

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Siebert, Christopher. Heart Rate and Accelerometry during Singles Footbag Net Play. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.650.

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Clark, Robert D. Heart Rate Variability in Male Sexual Arousal and Erectile Dysfunction. Fort Belvoir, VA: Defense Technical Information Center, January 2007. http://dx.doi.org/10.21236/ad1013961.

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King, David R. Heart Rate Complexity of Trauma Patients During Evaluation and Resuscitation. Fort Belvoir, VA: Defense Technical Information Center, May 2013. http://dx.doi.org/10.21236/ada590497.

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Chan DykN’an and Alexanyants. PECULIARITIES OF HEART RATE VARIABILITY OF QUALIFIED BADMINTON PLAYERS AT REST. Federal State Budgetary Educational Establishment of Higher Vocational Education "Povolzhskaya State Academy of Physical Culture, Sports and Tourism" Naberezhnye Chelny, December 2013. http://dx.doi.org/10.14526/34_2013_4.

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Henderson, Peter. Anticipatory Heart Rate Responses of Motor Vehicle Drivers Riding as Passengers. Fort Belvoir, VA: Defense Technical Information Center, May 1988. http://dx.doi.org/10.21236/ada194365.

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Brusseau, Valentin, I. Tauveron, R. Bagheri, U. Ugbolue, V. Magnon, J. B. Bouillon-Minois, V. Navel, and F. Dutheil. Effect of hyperthyroidism treatments on heart rate variability: A systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, August 2022. http://dx.doi.org/10.37766/inplasy2022.8.0062.

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Review question / Objective: The reversibility of HRV abnormalities in hyperthyroidism remains contradictory. The purpose of the study is to conduct a systematic review and meta-analysis on the effect of antithyroid treatments on HRV in hyperthyroidism. Population: Untreated hyperthyroid patients Intervention: Antithyroid treatment Control: Controls without hyperthyroidism Outcomes: Reversibility of heart rate variability abnormalities in hyperthyroidism Study design: Systematic review. Information sources: All studies that addressed the effect of hyperthyroidism treatment on HRV were reviewed. Studies were searched electronically through the major article databases (PubMed, Cochrane Library, Embase, and Google Scholar) with the following keywords: ("hyperthyroidism" OR "hyperthyroid") AND ("heart rate variability" OR "HRV") until April 4, 2022.
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Chung, Brian, Jonathan Lanier, Lolita M. Burrell, and Michael D. Matthews. Using Heart Rate to Predict Resilience and Susceptibility to PTSD in Soldiers. Fort Belvoir, VA: Defense Technical Information Center, April 2011. http://dx.doi.org/10.21236/ada540988.

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