Academic literature on the topic 'HRV analysis'

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Journal articles on the topic "HRV analysis"

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Savolainen, Carita, Pia Laine, Mick N. Mulders, and Tapani Hovi. "Sequence analysis of human rhinoviruses in the RNA-dependent RNA polymerase coding region reveals large within-species variation." Journal of General Virology 85, no. 8 (August 1, 2004): 2271–77. http://dx.doi.org/10.1099/vir.0.79897-0.

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Human rhinoviruses (HRVs; family Picornaviridae), the most frequent causative agents of respiratory infections, comprise more than 100 distinct serotypes. According to previous phylogenetic analysis of the VP4/VP2-coding sequences, all but one of the HRV prototype strains distribute between the two established species, Human rhinovirus A (HRV-A) and Human rhinovirus B (HRV-B). Here, partial sequences of the RNA-dependent RNA polymerase (3D polymerase)-coding gene of 48 HRV prototype strains and 12 field isolates were analysed. The designated division of the HRV strains into the species HRV-A a
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Laine, Pia, Carita Savolainen, Soile Blomqvist, and Tapani Hovi. "Phylogenetic analysis of human rhinovirus capsid protein VP1 and 2A protease coding sequences confirms shared genus-like relationships with human enteroviruses." Journal of General Virology 86, no. 3 (March 1, 2005): 697–706. http://dx.doi.org/10.1099/vir.0.80445-0.

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Phylogenetic analysis of the capsid protein VP1 coding sequences of all 101 human rhinovirus (HRV) prototype strains revealed two major genetic clusters, similar to that of the previously reported VP4/VP2 coding sequences, representing the established two species, Human rhinovirus A (HRV-A) and Human rhinovirus B (HRV-B). Pairwise nucleotide identities varied from 61 to 98 % within and from 46 to 55 % between the two HRV species. Interserotypic sequence identities in both HRV species were more variable than those within any Human enterovirus (HEV) species in the same family. This means that un
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Koch, Celine, Marcel Wilhelm, Stefan Salzmann, Winfried Rief, and Frank Euteneuer. "A meta-analysis of heart rate variability in major depression." Psychological Medicine 49, no. 12 (June 26, 2019): 1948–57. http://dx.doi.org/10.1017/s0033291719001351.

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AbstractBackgroundMajor depression (MD) is a risk factor for cardiovascular disease. Reduced heart rate variability (HRV) has been observed in MD. Given the predictive value of HRV for cardiovascular health, reduced HRV might be one physiological factor that mediates this association.MethodsThe purpose of this study was to provide up-to-date random-effects meta-analyses of studies which compare resting-state measures of HRV between unmedicated adults with MD and controls. Database search considered English and German literature to July 2018.ResultsA total of 21 studies including 2250 patients
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Blasi, Anna, Javier Jo, Edwin Valladares, Barbara J. Morgan, James B. Skatrud, and Michael C. K. Khoo. "Cardiovascular variability after arousal from sleep: time-varying spectral analysis." Journal of Applied Physiology 95, no. 4 (October 2003): 1394–404. http://dx.doi.org/10.1152/japplphysiol.01095.2002.

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We performed time-varying spectral analyses of heart rate variability (HRV) and blood pressure variability (BPV) recorded from 16 normal humans during acoustically induced arousals from sleep. Time-varying autoregressive modeling was employed to estimate the time courses of high-frequency HRV power, low-frequency HRV power, the ratio between low-frequency and high-frequency HRV power, and low-frequency power of systolic BPV. To delineate the influence of respiration on HRV, we also computed respiratory airflow high-frequency power, the modified ratio of low-frequency to high-frequency HRV powe
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Schneider, Martha, and Andreas Schwerdtfeger. "Autonomic dysfunction in posttraumatic stress disorder indexed by heart rate variability: a meta-analysis." Psychological Medicine 50, no. 12 (August 28, 2020): 1937–48. http://dx.doi.org/10.1017/s003329172000207x.

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AbstractBackgroundChanges in autonomic nervous system (ANS) function have been observed in a variety of psychological disorders, including posttraumatic stress disorder (PTSD). Analysis of heart rate variability (HRV) provides insight into the functioning of the ANS. Previous research on PTSD found lower HRV in PTSD patients compared to controls, indicating altered sympathetic and parasympathetic activity, but findings are inconsistent. The purpose of this meta-analysis was to examine differences in HRV indices between individuals with PTSD and healthy controls at baseline and during stress.Me
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Gawade, Ratnadeep. "ECG Analysis for HRV Detection." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 14, 2021): 2283–86. http://dx.doi.org/10.22214/ijraset.2021.34137.

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In this paper an algorithm is proposed for estimation of HRV with better accuracy and results. We are making use of Auto Regressive Model (AR Model) for the estimation. Since ECG wave is also contaminated with a lot of noise such as Power Line Interference (PLI), EMG and just some common artifacts like breathing disturbance’s, so to filter out all this noise from the wave we are using Cumulant based AR model for filtering the wave. Using IoT we will later use real time ECG waves to estimate HRV.
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German-Sallo, Zoltan. "Wavelet Transform based HRV Analysis." Procedia Technology 12 (2014): 105–11. http://dx.doi.org/10.1016/j.protcy.2013.12.462.

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Niskanen, Juha-Pekka, Mika P. Tarvainen, Perttu O. Ranta-aho, and Pasi A. Karjalainen. "Software for advanced HRV analysis." Computer Methods and Programs in Biomedicine 76, no. 1 (October 2004): 73–81. http://dx.doi.org/10.1016/j.cmpb.2004.03.004.

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Sieciński, Szymon, Paweł S. Kostka, and Ewaryst J. Tkacz. "Heart Rate Variability Analysis on Electrocardiograms, Seismocardiograms and Gyrocardiograms on Healthy Volunteers." Sensors 20, no. 16 (August 13, 2020): 4522. http://dx.doi.org/10.3390/s20164522.

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Physiological variation of the interval between consecutive heartbeats is known as the heart rate variability (HRV). HRV analysis is traditionally performed on electrocardiograms (ECG signals) and has become a useful tool in the diagnosis of different clinical and functional conditions. The progress in the sensor technique encouraged the development of alternative methods of analyzing cardiac activity: Seismocardiography and gyrocardiography. In our study we performed HRV analysis on ECG, seismocardiograms (SCG signals) and gyrocardiograms (GCG signals) using the PhysioNet Cardiovascular Toolb
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McIntyre, Chloe L., E. Carol McWilliam Leitch, Carita Savolainen-Kopra, Tapani Hovi, and Peter Simmonds. "Analysis of Genetic Diversity and Sites of Recombination in Human Rhinovirus Species C." Journal of Virology 84, no. 19 (July 28, 2010): 10297–310. http://dx.doi.org/10.1128/jvi.00962-10.

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ABSTRACT Human rhinoviruses (HRVs) are a highly prevalent and diverse group of respiratory viruses. Although HRV-A and HRV-B are traditionally detected by virus isolation, a series of unculturable HRV variants have recently been described and assigned as a new species (HRV-C) within the picornavirus Enterovirus genus. To investigate their genetic diversity and occurrence of recombination, we have performed comprehensive phylogenetic analysis of sequences from the 5′ untranslated region (5′ UTR), VP4/VP2, VP1, and 3Dpol regions amplified from 89 HRV-C-positive respiratory samples and available
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Dissertations / Theses on the topic "HRV analysis"

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Padmanabhan, Sivasankar. "Drowsiness detection using HRV analysis." Thesis, California State University, Long Beach, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=1596988.

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<p> The field of drowsiness detection is gaining more attention these days. An estimate by National Highway Traffic Safety Administration states that the total number of people falling asleep on the wheel is increasing day by day. If there is an effective way to monitor this condition and alert the drivers, many fatal accidents can be prevented. This thesis work elaborates on one such simple, yet effective drowsiness detection algorithm, the HRV - Heart Rate Variability analysis. Many psychological researchers have found out that when a person becomes drowsy, there is a variation in their hear
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Green, Jr Donald Lee. "ANALYSIS OF THE EFFECTS OF ATROPINE AND SALINE ON THE HRV OF RATS USING ENSEMBLE AVERAGING AND FREQUENCY ANALYSIS." MSSTATE, 2008. http://sun.library.msstate.edu/ETD-db/theses/available/etd-07102008-123307/.

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The aim of this study is to examine heart rate variability (HRV) alteration after the injection of atropine and saline and to determine if ensemble averaging affects the outcome of frequency domain analysis. The HRV data is pre-processed using ensemble averaging and then frequency domain and statistical analysis is done. The HRV readings originate from a previous study of four rats. Ensemble averaging reduces the mean drift effect in the data. The original and ensemble is then processed through an Fast Fourier Transform (FFT). The results show that the ensembled data allows frequency peaks and
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Nytorpe, Piledahl Staffan, and Daniel Dahlberg. "Detektering av stress från biometrisk data i realtid." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-31248.

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At the time of writing, stress and stress related disease have become the most common reasons for absence in the workplace in Sweden. The purpose of the work presented here is to identify and notify people managing unhealthy levels of stress. Since symptoms of mental stress manifest through functions of the Sympathetic Nervous System (SNS), they are best measured through monitoring of SNS changes and phenomena. In this study, changes in the sympathetic control of heart rate were recorded and analyzed using heart rate variability analysis and a simple runner’s heart rate sensor connected to a s
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Franěk, Pavel. "Analýza variability srdečního rytmu pomocí rekurentního diagramu." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2013. http://www.nusl.cz/ntk/nusl-220048.

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The aim of this thesis is to describe the variability of cardiac rhythm and familiarity with the methods of the analysis, ie by monitoring changes in heart rhythm electrogram signal recording and using the methods in the time domain using recurrent diagram. The work describes the quantification of the methods and possibilities of quantifiers in the evaluation of heart rate variability analysis. It also describes the clinical significance of heart rate variability and diagnostic capabilities changes of heart rate variability caused by ischemic heart disease. The practical part describes how to
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Macková, Pavlína. "EKG biofeedback." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219742.

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The master’s thesis is focused on the possibilities of measuring heart rate of ECG signal and its use in therapeutic game of ECG biofeedback. This thesis describes the way of measuring ECG with acquisition unit Biopac and analyzes signal processing for measurement of heart rate – algorithms of QRS detection, HRV analysis. Realisation of therapeutic is designed for applications in Matlab.
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Appelgren, Jörgen, and Fredrik Kjellström. "LCC-analys av FTX-system : En jämförelse av centralt- och lägenhetsplacerat." Thesis, Uppsala universitet, Institutionen för geovetenskaper, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-172562.

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This report is the result of a thesis conducted at the consulting firm Bjerking AB andis the final part of the Bachelor Programme in Construction Engineering at Universityof Uppsala. The work aims to investigate the costs and how the choice of ventilationsystem affects building projects during a long-term period. This report covers costssuch as investment, maintenance and energy but also how they affect residents andbuilders. Building regulations for energy consumption are expected to be tougher;therefore a comparison of two different heat recovery ventilation systems(HRV-system) was made. One
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Heiss, Leah Rose Laurel, and leah heiss@rmit edu au. "Empathy and the space between: investigating the role of digitally enhanced apparel in promoting remote empathetic connection." RMIT University. Architecture and Design, 2006. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20070112.101632.

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This body of work is the culmination of a two year investigation into the role of electronically enhanced apparel and artefacts in providing empathetic linkage between people who do not share physical space. The research draws from the diverse fields of philosophy, communications theory, neuropsychology, presence technologies and technologically advanced textiles, and proposes that a nexus of these disciplines may provide significant opportunities for enhancing the user interactivity of garments and artefacts. Remote emotional connection is investigated through the creation of
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Gunzenhauser, Jan. "Application of real-time HRV biofeedback in the scenario of meditation practice : Feasibility, usability and medical fidelity." Thesis, Linnéuniversitetet, Institutionen för medieteknik (ME), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-45420.

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Chronic stress is a prevalent and universally present hazard in modern society. It lowers the quality of life for individuals and significantly con- tributes to unsustainable health care costs. Therefore it is important to have natural and noninvasive ways of controlling stress. One such way is meditation, a technique which has been practiced for over five thousand years to improve stress regulation. Also, proceedings in sensing technologies lead to the discovery of biofeedback as another cost-effective technique for stress assessment and reduction. In continuation of research on real-time ref
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Thungtong, Anurak. "Synchronization, Variability, and Nonlinearity Analysis: Applications to Physiological Time Series." Case Western Reserve University School of Graduate Studies / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=case1364316597.

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Huang, Lin. "Effects of aromatherapy on negative emotions and work and study performance: heart rate variability analysis to assess the balance of the autonomic nervous system." Doctoral thesis, Universitat Autònoma de Barcelona, 2017. http://hdl.handle.net/10803/402260.

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El objetivo general de esta tesis es analizar la eficacia de la aromaterapia (AR) para reducir las emociones negativas e incrementar el nivel de atención y rendimiento en el situaciones laborales y académicas. Se probará esta eficacia con cuestionarios y evaluando el equilibrio del Sistema Nervioso Autónomo a partir del análisis HRV. Para llevar a cabo este objetivo general, se realizarán dos estudios principales. Analizaremos los efectos de la AR sobre la variabilidad de la frecuencia cardíaca (HRV) como un marcad
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Books on the topic "HRV analysis"

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Heart rate variability (HRV) signal analysis: Clinical applications. Boca Raton: Taylor & Francis, 2013.

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Poplaski, Richard S. HOV systems analysis. Charlottesville, Va: Virginia Transportation Research Council, 1994.

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Lomborg, Bjørn. Rethinking HIV priorities. Cambridge: Cambridge University Press, 2012.

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Rethinking HIV priorities. Cambridge: Cambridge University Press, 2012.

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Rodrigo, Allen G., and Gerald H. Learn, eds. Computational and Evolutionary Analysis of HIV Molecular Sequences. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/b112102.

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Papua New Guinea. HIV/AIDS NSP Steering Committee. and National AIDS Council (Papua New Guinea), eds. Situation analysis of HIV/AIDS in Papua New Guinea. Papua New Guinea: National AIDS Council, 2003.

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Joint United Nations Programme on HIV/AIDS. Zambia: HIV prevention response and modes of transmission analysis : final report. Lusaka, Zambia: Zambia National HIV/AIDS/STI/TB Council, 2009.

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Mngadi, Sibusiso. Swaziland HIV prevention, response, and modes of transmission analysis: Final report. Mbabane, Swaziland: NERCHA, 2009.

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Smith, Ann. HIV/AIDS and emergencies: Analysis and recommendations for practice. London: Overseas Development Institute, 2002.

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Gelmon, Lawrence. Kenya HIV prevention response and modes of transmission analysis. Nairobi: National AIDS Control Council, 2009.

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Book chapters on the topic "HRV analysis"

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Germán-Salló, Z., A. Gligor, and H. S. Grif. "Wavelet Based HRV Analysis." In International Conference on Advancements of Medicine and Health Care through Technology; 5th – 7th June 2014, Cluj-Napoca, Romania, 229–32. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07653-9_46.

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Dabas, Pawan Kumar, and Dhananjoy Shaw. "Reliability of Frequency Domain HRV Analysis." In IFMBE Proceedings, 1615–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14515-5_411.

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Huang, Chien-Sheng, Ching-Huang Lin, Chien-Yue Chen, Shao-Ciang Gan, and Guan-Syuan Hong. "The HRV Analysis on e-Book Reading." In Advances in Intelligent Systems and Computing, 217–22. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-12286-1_22.

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Butkevičiūtė, Eglė, Matīss Eriņš, and Liepa Bikulčienė. "Mobile Platform for Fatigue Evaluation: HRV Analysis." In Communications in Computer and Information Science, 541–52. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30275-7_42.

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Chang, F. S., T. M. Yu, J. H. Lin, and S. T. Tang. "An Alcohol Sensing System basing on HRV Analysis." In IFMBE Proceedings, 920–22. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03885-3_255.

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Janković, Danilo, and Radovan Stojanović. "Flexible system for HRV analysis using PPG signal." In IFMBE Proceedings, 705–12. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4166-2_106.

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Khandoker, Ahsan Habib, Chandan Karmakar, Michael Brennan, Andreas Voss, and Marimuthu Palaniswami. "Poincaré Plot Interpretation of HRV Using Physiological Model." In Poincaré Plot Methods for Heart Rate Variability Analysis, 25–46. Boston, MA: Springer US, 2013. http://dx.doi.org/10.1007/978-1-4614-7375-6_3.

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Khandoker, Ahsan Habib, Chandan Karmakar, Michael Brennan, Andreas Voss, and Marimuthu Palaniswami. "Poincaré Plot in Capturing Nonlinear Temporal Dynamics of HRV." In Poincaré Plot Methods for Heart Rate Variability Analysis, 47–68. Boston, MA: Springer US, 2013. http://dx.doi.org/10.1007/978-1-4614-7375-6_4.

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Ahn, Jae Mok, and Jeom Keun Kim. "Effects of Heart Rate on Results of HRV Analysis." In Advances in Intelligent Systems and Computing, 711–22. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6861-5_60.

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Navin, Om, Gautam Kumar, Nirmal Kumar, Kuldeep Baderia, Ranjeet Kumar, and Anil Kumar. "R-Peaks Detection Using Shannon Energy for HRV Analysis." In Lecture Notes in Electrical Engineering, 401–9. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2553-3_39.

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Conference papers on the topic "HRV analysis"

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Ji, Lianying, Jiankang Wu, Yuanjing Yang, Shaofeng Wang, and Aiguang Li. "Activity-aware HRV analysis." In 2011 IEEE International Conference on Systems, Man and Cybernetics - SMC. IEEE, 2011. http://dx.doi.org/10.1109/icsmc.2011.6083830.

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German-Sallo, Zoltan. "HRV Analysis Using Complexity Indices." In 2019 E-Health and Bioengineering Conference (EHB). IEEE, 2019. http://dx.doi.org/10.1109/ehb47216.2019.8969875.

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Ji, Lianying, Jiankang Wu, Yuanjing Yang, Shaofeng Wang, and Aiguang Li. "Context-aware HRV analysis system." In 2011 6th IEEE Conference on Industrial Electronics and Applications (ICIEA). IEEE, 2011. http://dx.doi.org/10.1109/iciea.2011.5975742.

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Jose, Sajeev K., Chandan M. Shambharkar, and Job Chunkath. "HRV analysis using ballistocardiogram with LabVIEW." In 2015 International Conference on Computing and Communications Technologies (ICCCT). IEEE, 2015. http://dx.doi.org/10.1109/iccct2.2015.7292732.

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Hoang ChuDuc, Luong DuongTrong, Thuan NguyenDuc, and Duc TrinhQuang. "Mobile device based HRV analysis system." In 2013 Fifth International Conference on Ubiquitous and Future Networks (ICUFN). IEEE, 2013. http://dx.doi.org/10.1109/icufn.2013.6614858.

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Ramos, Guilherme, Miquel Alfaras, and Hugo Gamboa. "Real-Time Approach to HRV Analysis." In 11th International Conference on Bio-inspired Systems and Signal Processing. SCITEPRESS - Science and Technology Publications, 2018. http://dx.doi.org/10.5220/0006641402080215.

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Aysin, Benhur, Joe Colombo, and Elif Aysin. "Comparison of HRV analysis methods during Orthostatic Challenge: HRV with respiration or without?" In 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2007. http://dx.doi.org/10.1109/iembs.2007.4353474.

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Munla, Nermine, Mohamad Khalil, Ahmad Shahin, and Azzam Mourad. "Driver stress level detection using HRV analysis." In 2015 International Conference on Advances in Biomedical Engineering (ICABME). IEEE, 2015. http://dx.doi.org/10.1109/icabme.2015.7323251.

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Chang, F. C., C. K. Chang, CC Chiu, S. F. Hsu, and Y. D. Lin. "Variations of HRV analysis in different approaches." In 2007 34th Annual Computers in Cardiology Conference. IEEE, 2007. http://dx.doi.org/10.1109/cic.2007.4745410.

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Pucik, Jozef, Oldrich Ondracek, Elena Cocherova, and Abdullah Sultan. "Spectrum of counts computation for HRV analysis." In 2009 19th International Conference Radioelektronika (RADIOELEKTRONIKA). IEEE, 2009. http://dx.doi.org/10.1109/radioelek.2009.5158749.

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Reports on the topic "HRV analysis"

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Acharya, R., and K. Sawa. HRB-22 preirradiation thermal analysis. Office of Scientific and Technical Information (OSTI), May 1995. http://dx.doi.org/10.2172/81077.

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Yang, Dean, James Allen, Arlete Mahumane, James Riddell, and Hang Yu. Knowledge, Stigma, and HIV Testing: An Analysis of a Widespread HIV/AIDS Program. Cambridge, MA: National Bureau of Economic Research, April 2021. http://dx.doi.org/10.3386/w28716.

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Boring, Ronald, and David Gertman. P-203: Human Reliability Analysis (HRA) Training Course. Office of Scientific and Technical Information (OSTI), March 2016. http://dx.doi.org/10.2172/1467594.

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Korber, Bette. LANL/New Mexico Consortium HIV vaccine design and Analysis. Office of Scientific and Technical Information (OSTI), July 2014. http://dx.doi.org/10.2172/1136461.

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Dadkhah, Mahyar S., and Albert S. Kobayashi. HRR Field of a Moving Crack, an Experimental Analysis. Fort Belvoir, VA: Defense Technical Information Center, September 1988. http://dx.doi.org/10.21236/ada198931.

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Servais, Marita. Overview of HRS Public Data Files for Cross-sectional and Longitudinal Analysis. Institute for Social Research, University of Michigan, 2010. http://dx.doi.org/10.7826/isr-um.06.585031.001.05.0023.2010.

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Dickerson, Robert, Patricia Dickerson, and Pallas Papin. Analysis of Sample DUM002 (INL pin casting, 800C/48 hr, 500C 8 hr). Office of Scientific and Technical Information (OSTI), October 2014. http://dx.doi.org/10.2172/1162149.

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Dadkhah, Mahyar S., and Albert S. Kobayashi. Further Studies of the HRR Field of a Moving Crack. An Experimental Analysis. Fort Belvoir, VA: Defense Technical Information Center, December 1988. http://dx.doi.org/10.21236/ada202545.

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Wright, C. W., and D. W. Later. HRI catalytic two-stage liquefaction (CTSL) process materials: chemical analysis and biological testing. Office of Scientific and Technical Information (OSTI), December 1985. http://dx.doi.org/10.2172/6089257.

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Sturm, G. P. Jr, J. Kim, and J. Shay. Coal liquefaction process streams characterization and evaluation: Analysis of coal-derived synthetic crude from HRI CTSL Run CC-15 and HRI Run CMSL-2. Office of Scientific and Technical Information (OSTI), January 1994. http://dx.doi.org/10.2172/10145702.

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