Relevant bibliographies by topics / HRV analysis

Academic literature on the topic 'HRV analysis'

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Published: 4 June 2021
Last updated: 3 February 2022

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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 and HRV-B was also seen in the 3D-coding region. Phylogenetically, HRV-B clustered closer to human enterovirus (HEV) species HEV-B, HEV-C and poliovirus than to HRV-A. Intraspecies variation within both HRV-A and HRV-B was greater in the 3D-coding region than in the VP4/VP2-coding region, with the difference maxima reaching 48 % at the nucleotide level and 36 % at the amino acid level in HRV-A and 53 and 35 %, respectively, in HRV-B. Within both species, a few strains formed a separate cluster differing from the majority of strains as much as HEV-B from HEV-C. Furthermore, the tree topology within HRV-A differed from that for VP4/VP2, suggesting possible recombination events in the evolutionary history of the strains. However, all 12 field isolates clustered similarly, as in the capsid region. These results showed that the within-species variation in the 3D region is greater in HRV than in HEV. Furthermore, HRV variation in the 3D region exceeds that in the capsid-coding region.
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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 unequivocal serotype identification by VP1 sequence analysis used for HEV strains may not always be possible for HRV isolates. On the other hand, a comprehensive insight into the relationships between VP1 and partial 2A sequences of HRV and HEV revealed a genus-like situation. Distribution of pairwise nucleotide identity values between these genera varied from 41 to 54 % in the VP1 coding region, similar to those between heterologous members of the two HRV species. Alignment of the deduced amino acid sequences revealed more fully conserved amino acid residues between HRV-B and polioviruses than between the two HRV species. In phylogenetic trees, where all HRVs and representatives from all HEV species were included, the two HRV species did not cluster together but behaved like members of the same genus as the HEVs. In conclusion, from a phylogenetic point of view, there are no good reasons to keep these two human picornavirus genera taxonomically separated.
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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 and 1982 controls were extracted. Significant differences between patients and controls were found for (i) frequency domains such as HF-HRV [Hedges' g = −0.318; 95% CI (−0.388 to −0.247)], LF-HRV (Hedges' g = −0.195; 95% CI (−0.332 to −0.059)], LF/HF-HRV (Hedges' g = 0.195; 95% CI (0.086–0.303)] and VLF-HRV (Hedges' g = −0.096; 95% CI (−0.179 to −0.013)), and for (ii) time-domains such as IBI (Hedges' g = −0.163; 95% CI (−0.304 to −0.022)], RMSSD (Hedges' g = −0.462; 95% CI (−0.612 to −0.312)] and SDNN (Hedges' g = −0.266; 95% CI (−0.431 to −0.100)].ConclusionsOur findings demonstrate that all HRV-measures were lower in MD than in healthy controls and thus strengthens evidence for lower HRV as a potential cardiovascular risk factor in these 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 power, and the average transfer gain between respiration and heart rate. During cortical arousal, muscle sympathetic nerve activity and heart rate increased and returned rapidly to baseline, but systolic blood pressure, the ratio between low-frequency and high-frequency HRV power, low-frequency HRV power, the modified ratio of low-frequency to high-frequency HRV power, and low-frequency power of systolic BPV displayed increases that remained above baseline up to 40 s after arousal. High-frequency HRV power and airflow high-frequency power showed concommitant decreases to levels below baseline, whereas the average transfer gain between respiration and heart rate remained unchanged. These findings suggest that 1) arousal-induced changes in parasympathetic activity are strongly coupled to respiratory pattern and 2) the sympathoexcitatory cardiovascular effects of arousal are relatively long lasting and may accumulate if repetitive arousals occur in close succession.
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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.MethodsThe included primary studies present an aggregate of studies analyzing different HRV indices. Examined HRV indices were standard deviation of the normalized NN-intervals (SDNN), root mean square of successive differences (RMSSD), low-frequency (LF) and high-frequency (HF) spectral components, LF/HF ratio, and heart rate (HR). Moderating effects of study design, HRV and PTSD assessment, and sample characteristics were examined via subgroup-analyses and meta-regressions.ResultsRandom-effects meta-analyses for HRV parameters at rest revealed significant group differences for RMSSD and HF-HRV, suggesting lower parasympathetic activity in PTSD. The aggregated effect size for SDNN was medium, suggesting diminished total variability in PTSD. A small effect was found for LF-HRV. A higher LF/HF ratio was found in the PTSD sample as compared to controls. Individuals with PTSD showed significantly higher HR. During stress, individuals with PTSD showed higher HR and lower HF-HRV, both indicated by small effect sizes.ConclusionsFindings suggest that PTSD is associated with ANS dysfunction.
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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 Toolbox. The heartbeats in ECG were detected using the Pan–Tompkins algorithm and the heartbeats in SCG and GCG signals were detected as peaks within 100 ms from the occurrence of the ECG R waves. The results of time domain, frequency domain and nonlinear HRV analysis on ECG, SCG and GCG signals are similar and this phenomenon is confirmed by very strong linear correlation of HRV indices. The differences between HRV indices obtained on ECG and SCG and on ECG and GCG were statistically insignificant and encourage using SCG or GCG for HRV estimation. Our results of HRV analysis confirm stronger correlation of HRV indices computed on ECG and GCG signals than on ECG and SCG signals because of greater tolerance to inter-subject variability and disturbances.
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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 published sequences. Branching orders of VP4/VP2, VP1, and 3Dpol trees were identical, consistent with the absence of intraspecies recombination in the coding regions. However, numerous tree topology changes were apparent in the 5′ UTR, where >60% of analyzed HRV-C variants showed recombination with species A sequences. Two recombination hot spots in stem-loop 5 and the polypyrimidine tract in the 5′ UTR were mapped using the program GroupingScan. Available HRV-C sequences showed evidence for additional interspecies recombination with HRV-A in the 2A gene, with breakpoints mapping precisely to the boundaries of the C-terminal domain of the encoded proteinase. Pairwise distances between HRV-C variants in VP1 and VP4/VP2 regions fell into two separate distributions, resembling inter- and intraserotype distances of species A and B. These observations suggest that, without serological cross-neutralization data, HRV-C genetic groups may be equivalently classified into types using divergence thresholds derived from distance distributions. The extensive sequence data from multiple genome regions of HRV-C and analyses of recombination in the current study will assist future formulation of consensus criteria for HRV-C type assignment and identification.
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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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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 heart signal. Monitoring this physiological variation would be more efficient than monitoring their facial movements such as blinking, eye brow contraction, and yawning, which are said to happen after much longer time when compared to the immediate changes in the heart rate. Hence, an algorithm that detects drowsiness based on HRV analysis is developed and implemented by analyzing heart signals. Simple hardware setups were used to collect the ECG data, and digital filters were used to remove noise and extract the desired information for further analysis. The developed algorithm was implemented successfully and the results obtained were more precise and satisfactory. This approach of monitoring drowsiness is more reliable and accurate and when implemented with its necessary features, it can monitor drowsiness more effectively and save hundreds of lives every day.

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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 changes to be seen more clearly than the FFT of the original data set. Through statistical analysis it is also shown that the change in HRV from the atropine injection is much greater than the change in HRV from the saline injection.
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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 smartphone. Mental stress data was collected through stressful video gaming. This was compared to data from non-stressful activities, physical activity and extremely stressful activities such as public speaking events. By using the period between heartbeats and selecting features from the frequency domain, a simple machine learning algorithm could differentiate between the types of data and thus could effectively recognize mental stress. The study resulted in a collection of 100 data points, an algorithm to extract features and an application to continuously collect and classify sequences of heart periods. It also revealed an interesting relationship in the data between different subjects. The fact that continuous stress monitoring can be achieved using minimally intrusive sensors is the greatest benefit of these results, especially when connsidering its potential value in the identification and prevention of stress related disease.
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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 create applications in Matlab to calculate the quantifiers analysis of heart rate variability in the time domain using recurrent diagram. The calculation was made of the positions R wave elektrogram signal isolated rabbit hearts. The calculated values of quantifiers both methods were statistically evaluated and discussed.
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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 system is based on a centrally placed unit that coversthe whole buildings ventilation through vertical shafts. The second system is based onapartment placed unit that only covers the individual apartment’s ventilation. The unitmakes it possible for the individual user to control the ventilation flow.The method used for comparison of the costs was Life Cycle Cost (LCC). It results inthe total cost during a selected calculation period of 20 years, where yearly basedcosts as energy and maintenance is included. Two housing projects in central Uppsalawere chosen as a reference. They were similar in design but with the two differentsystems of ventilation. A questionnaire was handed out to provide experience fromresidents with apartment units. The results were used in the analysis of the systemsand to determine its pros and cons.Information of costs was collected from different companies and resulted intocustomized spreadsheets to determine the cost per apartment. The result shows thatthe difference in investment is not significant between the systems but is big inmaintenance and energy. The biggest difference is maintenance where the apartmentsystems many service points is increasing the cost. Energy consumption for theapartment system leads to higher energy costs than with a central system, even if thecontrol function is used. The explanation is that a central systems fans have lowerpower usage and the heat recovery is more efficient then an apartment system.The conclusion is that a central system has a lower total cost compared to anapartment system during the calculation period. A reason for choosing the apartmentsystem would be if a need to maximize living space is a priority, and the developingphase of the project is well thought thru.Keywords: LCC-analysis, HRV-systems, Central unit, Apartment unit.
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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 sensor embedded garments and artefacts that have been developed in collaboration with a fashion designer and an electronics engineer. The prototypes encourage remote empathetic connection through the real-time transference of heartbeat. The exegesis is structured into five chapters which consider remote presence, flexible consciousness, the architecture of empathy, plasticity in sense perception and the development of prototypes. The project chapter focuses in the development of and testing of a rnage of garments and artefacts thatt conduct presence information between remotely located people. The garments sense, process, transmit and receive the heartbeat signal (ECG). They are enabled with ECG sensors, signal processing equipment, small vibration motors and radio transceivers which allow users to 'feel' the heartbeat of a remote friend/lover/relative as vibration through their garment. The prototypes aim to enrich the remote communications experience through reintroducing an embodied, tactile dimension that is present in face-to-face communication. A range of user testing trials are discussed in the thesis which have been undertaken to assess the impact of the garments at a conscious and a non-conscious level. Conscious experiences were gauged through qualitative testing by way of interviews and unsolicited written reactions. Non-conscious physiological ractions were assessed by recording ECG throughout user-testing periods. This data has been processed by using HRV (heart rate variability) analysis software, running on MatLab.
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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 reflective human-computer-interfaces, this thesis combines these techniques by exploring the application of electrocardiography sensing technology in a heart rate variability (HRV) biofeedback system for the scenario of medita- tion practice. A proof-of-concept prototype was designed and implemented which quantifies stress and gives feedback on meditation effectiveness. For evaluation, a user study has been performed. Results were analysed in a systematic way to evaluate the feasibility and acceptance of the solution as well as the fidelity of HRV data that was measured during user tests. The prototype was found to be feasible in the context of technology acceptance while the fidelity of data, acquired by an algorithm for time and frequency domain analysis of HRV, was confirmed. A final conclusion is that the reflective aspect of the implemented real-time biofeedback system helps to improve regulatory capacity and thus lowers stress in individuals.
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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 marcador del equilibrio simpático/parasimpático desde el SNA. El objetivo para el Estudio 1 fue analizar la eficacia de la AR parea reducir la ansiedad y mejorar la concentración en el estudio en estudiantes universitarios. La muestra fue de 12 estudiantes (edad entre 18 y 33 años). Analizamos los efectos del aceite esencial de albahaca (Basil) a corto término (1 hora) y a largo término (1 mes). Encontramos que la inhalación del aceite esencial de albahaca reduce las puntuaciones de ansiedad y mejora la variabilidad cardíaca (parámetros SDRR y RMSSD). La AR en una sesión corta o con una botella aromática colgada del cuello cada día durante un mes produce cambios emocionales y de HRV en los participantes. El objetivo del Estudio 2 fue analizar la eficacia de la AR para mejorar el rendimiento laboral y reducir el estrés en el lugar de trabajo. La muestra estaba formada por 42 trabajadores universitarios administrativos (edad: 42.21 años, SD=7.12; género: 10 hombres y 32 mujeres). Todas las sesiones fueron realizadas en un aula universitaria de ordenadores personales. Los participantes fueron asignados al azar a un grupo de aromaterapia (AG) y a un grupo control (CG), y fueron invitados a participar en una sesión específica solo una vez. Se sentaron frente a un ordenador. Durante el período de intervención, se pusieron en marcha algunos difusores de aceite y se mantuvieron funcionando a lo largo de la sesión con aceite esencial de petit grain para las sesiones del grupo AG y un aceite neutro (almendra) para las sesiones de CG. Al mismo tiempo, los participantes completaron una tarea de ordenador en un sitio web específico escribiendo con su teclado hasta que la terminaron. Los tiempos fueron diferentes para todos los participantes y se registraron en el sitio web como "Tiempo de ejecución". El grupo de aromaterapia realizó la tarea del sitio web con el teclado 2, 28 min más rápido que la de CG (p = 0,05) y mostró una mejor variabilidad cardíaca (parámetros HF, SDNN y RMSSD). La inhalación de aceite esencial Petitgrain reduce el estrés y mejora el rendimiento en el lugar de trabajo. La AR mejora el tiempo de rendimiento al escribir con el teclado en una sesión simulada de trabajo de ordenador y produce algunos cambios mejorando la HRV. Conclusiones generales: Esta tesis doctoral confirma que la aromaterapia (inhalar aceites esenciales) puede mejorar el rendimiento en el lugar de trabajo, puede ayudar a manejar emociones negativas y puede incrementar el nivel de atención en situaciones académicas y laborales. Nuestros resultados confirman que la inhalación de aceites esenciales produce este efecto equilibrando el sistema simpático / parasimpático del Sistema Nervioso Autonómo. El análisis de HRV es un buen marcador de este efecto. Este equilibrio del SNA puede explicarse por una acción combinada de los componentes principales de los aceites esenciales Petitgrain y Basil. Algunos de ellos tienen efectos sedantes, que pueden inducir cambios en la actividad parasimpática, y otros componentes tienen efectos de activación, que estimulan la actividad simpática. El efecto final puede ser una mejora de la condición mental y emocional por una combinación de reducir el nivel de estrés y aumentar el nivel de arousal de los participantes en términos de atención y alerta. También podemos explicar nuestros resultados según la Medicina Tradicional China (TCM). Los aceites esenciales pueden trabajar a través de una terapia verdaderamente holística, teniendo en cuenta la mente, el cuerpo y el espíritu de la persona. Los aceites esenciales pueden conectarse con nuestro cuerpo y ayudarlo a encontrar la mejor manera de resolver sus necesidades. Los efectos relajantes (actividad parasimpática) pueden estar relacionados con el YIN y los efectos de activación (actividad simpática) pueden estar relacionados con el YANG.
The general aim of this thesis is to analyse the aromatherapy (AR) efficacy to reduce negative emotions and increase the attention level and performance in the workplace and in academic situations. Its efficacy will be tested through questionnaires and by checking the balance of the Autonomic Nervous System through HRV analysis. To carry out this general objective, we conducted two main studies. We will analyse the AR effects over the heart rate variability (HRV) as a marker of the sympathetic/parasympathetic balance from the ANS. The objective for Study 1 was to analyse the AR efficacy for reducing anxiety and improving study concentration in university students. The sample was composed by 12 students (age between 18 and 33 years old). We analysed the effects of basil essential oil inhalation at short-­‐time (1 hour) and at long-­‐time (1 month). We found that Inhalation of Basil essential oil reduces anxiety scoring and improves cardiac variability (SDRR and RMSSD parameters). AR in a short session or with an aromatic necklace every day during one month produces emotional and HRV changes on participants. The objective for Study 2 was to analyse the aromatherapy efficacy to improve the work performance and reduce the workplace stress. The sample was composed by 42 administrative university workers (age: 42.21 years, SD=7.12; gender: 10 men and 32 women). All sessions were performed in a university computer classroom. The participants were randomly assigned into an aromatherapy group (AG) and a control group (CG), and they were invited to participate in a specific session only once. They were seated in front of a computer. During the intervention period, some oil diffusers were launched and worked throughout the session with petit grain essential oil for AG sessions and a neutral oil (almond) for CG sessions. At the same time, participants completed a computer task in a specific website typing on their keyboard until they finished it. The single times were different for all participants and were recorded in the website as “Performance Time”. The aromatherapy group performed the website task with the keyboard 2, 28 min faster than CG typing (p=0.05) and showed better cardiac variability (HF, SDNN and RMSSD parameters). Inhalation of Petitgrain essential oil reduces stress and improves performance in the workplace. AR improves the performance time when typing with the keyboard in a simulated computer work session and produces some changes improving HRV. General Conclusions: This doctoral thesis confirms that aromatherapy (inhaling essential oils) can improve performance in the workplace, can help to manage negative emotions and can increment attention level in academic and workplace situations. Our results confirm that inhalation of essential oils produces this effect by balancing the sympathetic/parasympathetic system of the Autonomic Nervous System. HRV analysis is a good marker of this effect. This ANS balance can be explained by a combined action of the Petitgrain and Basil main components. Some of them have sedative effects, which can induce changes on the parasympathetic activity, and other components have activation effects, which stimulate the sympathetic activity. The final effect can be an improvement of the mental and emotional condition by a combination of reducing stress level and increasing arousal level of the participants in terms of attentiveness and alertness. We can also explain our results according to TCM. Essential oils can work through a truly holistic therapy, taking into account the mind, the body and the spirit of the person. Essential oils can connect with our body and help it to find the best way to solve its needs. The relaxing effects (parasympathetic activity) can be related to YIN and the activation effects (sympathetic activity) can be related to YANG.
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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"

1

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"

1

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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