1,721,013 research outputs found

    A New Method for Continuous Relative Blood Volume and Plasma Sodium Concentration Estimation during Hemodialysis

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    Non-invasive sensing and reliable estimation of physiological parameters are important features of hemodialysis machines, especially for therapy customization (biofeedback). In this work, we present a new method for joint estimation of two important hemodialysis-related physiological parameters: relative blood volume and plasma sodium concentration. Methods: Our method makes use of a non-invasive sensor setup and of a mathematical estimator. The estimator, based on the Kalman filter, allows to merge data from multiple sensors, newly-designed as well as on-board, with modeling knowledge about the hemodialysis process. The system was validated on in-vitro hemodialysis sessions using bovine blood. Results: The estimation error we obtained (0.97±0.73% on relative blood volume and 0.47±0.19 mM on plasmatic sodium) proved to be comparable with that of reference data for both parameters: the system is sufficiently accurate to be relevant in a clinical context. Conclusion: Our system has the potential to provide accurate and important information on the state of a patient undergoing hemodialysis, while only low-cost modifications to the existing on-board sensors are required. Significance: Through improved knowledge of blood parameters during hemodialysis, our method will allow better patient monitoring and therapy customization in hemodialysis

    A Statistical Atrioventricular Node Model Accounting for Pathway Switching During Atrial Fibrillation

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    Objective: The atrioventricular (AV) node plays a central role in atrial fibrillation (AF) as it influences the conduction of impulses from the atria into the ventricles. In the present paper, the statistical dual pathway AV node model, previously introduced by us, is modified so that it accounts for atrial impulse pathway switching even if the preceding impulse did not cause a ventricular activation. Methods: The proposed change in model structure implies that the number of model parameters subjected to maximum likelihood estimation is reduced from five to four. The model is evaluated using the data acquired in the RATe control in Atrial Fibrillation (RATAF) study, involving 24- h ECG recordings from 60 patients with permanent AF. Results: When fitting the models to the RATAF database, similar results were obtained for both the present and the previous model, with a median fit of 86%. The results show that the parameter estimates characterizing refractory period prolongation exhibit considerably lower variation when using the present model, a finding that may be ascribed to fewer model parameters. Conclusion: The new model maintains the capability to model RR intervals, while providing more reliable parameters estimates. Significance: The model parameters are expected to convey novel clinical information, and may be useful for predicting the effect of rate control drugs

    OPERATION OF IMPLANTABLE MEDICAL DEVICE SYSTEM TO DETERMINE ATRIAL FIBRILLATION RECURRENCE LIKELIHOOD

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    In some examples a medical system comprising an implantable medical device and processing circuitry. The implantable medical device is configured to: sense a cardiac signal of a patient; detect a plurality of episodes of atrial fibrillation (AF) over a time period based on the cardiac signal; and stare AF episode data for the plurality of episodes of AF detected over the time period. The processing circuitry configured to: determine, based on the AF episode data, a first parameter representing a prevalence over the time of AF episodes and a second parameter representing a degree of temporal clustering of the AF episodes; determine a likelihood of recurrence of AF after an AF treatment procedure based on the first parameter and the second parameter; and transmit the likelihood to a computing device for presentation to a clinician

    ECG-derived Respiratory Rate in Atrial Fibrillation

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    Objective: The present study addresses the problem of estimating the respiratory rate from the morphological ECG variations in the presence of atrial fibrillatory waves (f-waves). The significance of performing f-wave suppression before respiratory rate estimation is investigated. Methods: The performance of a novel approach to ECG-derived respiration, named “slope range” (SR) and designed particularly for operation in atrial fibrillation (AF), is compared to that of two well-known methods based on either R-wave angle (RA) or QRS loop rotation angle (LA). A novel rule is proposed for spectral peak selection in respiratory rate estimation. The suppression of f-waves is accomplished using signal- and noise-dependent QRS weighted averaging. The performance evaluation embraces real as well as simulated ECG signals acquired from patients with persistent AF; the estimation error of the respiratory rate is determined for both types of signals. Results: Using real ECG signals and reference respiratory signals, rate estimation without f-wave suppression resulted in a median error of 0.015±0.021 Hz and 0.019±0.025 Hz for SR and RA, respectively, whereas LA with f-wave suppression resulted in 0.034±0.039 Hz. Using simulated signals, the results also demonstrate that f-wave suppression is superfluous for SR and RA, whereas it is essential for LA. Conclusion: The results show that SR offers the best performance as well as computational simplicity since f-wave suppression is not needed. Significance: The respiratory rate can be robustly estimated from the ECG in the presence of AF

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis

    Propagation pattern analysis during atrial fibrillation based on sparse modeling

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    Abstract in UndeterminedIn this study, sparse modeling is introduced for the estimation of propagation patterns in intracardiac atrial fibrillation (AF) signals. The estimation is based on the partial directed coherence function, derived from fitting a multivariate autoregressive model to the observed signal using least-squares (LS) estimation. The propagation pattern analysis incorporates prior information on sparse coupling as well as the distance between the recording sites. Two optimization methods are employed for estimation of the model parameters, namely, the adaptive group least absolute selection and shrinkage operator (aLASSO), and a novel method named the distance-adaptive group LASSO (dLASSO). Using simulated data, both optimization methods were superior to LS estimation with respect to detection and estimation performance. The normalized error between the true and estimated model parameters dropped from 0.20 +/- 0.04 for LS estimation to 0.03 +/- 0.01 for both aLASSO and dLASSO when the number of available data samples exceeded the number of model parameters by a factor of 5. For shorter data segments, the error reduction was more pronounced and information on the distance gained in importance. Propagation pattern analysis was also studied on intracardiac AF data, the results showing that the identification of propagation patterns is substantially simplified by the sparsity assumption
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