Bioingeniería

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Time-varying procedures for insulin-dependent diabetes mellitus control
(2011-03) Sánchez-Peña, Ricardo; Ghersin, Alejandro S.; Bianchi, Fernando D.
"This work considers the problem of automatically controlling the glucose level in insulin dependent diabetes mellitus (IDDM) patients. The objective is to include several important and practical issues in the design: model uncertainty, time variations, nonlinearities, measurement noise, actuator delay and saturation, and real time implementation. These are fundamental issues to be solved in a device implementing this control. Two time-varying control procedures have been proposed which take into consideration all of them: linear parameter varying (LPV) and unfalsiﬁed control (UC). The controllers are implemented with low-order dynamics that adapt continuously according to the glucose levels measured in real time in one case (LPV) and by controller switching based on the actual performance in the other case (UC). Both controllers have performed adequately under all these practical restrictions, and a discussion on pros and cons of each method is presented at the end."
Herramienta web para post-análisis de simulaciones de dinámica molecular
(2013) Borgna, Karina Giselle; Fernández, María Laura; Risk, Marcelo
"En este trabajo se busca desarrollar una aplicación web interactiva y personalizada que permita analizar resultados generados mediante simulaciones de dinámica molecular. Con esta herramienta se pretende analizar las propiedades cada átomo o molécula de manera individual o conjunta a partir de una trayectoria, permitiendo segmentaciones tridimensionales que el usuario puede personalizar, así como análisis estadísticos no disponibles en las aplicaciones de post análisis que brindan los paquetes de dinámica molecular. Una herramienta de estas características es de gran ayuda en el estudio de los datos obtenidos permitiendo al usuario proponer el análisis o representación de los mismos que considere necesarios. Para este trabajo, como ejemplo, se tomaron datos generados por el programa Gromacs y fueron incorporados a una base de datos desarrollada en un entorno web. Se seleccionaron simulaciones de una bicapa lipídica expuesta a un campo eléctrico por el gran costo computacional que presenta de modo de generar una aplicación que pueda ser capaz de analizar datos independientemente de la demanda que éstos requieran. El sitio web se desarrolló con el framework Django, el cual permite utilizar Python, mientras que la base de datos se implementó en PostgreSQL. Se obtuvo una aplicación web que permite cargar datos de una trayectoria y generar un análisis estadístico, así como gráficos y representaciones espaciales. Se propone generar modelos 3D que permitan estimar superficie o volumen de la selección de átomos que el usuario considere necesarios."
Nanobioingeniería: historia y futuro
(2015) Risk, Marcelo
"Las aplicaciones de la nanotecnología desde la ingeniería a los ámbitos de la biología y la medicina constituyen la nanobioingeniería. Entonces la nanobioingeniería se puede describir como un área de trabajo multidisciplinaria, donde convergen las ciencias básicas como biología, matemática, química y física, con la medicina, la electrónica, la mecánica, informática y los aspectos éticos y legales."
Reducing glucose variability due to meals and postprandial exercise in TI DM using switched LPV control: in silico studies
(2016) Colmegna, Patricio; Sánchez-Peña, Ricardo; Gondhalekar, Ravi; Dassau, Eyal; Doyle III, Frank J.
"Time-varying dynamics is one of the main issues for achieving safe blood glucose control in type I diabetes mellitus (TI DM) patients. In addition, the typical disturbances considered for controller design are meals, which increase the glucose level, and physical activity (PA), which increases the subject's sensitivity to insulin. In previous works the authors have applied a linear parameter-varying (LPV) control technique to manage unannounced meals."
Switched LPV glucose control in type 1 diabetes
(2016-06) Colmegna, Patricio; Sánchez-Peña, Ricardo; Gondhalekar, Ravi; Dassau, Eyal; Doyle III, Frank J.
"The purpose of this work is to regulate the blood glucose level in Type 1 Diabetes Mellitus (T1DM) patients with a practical and flexible procedure that can switch amongst a finite number of distinct controllers, depending on the user´s choice."
User-centered design improves the usability of drug-drug interaction alerts: experimental comparison of interfaces
(2017) Luna, Daniel; Rizzato Lede, Daniel; Otero, Carlos; Risk, Marcelo; González Bernaldo de Quirós, Fernán
"Clinical Decision Support Systems can alert health professionals about drug interactions when they prescribe medications. The Hospital Italiano de Buenos Aires in Argentina developed an electronic health record with drug-drug interaction alerts, using traditional software engineering techniques and requirements. Despite enhancing the drug-drug interaction knowledge database, the alert override rate of this system was very high. We redesigned the alert system using user-centered design (UCD) and participatory design techniques to enhance the drug-drug interaction alert interface. This paper describes the methodology of our UCD. We used crossover method with realistic, clinical vignettes to compare usability of the standard and new software versions in terms of efficiency, effectiveness, and user satisfaction. Our study showed that, compared to the traditional alert system, the UCD alert system was more efficient (alerts faster resolution), more effective (tasks completed with fewer errors), and more satisfying. These results indicate that UCD techniques that follow ISO 9241-210 can generate more usable alerts than traditional design."
Classification of normal and pre-ictal EEG signals using permutation entropies and a generalized linear model as a classifier
(2017-02) Redelico, Francisco; Traversaro Varela, Francisco; García, María del Carmen; Silva, Walter; Rosso, Osvaldo A.; Risk, Marcelo
"In this contribution, a comparison between different permutation entropies as classifiers of electroencephalogram (EEG) records corresponding to normal and pre-ictal states is made. A discrete probability distribution function derived from symbolization techniques applied to the EEG signal is used to calculate the Tsallis entropy, Shannon Entropy, Renyi Entropy, and Min Entropy, and they are used separately as the only independent variable in a logistic regression model in order to evaluate its capacity as a classification variable in a inferential manner. The area under the Receiver Operating Characteristic (ROC) curve, along with the accuracy, sensitivity, and specificity are used to compare the models. All the permutation entropies are excellent classifiers, with an accuracy greater than 94.5% in every case, and a sensitivity greater than 97%. Accounting for the amplitude in the symbolization technique retains more information of the signal than its counterparts, and it could be a good candidate for automatic classification of EEG signals."
Predicción de crisis epilépticas utilizando el coeficiente de correlación producto-momento de Pearson a partir de un clasificador lineal de la distribución Gaussiana generalizada
(2018) Quintero-Rincón, Antonio; D'Giano, Carlos; Risk, Marcelo
"Predecir una crisis epiléptica significa la capacidad de determinar de antemano el momento de una crisis con la mayor precisión posible. Un pronóstico correcto de un evento epiléptico en aplicaciones clínicas es un problema típico en procesamiento de senales biomédicas, lo cual ayuda a un diagnóstico y tratamiento apropiado de esta enfermedad. En este trabajo, utilizamos el coeficiente de correlación producto-momento de Pearson a partir de las clases estimadas con un clasificador lineal, usando los parámetros de la distribución Gaussiana generalizada. Esto con el fin de poder pronosticar eventos con crisis y eventos con no-crisis en senales epilépticas. El desempeño en 36 eventos epilépticos de 9 pacientes muestra un buen rendimiento, con un 100% de efectividad para sensibilidad y especificidad superior al 83% para eventos con crisis en todos los ritmos cerebrales. El test de Pearson indica que todos los ritmos cerebrales están altamente correlacionados en los eventos con no-crisis, más no durante los eventos con crisis. Esto indica que nuestro modelo puede escalarse con el coeficiente de correlación producto-momento de Pearson para la detección de crisis en senales epilépticas."
Spike-and-wave detection in epileptic signals using cross-correlation and decision trees
(2018) Quintero-Rincón, Antonio; Alanis, Manuela; Muro, Valeria; D'Giano, Carlos
"Identify spike-and-waves patterns in epileptic signals is a typical problem in electroencephalographic (EEG) signal processing. In this paper we propose cross-correlation coupled with decision tree model as new method in order to assess and detect spike-and-wave discharges (SWD) in long-term epileptic signals. The proposed approach is demonstrated in terms of accuracy, sensitivity and specificity classification on real EEG signals using a database developed with medical annotations."
Real-time detection of imminent ventricular fibrillation using mean and standard deviation of beat-to-beat HRV
(2018) Mosquera, Candelaria; Racca, Dora María; Quintero-Rincón, Antonio
"It is estimated that 50% of all cardiovascular deaths are caused by a sudden cardiac arrest (SCA), which represents 15% of global mortality, and its main cause is ventricular fibrillation (VF). Therefore, it is of interest to design new methods capable to detect changes in heart rate (HR or RR interval) that could announce the beginning of an imminent fibrillation. In this work, an effective novel indicator, based on mean and standard deviation of Heart Rate Variability (HRV), was studied and used to develop an algorithm that predicts imminent VF with 100% sensitivity and 100% specificity. The study was based on 65 RR intervals signals. The algorithm’s simplicity provides a quick-to-use implementation in a micro controller unit (MCU) for real-time VF detection, allowing its application in a variety of medical devices with electrocardiogram (ECG) modules."
Asymmetric patterns of small molecule transport after nanosecond and microsecond electropermeabilization
(2018) Sözer, Esin B.; Pocetti, Florencia; Vernier, P. Thomas
"Imaging of fluorescent small molecule transport into electropermeabilized cells reveals polarized patterns of entry, which must reflect in some way the mechanisms of the migration of these molecules across the compromised membrane barrier. In some reports, transport occurs primarily across the areas of the membrane nearest the positive electrode (anode), but in others cathode-facing entry dominates. Here we compare YO-PRO-1, propidium, and calcein uptake into U-937 cells after nanosecond (6 ns) and microsecond (220 ls) electric pulse exposures. Each of the three dyes exhibits a different pattern. Calcein shows no preference for anode- or cathode-facing entry that is detectable with our measurement system. Immediately after a microsecond pulse, YO-PRO-1 and propidium enter the cell roughly equally from the positive and negative poles, but transport through the cathode-facing side dominates in less than 1 s. After nanosecond pulse permeabilization, YO-PRO-1 and propidium enter primarily on the anode-facing side of the cell."
Fast statistical model-based classification of epileptic EEG signals
(2018-01) Quintero-Rincón, Antonio; Pereyra, Marcelo; D'Giano, Carlos; Risk, Marcelo; Batatia, Hadj
"This paper presents a supervised classification method to accurately detect epileptic brain activity in real-time from electroencephalography (EEG) data. The proposed method has three main strengths: it has low computational cost, making it suitable for real-time implementation in EEG devices; it performs detection separately for each brain rhythm or EEG spectral band, following the current medical practices; and it can be trained with small datasets, which is key in clinical problems where there is limited annotated data available. This is in sharp contrast with modern approaches based on machine learning techniques, which achieve very high sensitivity and specificity but require large training sets with expert annotations that may not be available. The proposed method proceeds by first separating EEG signals into their five brain rhythms by using awavelet filter bank. Each brain rhythm signal is then mapped to a low-dimensional manifold by using a generalized Gaussian statistical model; this dimensionality reduction step is computationally straightforward and greatly improves supervised classification performance in problems with little training data available. Finally, this is followed by parallel linear classifications on the statistical manifold to detect if the signals exhibit healthy or abnormal brain activity in each spectral band. The good performance of the proposed method is demonstrated with an application to paediatric neurology using 39 EEG recordings from the Children's Hospital Boston database, where it achieves an average sensitivity of 98%, specificity of 88%, and detection latency of 4 s, performing similarly to the best approaches from the literature."
Transport of charged small molecules after electropermeabilization — drift and diffusion
(2018-03) Sözer, Esin B.; Pocetti, Florencia; Vernier, P. Thomas
"We provide a direct quantitative comparison of molecular transport of three similarly sized but chemically different fluorescent indicators of membrane permeabilization — two cationic molecules (YO-PRO-1 and propidium), and one anionic molecule (calcein). Our results show that the influx of YO-PRO-1 and propidium (both cations) into electropermeabilized cells is an order of magnitude greater than that of calcein (an anion) after the same pulse exposure. Calcein efflux from cells loaded before permeabilization, however, is similar in magnitude to YO-PRO-1 and propidium influx."
Electropore formation in mechanically constrained phospholipid bilayers
(2018-04) Fernández, María Laura; Risk, Marcelo; Vernier, P. Thomas
"Molecular dynamics simulations of lipid bilayers in aqueous systems reveal how an applied electric field stabilizes the reorganization of the water–membrane interface into water-filled, membrane-spanning, conductive pores with a symmetric, toroidal geometry. The pore formation process and the resulting symmetric structures are consistent with other mathematical approaches such as continuum models formulated to describe the electroporation process. Some experimental data suggest, however, that the shape of lipid electropores in living cell membranes may be asymmetric. We describe here the axially asym-metric pores that form when mechanical constraints are applied to selected phospholipid atoms. Electropore formation pro-ceeds even with severe constraints in place, but pore shape and pore formation time are affected. Since lateral and transverse movement of phospholipids may be restricted in cell membranes by covalent attachments to or non-covalent associations with other components of the membrane or to membrane-proximate intracellular or extracellular biomolecular assemblies, these lipid-constrained molecular models point the way to more realistic representations of cell membranes in electric fields."
Confidence intervals and hypothesis testing for the Permutation Entropy with an application to epilepsy
(2018-04) Traversaro Varela, Francisco; Redelico, Francisco
"In nonlinear dynamics, and to a lesser extent in other fields, a widely used measure of complexity is the Permutation Entropy. But there is still no known method to determine the accuracy of this measure. There has been little research on the statistical properties of this quantity that characterize time series. The literature describes some resampling methods of quantities used in nonlinear dynamics - as the largest Lyapunov exponent - but these seems to fail. In this contribution, we propose a parametric bootstrap methodology using a symbolic representation of the time series to obtain the distribution of the Permutation Entropy estimator. We perform several time series simulations given by well-known stochastic processes: the 1/f α noise family, and show in each case that the proposed accuracy measure is as efficient as the one obtained by the frequentist approach of repeating the experiment. The complexity of brain electrical activity, measured by the Permutation Entropy, has been extensively used in epilepsy research for detection in dynamical changes in electroencephalogram (EEG) signal with no consideration of the variability of this complexity measure. An application of the parametric bootstrap methodology is used to compare normal and pre-ictal EEG signals."
Automatic regulatory control in type 1 diabetes without carbohydrate counting
(2018-05) Colmegna, Patricio; Garelli, Fabricio; De Battista, Hernán; Sánchez-Peña, Ricardo
"A new approach to automatically regulate the glucose level in type 1 diabetes is presented in this work. This is the so-called Automatic Regulation of Glucose (ARG) algorithm, which is based on a switched Linear Quadratic Gaussian (LQG) inner controller, combined with an outer sliding mode safety loop with Insulin on Board (IOB) constraints. In silico and in vivo results without feedforward insulin boluses delivered at meal times indicate that safe blood glucose control can be achieved by the proposed controller. This controller is simple to migrate to well-known hardware platforms, and intuitive to tune using a priori clinical information."
Dead space analysis at different levels of positive end-expiratory pressure in acute respiratory distress syndrome patients
(2018-06) Gogniat, Emiliano; Ducrey, Marcela; Dianti, José; Madorno, Matías; Roux, Nicolás; Midley, Alejandro; Raffo, Julio; Giannasi, Sergio; San Román, Eduardo; Suárez-Sipmann, Fernando; Tusman, Gerardo
"To analyze the effects of positive end-expiratory pressure (PEEP) on Bohr's dead space (VDBohr/VT) in patients with acute respiratory distress syndrome (ARDS)."
Sizing the lung in dogs: the inspiratory capacity defines the tidal volume
(2018-06) Donati, Pablo Alejandro; Gogniat, Emiliano; Madorno, Matías; Guevara, Juan Manuel; Guillemi, Eliana Carolina; Lavalle, María del Carmen; Scorza, Francisco Patricio; Mayer, Germán Federico; Rodríguez, Pablo Oscar
"To evaluate a novel physiological approach for setting the tidal volume in mechanical ventilation according to inspiratory capacity, and to determine if it results in an appropriate mechanical and gas exchange measurements in healthy and critically ill dogs."
Analysis of ischaemic crisis using the informational causal entropy-complexity plane
(2018-07) Legnani, Walter; Traversaro Varela, Francisco; Redelico, Francisco; Cymberknop, Leandro J.; Armentano, Ricardo L.; Rosso, Osvaldo A.
"In the present work, an ischaemic process, mainly focused on the reperfusion stage, is studied using the informational causal entropy-complexity plane. Ischaemic wall behavior under this condition was analyzed through wall thickness and ventricular pressure variations, acquired during an obstructive flow maneuver performed on left coronary arteries of surgically instrumented animals. Basically, the induction of ischaemia depends on the temporary occlusion of left circumflex coronary artery (which supplies blood to the posterior left ventricular wall) that lasts for a few seconds. Normal perfusion of the wall was then reestablished while the anterior ventricular wall remained adequately perfused during the entire maneuver. The obtained results showed that system dynamics could be effectively described by entropy-complexity loops, in both abnormally and well perfused walls. These results could contribute to making an objective indicator of the recovery heart tissues after an ischaemic process, in a way to quantify the restoration of myocardial behavior after the supply of oxygen to the ventricular wall was suppressed for a brief period."
Bandt-Pompe symbolization dynamics for time series with tied values: a data-driven approach
(2018-07) Traversaro Varela, Francisco; Redelico, Francisco; Risk, Marcelo; Frery, Alejandro C.; Rosso, Osvaldo A.
"In 2002, Bandt and Pompe [Phys. Rev. Lett. 88, 174102 (2002)] introduced a successfully symbolic encoding scheme based on the ordinal relation between the amplitude of neighboring values of a given data sequence, from which the permutation entropy can be evaluated. Equalities in the analyzed sequence, for example, repeated equal values, deserve special attention and treatment as was shown recently by Zunino and co-workers [Phys. Lett. A 381, 1883 (2017)]. A significant number of equal values can give rise to false conclusions regarding the underlying temporal structures in practical contexts. In the present contribution, we review the different existing methodologies for treating time series with tied values by classifying them according to their different strategies. In addition, a novel data-driven imputation is presented that proves to outperform the existing methodologies and avoid the false conclusions pointed by Zunino and co-workers."

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