Bioingeniería

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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."
Artificial pancreas: clinical study in Latin America without premeal insulin boluses
(2018-09) Sánchez-Peña, Ricardo; Colmegna, Patricio; Garelli, Fabricio; De Battista, Hernán; García Violini, Demián; Moscoso-Vásquez, Marcela; Rosales, Nicolás; Fushimi, Emilia; Campos-Náñez, Enrique; Breton, Marc; Beruto, Valeria; Scibona, Paula; Rodriguez, Cintia; Giunta, Javier; Simonovich, Ventura; Belloso, Waldo H.; Cherñavvsky, Daniel; Grosembacher, Luis
"Background: Emerging therapies such as closed-loop (CL) glucose control, also known as artificial pancreas (AP) systems, have shown significant improvement in type 1 diabetes mellitus (T1DM) management. However, demanding patient intervention is still required, particularly at meal times. To reduce treatment burden, the automatic regulation of glucose (ARG) algorithm mitigates postprandial glucose excursions without feedforward insulin boluses. This work assesses feasibility of this new strategy in a clinical trial. Methods: A 36-hour pilot study was performed on five T1DM subjects to validate the ARG algorithm. Subjects wore a subcutaneous continuous glucose monitor (CGM) and an insulin pump. Insulin delivery was solely commanded by the ARG algorithm, without premeal insulin boluses. This was the first clinical trial in Latin America to validate an AP controller. Results: For the total 36-hour period, results were as follows: average time of CGM readings in range 70-250 mg/dl: 88.6%, in range 70-180 mg/dl: 74.7%, <70 mg/dl: 5.8%, and <50 mg/dl: 0.8%. Results improved analyzing the final 15-hour period of this trial. In that case, the time spent in range was 70-250 mg/dl: 94.7%, in range 70-180 mg/dl: 82.6%, <70 mg/dl: 4.1%, and <50 mg/dl: 0.2%. During the last night the time spent in range was 70-250 mg/dl: 95%, in range 70-180 mg/dl: 87.7%, <70 mg/dl: 5.0%, and <50 mg/dl: 0.0%. No severe hypoglycemia occurred. No serious adverse events were reported. Conclusions: The ARG algorithm was successfully validated in a pilot clinical trial, encouraging further tests with a larger number of patients and in outpatient settings."
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."
Automated detection and quantification of reverse triggering efort under mechanical ventilation
(2021-02-15) Pham, Tài; Montanya, Jaume; Telias, Irene; Piraino, Thomas; Magrans, Rudys; Coudroy, Rémi; Damiani, L. Felipe; Mellado Artigas, Ricard; Madorno, Matías; Blanch, Lluis; Brochard, Laurent
"Reverse triggering (RT) is a dyssynchrony defned by a respiratory muscle contraction following a passive mechanical insufation. It is potentially harmful for the lung and the diaphragm, but its detection is challenging. Magnitude of efort generated by RT is currently unknown. Our objective was to validate supervised methods for automatic detection of RT using only airway pressure (Paw) and fow. A secondary objective was to describe the magnitude of the eforts generated during RT."
Automatic glucose control during meals and exercise in type 1 diabetes: proof-of-concept in silico tests using a switched LPV approach
(2021) Colmegna, Patricio; Bianchi, Fernando D.; Sánchez-Peña, Ricardo
"Keeping the blood glucose levels within the safe range during meals and exercise still represents a major hurdle not only for patients with type 1 diabetes (T1D), but also for Artificial Pancreas (AP) systems. One of the reasons a fully (autonomous) closed-loop solution has not been released onto the market yet is the slow action of current insulin analogs. To partially overcome this limitation, the authors have previously designed a switched control strategy equipped with an insulin-on-board (IOB) safety loop that mitigates meal-related glucose excursions without carbohydrate counting. In this paper, a similar strategy based on a Linear Parameter-Varying (LPV) control law has been adapted to safely handle also exercise challenges with minimum user intervention. In silico results using the UVA/Padova simulator evidence that the proposed closedloop scheme is feasible under moderate-intense exercise bouts by effectively and safely reducing the risk of hypoglycemia."
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."
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."
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."
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."
Control no-híbrido de glucemia ensayado en pacientes ambulatorios con Diabetes Tipo 1
(2022-07) Garelli, Fabricio; Fushimi, Emilia; Rosales, Nicolás; Arambarri, Delfina; Serafini, María Cecilia; De Battista, Hernán; Grosembacher, Luis; Sánchez-Peña, Ricardo
"En este trabajo se presenta la experiencia argentina en el problema de regulación de los niveles de glucosa en sangre para pacientes con Diabetes Mellitus Tipo 1 (insulino-dependientes), denominado Páncreas Artificial. El grupo de trabajo ha realizado 3 pruebas clínicas, las primeras en Latinoamérica. Las dos primeras fueron concretadas en 2016 y 2017, ambas en el Hospital Italiano de Buenos Aires (HIBA) con 5 pacientes adultos durante 36 hs. En la segunda de ellas se utilizó un nuevo algoritmo de control de lazo cerrado puro (sin bolo prandial), llamado ARG (Automatic Regulation of Glucose) y basado en un control LQG conmutado en combinación con una capa de seguridad llamada SAFE (Safety Auxiliary Feedback Element). Más recientemente y en plena pandemia de COVID-19 se llevó a cabo la primera prueba ambulatoria, realizada en 2021 en un hotel con 5 pacientes durante 6 días. En esta tercera prueba además, se utilizó una plataforma desarrollada por la Universidad Nacional de La Plata (UNLP), denominada InsuMate. Ésta conecta el celular con la bomba de insulina y el monitor de glucosa, aloja el algoritmo de control y permite el monitoreo remoto de múltiples pacientes. Los resultados obtenidos sugieren que el uso del algoritmo ARG en forma ambulatoria es factible, seguro y eficaz en comparación con la terapia usual. Asimismo, la plataforma InsuMate resultó ser intuitiva y sencilla para los usuarios, tanto médicos como pacientes participantes del ensayo, logrando un tiempo de funcionamiento del lazo cerrado superior al 95 %."
A control strategy for a tethered follower robot for pulmonary rehabilitation
(2020-12-03) Bianchi, Luciano Gustavo; Buniak, Esteban Alejandro; Ramele, Rodrigo; Santos, Juan Miguel
"Patients that suffer Chronic Obstructive Pulmonary Disease (COPD) undergo a procedure called Pulmonary Rehabilitation that helps them to improve disease prognosis. Pulmonary Rehabilitation consists of different physical exercises and walking activities conducted at medical facilities under supervision of a physical therapist. In order to perform these procedures, patients require oxygen assistance, but the oxygen tank cannot be carried by the patient due to the musculoskeletal atrophy that characterize this pathology and external assistance is required. The assistance to transport the bulky oxygen tank can be provided by a robotic device that follows the patient while performing the physical activities. This work provides an initial study on the controlling mechanism of a differential tethered robot that implements a leader-follower configuration to carry the oxygen tank for these procedures. Two alternative control strategies are proposed. Results on a simulated and on a real prototype confirms the feasibility of the proposed solution."
Control-oriented model with intra-patient variations for an artificial pancreas
(2020) Moscoso-Vásquez, Marcela; Colmegna, Patricio; Rosales, Nicolás; Garelli, Fabricio; Sánchez-Peña, Ricardo
"In this work, a low-order model designed for glucose regulation in Type 1 Diabetes Mellitus (T1DM) is obtained from the UVA/Padova metabolic simulator. It captures not only the nonlinear behavior of the glucose-insulin system, but also intrapatient variations related to daily insulin sensitivity (SI) changes. To overcome the large inter-subject variability, the model can also be personalized based on a priori patient information. The structure is amenable for linear parameter varying (LPV) controller design, and represents the dynamics from the subcutaneous insulin input to the subcutaneous glucose output. The eficacy of this model is evaluated in comparison with a previous control-oriented model which in turn is an improvement of previous models. Both models are compared in terms of their open- and closed-loop differences with respect to the UVA/Padova model. The proposed model outperforms previous T1DM control oriented models, which could potentially lead to more robust and reliable controllers for glycemia regulation."
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)."
Detection of atypical response trajectories in biomedical longitudinal databases
(De Gruyter, 2022-10-24) Pantazis, Lucio José; García, Rafael Antonio
Many health care professionals and institutions manage longitudinal databases, involving follow-ups for different patients over time. Longitudinal data frequently manifest additional complexities such as high variability, correlated measurements and missing data. Mixed effects models have been widely used to overcome these difficulties. This work proposes the use of linear mixed effects models as a tool that allows to search conceptually different types of anomalies in the data simultaneously.
Effect of PEEP on dead space in an experimental model of ARDS
(2020) Tusman, Gerardo; Gogniat, Emiliano; Madorno, Matías; Otero, Pablo; Dianti, José; Fernández Ceballos, Ignacio; Ceballos, Martín; Verdier, Natalí; Böhm, Stephan H.; Rodríguez, Pablo Oscar; San Román, Eduardo
"Background: Difference between Bohr and Enghoff dead space are not well described in ARDS patients. We aimed to analyze the effect of PEEP on the Bohr and Enghoff dead spaces in a model of ARDS. Methods: 10 pigs submitted to randomized PEEP steps of 0, 5, 10, 15, 20, 25 and 30 cm H2O were evaluated with the use of lung ultrasound images, alveolar-arterial oxygen difference (P(A-a)O2), transpulmonary mechanics, and volumetric capnography at each PEEP step. Results: At PEEP > 15 cm H2O, atelectasis and P(A-a)O2 progressively decreased while endinspiratory transpulmonary pressure (PL), end-expiratory PL, and driving PL increased (all P < .001). Bohr dead space (VDBohr/VT), airway dead space (VDaw/VT), and alveolar dead space (VDalv/VTalv) reached their highest values at PEEP 30 cm H2O (0.69 0.10, 0.53 0.13 and 0.35 0.06, respectively). At PEEP <15 cm H2O, the increases in atelectasis and P(A-a)O2 were associated with negative end-expiratory PL and highest driving PL. VDBohr/VT and VDaw/VT showed the lowest values at PEEP 0 cm H2O (0.51 0.08 and 0.32 0.08, respectively), whereas VDalv/VTalv increased to 0.27 0.05. Enghoff dead space and its derived VDalv/VTalv showed high values at low PEEPs (0.86 0.02 and 0.79 0.04, respectively) and at high PEEPs (0.84 0.04 and 0.65 0.12), with the lowest values at 15 cm H2O (0.77 0.05 and 0.61 0.11, respectively; all P < .001). CONCLUSIONS: Bohr dead space was associated to lung stress, whereas Enghoff dead space was partially affected by the shunt effect. Key words: dead space; PEEP; lung stress; ARDS; VILI; carbon dioxide."
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."
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."
Field Evaluation of Novel Spatial Repellent Controlled Release Devices (CRDs) against Mosquitoes in an Outdoor Setting in the Northern Peruvian Amazon
(Tropical Medicine and Infectious Disease, 7(11), 372. MDPI AG, 2022) Flores-Mendoza, Carmen; López-Sifuentes, Victor M.; Vásquez, Gissella M.; Stoops, Craig A.; Fisher, Michael L.; Bernier, Ulrich R.; Perry, Melynda; Mollica, Juan; Coltzau, Damián A.; Gurman, Pablo; D’hers, Sebastián; Elman, Noel M.
U.S. military troops are exposed to mosquito-borne pathogens when deployed to endemic regions. Personal protective measures such as permethrin-treated uniforms and dermal repellents are the cornerstones of mosquito-borne disease prevention for the U.S. military. These measures have limitations and additional personal protection tools, such as spatial repellent devices to decrease the risk of vector-borne pathogen transmission, are required. Novel spatial repellent controlled-release devices formulated with metofluthrin were evaluated in an outdoor setting in the northern Amazon of Peru to evaluate performance under field conditions. The metofluthrin emitting devices lowered the number of mosquitoes captured in protected human landing collections (HLC) compared to blank devices, although there were effect differences between Anopheles spp. and species in other mosquito genera. A computational-experimental model was developed to correlate HLC and active ingredient (AI) concentrations as a function of time and space. Results show a strong correlation between the released AI and the decrease in HLC. This model represents the first effort to obtain a predictive analytical tool on device performance using HLC as the entomological endpoint.
First outpatient clinical trial of a full closed-loop artificial pancreas system in South America
(2022-05) Garelli, Fabricio; Fushimi, Emilia; Rosales, Nicolás; Arambarri, Delfina; Mendoza, Leandro; Serafini, María Cecilia; Moscoso-Vásquez, Marcela; Stasi, Marianela; Duette, Patricia; García Arabehety, Julia; Giunta, Javier; De Battista, Hernán; Sánchez-Peña, Ricardo; Grosembacher, Luis
"The first two studies of an artificial pancreas (AP) system carried out in Latin America took place in 2016 (phase 1) and 2017 (phase 2). They evaluated a hybrid algorithm from the University of Virginia (UVA) and the automatic regulation of glucose (ARG) algorithm in an inpatient setting using an AP platform developed by the UVA. The ARG algorithm does not require carbohydrate (CHO) counting and does not deliver meal priming insulin boluses. Here, the first outpatient trial of the ARG algorithm using an own AP platform and doubling the duration of previous phases is presented."
Hand bone conduction sound study by using the DSP Logger MX 300
(2020) Adler, Melanie Victoria; Fialá Sánchez, Mariana; Martini, Constanza; Vartabedian, Luciana Mariam; Zazzali, Matías Nicolás; Quintero-Rincón, Antonio
"Bone conduction is the transmission of acoustic energy to the inner ear by different paths involving the bones of the skull. In this work, we use the path the hand provides in order to transmit the sound coming from the cell phone using Bluetooth system. The aim of this work was to study the vibrations produced by a sound transmitted through bone conduction between a mobile phone and the hand analyzed with the DSP Logger MX equipment."

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