Publications by authors named "Giraldo B"

Accurate monitoring of respiratory activity can lead to early identification and treatment of possible respiratory failure. However, spontaneous breathing can vary considerably. To quantify this variability, this study aimed at comparing the breathing pattern characteristics obtained from several recording sensors during different breathing types.

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Respiratory patterns present great variability, both in healthy subjects and in patients with different diseases and forms of nasal, oral, superficial or deep breathing. The analysis of this variability depends, among others, on the device used to record the signals that describe these patterns. In this study, we propose multivariable regression models to estimate tidal volume (V) considering different breathing patterns.

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Article Synopsis
  • A lot of older people have heart problems, making it hard to figure out their specific types of heart disease early on.
  • This study looked at 41 patients with different types of heart disease and compared them to 39 healthy people to see how their heart and breathing regulated blood pressure.
  • The researchers created models that were really good at classifying the different heart disease types, achieving over 92% accuracy in distinguishing between patient groups.
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The optimal extubating moment is still a challenge in clinical practice. Respiratory pattern variability analysis in patients assisted through mechanical ventilation to identify this optimal moment could contribute to this process. This work proposes the analysis of this variability using several time series obtained from the respiratory flow and electrocardiogram signals, applying techniques based on artificial intelligence.

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A large portion of the elderly population are affected by cardiovascular diseases. The early prognosis of cardiomyopathies is still a challenge. The aim of this study was to classify cardiomyopathy patients by their etiology in function of significant indexes extracted from the characterization of the recurrence plot of the systems involved.

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Cardiorespiratory Phase Synchronization (CRPS) is the manifestation of the non-linear coupling between the cardiac and the respiratory systems, different to the Respiratory Sinus Arrythmia (RSA). This takes place when the heartbeats occur at the same relative phase of the breathing, during a succession of respiratory cycles. In this study, we investigated the CRPS in 45 elderly patients admitted to the semi-critical unit of a hospital.

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Weaning from mechanical ventilation in the intensive care unit is a complex and relevant clinical problem. Prolonged mechanical ventilation leads to a variety of medical complications that increase hospital stay and costs, in addition to contributing the morbidity and mortality, affecting long-term quality of life. This work presents a methodology to establish the optimal moment of extubation of a patient connected to a mechanical ventilator, submitted to the T-Tube test.

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Prolonged use of mechanical ventilation (MV) can lead to greater complications for a patient. In clinical practice, it is important to identify patients who could fail in the extubation process. However, accurately predicting the outcome of this process remains a challenge.

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In clinical practice, when a patient is undergoing mechanical ventilation, it is important to identify the optimal moment for extubation, minimizing the risk of failure. However, this prediction remains a challenge in the clinical process. In this work, we propose a new protocol to study the extubation process, including the electromyographic diaphragm signal (diaEMG) recorded through 5-channels with surface electrodes around the diaphragm muscle.

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Cardiomyopathies diseases affects a great number of the elderly population. An adequate identification of the etiology of a cardiomyopathy patient is still a challenge. The aim of this study was to classify patients by their etiology in function of indexes extracted from the characterization of the pulse transit time (PTT).

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Electrostatically defined quantum dots (QDs) in Bernal stacked bilayer graphene (BLG) are a promising quantum information platform because of their long spin decoherence times, high sample quality, and tunability. Importantly, the shape of QD states determines the electron energy spectrum, the interactions between electrons, and the coupling of electrons to their environment, all of which are relevant for quantum information processing. Despite its importance, the shape of BLG QD states remains experimentally unexamined.

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Heart diseases are the leading cause of death in developed countries. Ascertaining the etiology of cardiomyopathies is still a challenge. The objective of this study was to classify cardiomyopathy patients through cardio, respiratory and vascular variability analysis, considering the vascular activity as the input and output of the baroreflex response.

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Respiration rate can be assessed by analyzing respiratory changes of the electrocardiogram (ECG). Several methods can be applied to derive the respiratory signal from the ECG (EDR signal). In this study, four EDR estimation methods based on QRS features were analyzed.

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Designing a thin-film structure often begins with choosing a film deposition method that employs a specific process by which chemical species are formed and transported; in other words, a film deposition system in which two deposition methods are hybridized should lead to new ways of designing thin-film structures. This premise inspires us to combine atomic layer deposition (ALD) and magnetron sputtering (SPU) within a single chamber-supttering atomic layer augmented deposition (SALAD). SALAD takes full advantage of both ALD's precise and accurate precursor delivery and SPU's versatility in choosing chemical elements.

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Obstructive Sleep Apnea severity is commonly determined after a sleep polysomnographic study by the Apnea-Hypopnea Index (AHI). This index does not contain information about the duration of events, and weights apneas and hypopneas alike. Significant differences in disease severity have been reported in patients with the same AHI.

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Cardiovascular diseases are one of the most common causes of death in elderly patients. The etiology of cardiomyopathies is difficult to discern clinically. The objective of this study was to classify cardiomyopathy patients using coupling analysis, through their cardiovascular behavior and the baroreflex response.

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Cardiovascular diseases are one of the most common causes of death; however, the early detection of patients at high risk of sudden cardiac death (SCD) remains an issue. The aim of this study was to analyze the cardio-vascular couplings based on heart rate variability (HRV) and blood pressure variability (BPV) analyses in order to introduce new indices for noninvasive risk stratification in idiopathic dilated cardiomyopathy patients (IDC). High-resolution electrocardiogram (ECG) and continuous noninvasive blood pressure (BP) signals were recorded in 91 IDC patients and 49 healthy subjects (CON).

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Several neurological and mechanical non-linear mechanisms relate the respiratory and cardiovascular systems to one another. Besides the well-known modulation of heart rate by respiration, another form of non-linear interaction between both systems is Cardiorespiratory Phase Synchronization (CRPS). In this study we investigated CRPS on a group of 27 healthy individuals subject to a stimulation protocol with five different mental states: a basal state, a videogame, a comedy video, a suspense video and a reading state.

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In congestive heart failure (CHF), dilated cardiomyopathy (DCM) and ischemic cardiomyopathy (ICM) are two highly related pathologies that are not fully characterized. The aim of this study is to assess respiratory sinus arrhythmia (RSA) index of the parasympathetic system, in order to discriminate between both pathologies, DCM and ICM. For this, ECG-signals of 49 subjects (12 DCM patients, 21 ICM patients, 6 ICM patients with diabetes mellitus (DM) type II and 10 control subjects) from the database HERIS II and of 173 subjects (50 DCM, 50 ICM, 15 DCM with DM type II, 15 ICM with DM type II and 47 control subjects) from the database MUSIC2 were analyzed.

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In this work, the cardiorespiratory pattern of patients undergoing extubation process is studied. First, the respiratory and cardiac signals were resampled, next the Symbolic Dynamics (SD) technique was implemented, followed of a dimensionality reduction applying Forward Selection (FS) and Moving Window with Variance Analysis (MWVA) methods. Finally, the Linear Discriminant Analysis (LDA) and Support Vector Machines (SVM) classifiers were used.

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Synchronization is a central key feature of neural information processing and communication between different brain areas. Disturbance of oscillatory brain rhythms and decreased synchronization have been associated with different disorders including schizophrenia. The aim of this study was to investigate whether synchronization (in relaxed conditions with no stimuli) between different brain areas within the delta, theta, alpha (alpha1, alpha2), beta (beta1, beta2), and gamma bands is altered in patients with a neurological disorder in order to generate significant cortical enhancements.

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Obstructive Sleep Apnea (OSA) is a sleep disorder with a high prevalence in the general population. It is a risk factor for many cardiovascular diseases, and an independent risk factor for cerebrovascular diseases such as stroke. After an apnea episode, both arterial blood pressure and cerebral blood flow velocity change in function of the apnea duration (AD).

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Cardiac death risk is still a big problem by an important part of the population, especially in elderly patients. In this study, we propose to characterize and analyze the cardiovascular and cardiorespiratory systems using the Poincaré plot. A total of 46 cardiomyopathy patients and 36 healthy subjets were analyzed.

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Aging population is a major concern that is reflected in the increase of chronic diseases. Heart Failure (HF) is one of the most common chronic diseases of elderly people that is punctuated with acute episodes, which result in hospitalization. The periodic modulation of the amplitude of the breathing pattern is proved to be one of the multiple symptoms of an acute episode, and thus, the features extracted from its characterization contribute in the improvement of the first diagnosis of the clinical practice.

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Changes in the left ventricle function produce alternans in the hemodynamic and electric behavior of the cardiovascular system. A total of 49 cardiomyopathy patients have been studied based on the blood pressure signal (BP), and were classified according to the left ventricular ejection fraction (LVEF) in low risk (LR: LVEF>35%, 17 patients) and high risk (HR: LVEF≤35, 32 patients) groups. We propose to characterize these patients using a linear and a nonlinear methods, based on the spectral estimation and the recurrence plot, respectively.

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