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Arterial stiffness is a major condition related to many cardiovascular diseases. Traditional approaches in the assessment of arterial stiffness supported by machine learning techniques are limited to the pulse wave velocity (PWV) estimation based on pressure signals from the peripheral arteries. Nevertheless, arterial stiffness can be assessed based on the pressure-strain relationship by analyzing its hysteresis loop. In this work, the capacity of deep learning models based on generative adversarial networks (GANs) to transfer pressure signals from the peripheral arterial region to pressure and area signals located in the central arterial region is explored. The studied signals are from a public and validated virtual database. Compared to other works in which the assessment of arterial stiffness was performed via PWV, in the present work the pressure-strain hysteresis loop is reconstructed and evaluated in terms of classical machine learning metrics and clinical parameters. Least-square GAN (LSGAN) and Wasserstein GAN with gradient penalty (WGAN-GP) adversarial losses are compared, yielding better results with LSGAN. LSGAN mean ± standard deviation of error for pressure and area pulse waveforms are 0.8 ± 0.4 mmHg and 0.1 ± 0.1 cm2, respectively. Regarding the pressure-strain elastic modulus, it is achieved a mean absolute percentage error of 6.5 ± 5.1%. GAN-based deep learning models can recover the pressure-strain loop of central arteries while observing pressure signals from peripheral arteries.

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Arterial blood pressure (ABP) is an important vital sign from which it can be extracted valuable information about the subject's health. After studying its morphology it is possible to diagnose cardiovascular diseases such as hypertension, so ABP routine control is recommended. The most common method of controlling ABP is the cuff-based method, from which it is obtained only the systolic and diastolic blood pressure (SBP and DBP, respectively). This paper proposes a cuff-free method to estimate the morphology of the average ABP pulse (ABPM¯) through a deep learning model based on a seq2seq architecture with attention mechanism. It only needs raw photoplethysmogram signals (PPG) from the finger and includes the capacity to integrate both categorical and continuous demographic information (DI). The experiments were performed on more than 1100 subjects from the MIMIC database for which their corresponding age and gender were consulted. Without allowing the use of data from the same subjects to train and test, the mean absolute errors (MAE) were 6.57 ± 0.20 and 14.39 ± 0.42 mmHg for DBP and SBP, respectively. For ABPM¯, R correlation coefficient and the MAE were 0.98 ± 0.001 and 8.89 ± 0.10 mmHg. In summary, this methodology is capable of transforming PPG into an ABP pulse, which obtains better results when DI of the subjects is used, potentially useful in times when wireless devices are becoming more popular.

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The shudders of the COVID-19 pandemic have projected newer challenges in the healthcare domain across the world. In South American scenario, severe issues and difficulties have been noticed in areas like patient consultations, remote monitoring, medical resources, healthcare personnel etc. This work is aimed at providing a holistic view to the digital healthcare during the times of COVID-19 pandemic in South America. It includes different initiatives like mobile apps, web-platforms and intelligent analyses toward early detection and overall healthcare management. In addition to discussing briefly the key issues toward extensive implementation of eHealth paradigms, this work also sheds light on some key aspects of Artificial Intelligence and the Internet of Things along their potential applications like clinical decision support systems and predictive risk modeling, especially in the direction of combating the emergent challenges due to the COVID-19 pandemic.

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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.

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To enhance the efficiency of patient-specific risk stratification and diagnosis, an assessment of arterial structural and functional changes associated to a vascular disease in both early and advanced stages have been proposed, with the objective of limiting the progression or revert vascular alterations. In this connection, an interdisciplinary international partnership made up by research institutions from France, Argentina, Uruguay and Spain was established, with the objective of contributing to the evaluation and follow-up of factors involved in the physiopathology of cardiometabolic diseases and human aging. Several studies, such as the effect of hypertension in large arteries, alterations in arterial wall viscosity, stiffness and inertia, endothelial function and vascular reactivity, cardiovascular risk improvement, vascular age assessment and cryografts vascular response evaluation were carried out as a result of this international collaboration during the last twenty-five years.

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This paper illustrates the evolution of our knowledge of arterial mechanics from our initial research works up to the present time. Several techniques focusing on this topic in terms of our experience are discussed. An interdisciplinary team composed by different institutions from Argentina, Uruguay, France and Spain was created to conduct research, to train human resources and to fulfill the inevitable social role of gaining access to technological innovation to improve public health.

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Arterial pressure waves have been described in one dimension using several approaches, such as lumped (Windkessel) or distributed (using Navier-Stokes equations) models. An alternative approach consists of modeling blood pressure waves using a Korteweg-de Vries (KdV) equation and representing pressure waves as combinations of solitons. This model captures many key features of wave propagation in the systemic network and, in particular, pulse pressure amplification (PPA), which is a mechanical biomarker of cardiovascular risk. The main objective of this work is to compare the propagation dynamics described by a KdV equation in a human-like arterial tree using acquired pressure waves. Furthermore, we analyzed the ability of our model to reproduce induced elastic changes in PPA due to different pathological conditions. To this end, numerical simulations were performed using acquired central pressure signals from different subject groups (young, adults, and hypertensive) as input and then comparing the output of the model with measured radial artery pressure waveforms. Pathological conditions were modeled as changes in arterial elasticity (E). Numerical results showed that the model was able to propagate acquired pressure waveforms and to reproduce PPA variations as a consequence of elastic changes. Calculated elasticity for each group was in accordance with the existing literature.

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The synergy amongst Engineering, Medicine and Biology evolves as fast as these disciplines. We propose to articulate these specialties based on the premise that new professionals must face different situations or crisis due to the so-called islands of excellence. René Favaloro focused his work and struggles against poverty, since malnutrition and environmental degradation may increase the propensity to cardiovascular diseases. Doctor Favaloro has dedicated, throughout his career, a considerable amount of time to prepare and qualify a research group, aware of the importance that an adequate working environment has over the final results. He created a team of young students, engineers, medical doctors, physicists, mathematicians and other specialists. He centered his attention on human resources, in order to disseminate his latest advances in Biology, Medicine and Engineering. We are revising the programs of biomedical engineering education and the application of new pedagogic paradigms, where critical thinking is the key: a holistic challenge that consists of a new way of learning, innovating, communicating and shearing, with a creative attitude that represents quality of perception.

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UNLABELLED: Arterial stiffening is a common but highly variable disorder. Additionally, excessive arterial pulsatility is associated with various common diseases of aging and hypertension. Fractal dimension (FD) quantifies the time series complexity defined by its geometrical representation. OBJECTIVE: Arterial pressure and diameter time series were evaluated in order to assess the relationship between arterial stiffness and FD. METHODS: Three Corriedale male sheep were operated. Left anterior descending artery (LAD) was dissected and the external arterial diameter was measured trough sonomicrometry. Similarly, a pressure microtransducer was positioned in the upper third of the ascending aorta. Simultaneous pressure and diameter were measured in normal state and under smooth muscle activation. Each time series FD were assessed by the application of Higuchi's method while arterial wall elastic modulus was evaluated by means of the pressure-strain relationship. RESULTS: Coronary stiffness was increased from normal state to phenylephrine state (47.32%, 21.12%, 10.87%) while aortic pressure FD was decreased (2.11%, 2.57%, 6.85%), respectively. CONCLUSION: Acute hypertension induced by phenylephrine produces an increase in the coronary wall elastic modulus with a concomitant decrease in the fractal nature of the aortic pressure, suggesting that coronary stiffening is associated with an unwrinkled aortic pressure.

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