Nonlinear Systems in Healthcare towards Intelligent Disease Prediction

Healthcare is one of the key fields that works quite strongly with advanced analytical techniques for prediction of diseases and risks. Data being the most important asset in recent times, a huge amount of health data is being collected, thanks to the recent advancements of IoT, smart healthcare, etc. But the focal objective lies in making sense of that data and to obtain knowledge, using intelligent analytics. Nonlinear systems find use specifically in this field, working closely with health data. Using advanced methods of machine learning and computational intelligence, nonlinear analysis performs a key role in analyzing the enormous amount of data, aimed at finding important patterns and predicting diseases. Especially in the field of smart healthcare, this chapter explores some aspects of nonlinear systems in predictive analytics, providing a holistic view of the field as well as some examples to illustrate such intelligent systems toward disease prediction

Exploring Arterial Wave Frequency Features for Vascular Age Assessment through Supervised Learning with Risk Factor Insights

With aging being a major non-reversible risk factor for cardiovascular disease, the concept of Vascular Age (VA) emerges as a promising alternate measure to assess an individual’s cardiovascular risk and overall health. This study investigated the use of frequency features and Supervised Learning (SL) models for estimating a VA Age-Group (VAAG), as a surrogate of Chronological Age (CHA). Frequency features offer an accessible alternative to temporal and amplitude features, reducing reliance on high sampling frequencies and complex algorithms. Simulated subjects from One-dimensional models were employed to train SL algorithms, complemented with healthy in vivo subjects. Validation with real-world subject data was emphasized to ensure model applicability, using well-known risk factors as a form of cardiovascular health analysis and verification. Random Forest (RF) proved to be the best-performing model, achieving an accuracy/AUC score of 66.5%/0.59 for the in vivo test dataset, and 97.5%/0.99 for the in silico one. This research contributed to preventive medicine strategies, supporting early detection and personalized risk assessment for improved cardiovascular health outcomes across diverse populations.Fil: Ipar, Eugenia. Universidad Tecnologica Nacional. Facultad Regional Buenos Aires. Grupo de Investigacion y Desarrollo En Bioingenieria.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Cymberknop, Leandro Javier. Universidad Tecnologica Nacional. Facultad Regional Buenos Aires. Grupo de Investigacion y Desarrollo En Bioingenieria.; ArgentinaFil: Armentano, Ricardo Luis. Universidad de la República; Urugua

Fractal Analysis of Cardiovascular Signals Empowering the Bioengineering Knowledge

The cardiovascular system is composed of a complex network of vessels, where highly uniform hierarchical branching structures are regulated by the anatomy and local flow requirements. Arteries bifurcate many times before they become capillaries where the scaling factor of vessel length, diameter and angle between two children branches is established at each level of recurrence. This behaviour can be easily described using a fractal scaling principle. Moreover, it was observed that the basic pattern of blood distribution is also fractal, imposed both by the anatomy of the vascular tree and the local regulation of vascular tone. In this chapter, arterial physiology was analysed, where waveform complexity of arterial pressure time series was related to arterial stiffness changes, pulse pressure variations and the presence wave reflection. Fractal dimension was used as a nonlinear measure, giving place to a ‘holistic approach of fractal dimension variations throughout the arterial network’, both in health and disease

Analysis of ischaemic crisis using the informational causal entropy-complexity plane

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.Fil: Legnani, Walter. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires; Argentina. Universidad Nacional de Lanús; ArgentinaFil: Traversaro Varela, Francisco. Instituto Tecnológico de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Redelico, Francisco Oscar. Hospital Italiano; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Quilmes; ArgentinaFil: Cymberknop, Leandro Javier. Instituto Tecnologico de Buenos Aires. Departamento de Bioingenieria; Argentina. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires; ArgentinaFil: Armentano, Ricardo Luis. Universidad Tecnológica Nacional. Facultad Regional Buenos Aires; Argentina. Instituto Tecnologico de Buenos Aires. Departamento de Bioingenieria; ArgentinaFil: Rosso, Osvaldo Aníbal. Universidad de los Andes; Chile. Universidade Federal de Alagoas; Brasil. Hospital Italiano; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Device for the Evaluation of Carotid Arterial Pressure Based on IoT and 3D-Printing: uFISIO

El análisis de la forma de onda de presión aórtica central (PAC) permite un seguimiento más específico de patologías tales como la hipertensión arterial, la enfermedad coronaria y la diabetes. Se diseñó un dispositivo inalámbrico, portátil y ergonómico (uFISIO) para realizar evaluaciones morfológicas de la presión de la arteria carótida (PACar), que está estrechamente vinculada al comportamiento de la PAC. La forma de onda PACar fue adquirida por la técnica de tonometría de aplanamiento y enviada a un nodo central de una red inalámbrica local, para ser procesada en un dispositivo móvil. Los resultados fueron posteriormente transmitidos a un servidor central, en virtud del concepto 'Internet de las Cosas' (IoT). Complementariamente se utilizó tecnología de impresión 3D, para el desarrollo del diseño. El dispositivo fue probado en 6 individuos jóvenes, donde fueron evaluados parámetros morfológicos de PCar tales como el factor de forma, índice de aumento, tiempos característicos e integrales temporales a través de la aplicación móvil. Las formas de onda fueron adquiridas, transmitidas, procesadas y almacenadas adecuadamente, obteniendo valores de acuerdo con publicaciones anteriores. El dispositivo mostró versatilidad y confortabilidad en su utilización para evaluar PACar, así como para la gestión de la información resultante. Se requieren estudios futuros para determinar su aplicabilidad clínica, especialmente en diferentes grupos etarios.Pulse wave analysis of central aortic pressure waveform (CAP) allows a detailed follow-up of pathologies such as hypertension, coronary artery disease and diabetes. A wireless, portable and ergonomic device (uFISIO) was designed to perform morphological evaluations of carotid artery pressure (APCar), which is closely linked to CAP behavior. APCar waveform was acquired by the applanation tonometry technique and sent to a hub node of a local wireless network, in order to be processed in a mobile device. The results were posteriorly transmitted to a central server, in virtue of the ‘Internet of Things’ (IoT) concept. 3D printing technology was also used to develop the design. The device was tested in 6 young individuals, where APCar morphological parameters such as form factor, augmentation index, characteristic times and temporal integrals were assessed by the mobile application. Waveforms were acquired, transmitted, processed and stored adequately, obtaining values in agreement with previous publications. The device showed versatility and comfortability in its use for APCar evaluation, as well as for the management of the resulting information. Future studies are required to determine its clinical applicability, especially in different age groups.Fil: De Luca, Martín A.. Universidad Tecnologica Nacional. Facultad Regional Buenos Aires. Grupo de Investigacion y Desarrollo En Bioingenieria.; ArgentinaFil: Cymberknop, Leandro Javier. Universidad Tecnologica Nacional. Facultad Regional Buenos Aires. Grupo de Investigacion y Desarrollo En Bioingenieria.; ArgentinaFil: Meyer, Iván. Universidad Tecnologica Nacional. Facultad Regional Buenos Aires. Grupo de Investigacion y Desarrollo En Bioingenieria.; ArgentinaFil: Percunte, Maia Daniela. Universidad Tecnologica Nacional. Facultad Regional Buenos Aires. Grupo de Investigacion y Desarrollo En Bioingenieria.; ArgentinaFil: Chatterjee, Parag. Universidad Tecnologica Nacional. Facultad Regional Buenos Aires. Grupo de Investigacion y Desarrollo En Bioingenieria.; ArgentinaFil: Arbeitman, Claudia Roxana. Universidad Tecnologica Nacional. Facultad Regional Buenos Aires. Grupo de Investigacion y Desarrollo En Bioingenieria.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Armentano, Ricardo Luis. Universidad Tecnologica Nacional. Facultad Regional Buenos Aires. Grupo de Investigacion y Desarrollo En Bioingenieria.; Argentin

Internet of Things and Artificial Intelligence in Healthcare During COVID-19 Pandemic—A South American Perspective

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

Blood Pressure Morphology Assessment from Photoplethysmogram and Demographic Information Using Deep Learning with Attention Mechanism

International audienceArterial 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

Evaluación No-Invasiva de la Dinámica Cardiovascular a Utilizando Herramientas de Aprendizaje Estadístico

International audienceSe presentan algunos resultados con respecto a dos parámetros claves relacionados a la salud cardiovascular como la presión central y la velocidad de onda de pulso, así como también un marcador de puntos característicos de la señal de presión arterial basado en el aprendizaje profundo

Aplicación de Conceptos del Cálculo Diferencial al Estudio de la Curva de Presión Arterial. Una Experiencia Interdisciplinar

During the last years, new forms of pedagogy have been implemented in the engineering area, given that the real challenges that the future engineer will face must be addressed in an interdisciplinary way. For this reason, from the first years of his career and from the basic sciences, it is convenient for the student to deal with difficulties coming from other scenarios and thus be able to establish bridges between the different sciences and enhance the contributions of each one of them. The main objective of this work is to describe the result of an interdisciplinary experience in which the student was involved in applying mathematical concepts to a biological discipline. The experience was carried out with students of an Advanced Calculus course, corresponding to the first year of the different Engineering careers of the Buenos Aires Faculty at the Universidad Tecnológica Nacional, where an activity related to the concept of “engineering applied to the modeling of the cardiovascular system” was presented to them. To address it, 58 students had to apply concepts studied in the subject and incorporate those linked to human physiology. They also participated in both general data collection and assistance in data acquisition, which were later analyzed in group work. A descriptive methodology based on an individual questionnaire was considered, in order to complete the evaluation of the experience. The obtained results evidenced a high interest on the part of the students in dealing with problematic situations, with an 89% approval in relation to the importance to establish relationships between the different areas of knowledge. The activity was designed within the framework of the research and development project: "Use of interdisciplinary problems in mathematics subjects in engineering careers" together with the Group of Research and Development in Bioengineering, belonging to the same institution, and by virtue of the expertise of its members in topics related to cardiovascular health. Indeed, the obtained results demonstrate that the implementation of research-based teaching strategies, promotes an increase in student attention, a greater participation and provides a direct application of the studied mathematical tools.En estos últimos años se han implementado nuevas formas de pedagogía en el área de ingeniería, habida cuenta que los desafíos reales que enfrentará el futuro ingeniero deberán ser abordados de manera interdisciplinaria. Es por ello que desde los primeros años de su carrera y ya desde las ciencias básicas, es conveniente que el estudiante pueda enfrentar problemas procedentes de otros escenarios y así poder establecer puentes entre las distintas ciencias y potenciar los aportes de cada una de ellas. El objetivo principal del presente trabajo es describir el resultado de una experiencia interdisciplinar en la que se involucra al estudiante en la aplicación de conceptos matemáticos a una disciplina biológica. La experiencia se llevó a cabo con estudiantes cursantes de la asignatura Análisis Matemático I, correspondiente al primer año de las distintas carreras de Ingeniería de la Facultad Buenos Aires en la Universidad Tecnológica Nacional, a quienes se les presentó una actividad relacionada con el concepto de “ingeniería aplicada al modelado del sistema cardiovascular”. Para abordarla, 58 estudiantes debieron aplicar conceptos estudiados en la asignatura e incorporar aquellos ligados a la fisiología humana. Asimismo, participaron tanto en la recolección general de datos como en la asistencia para la adquisición de los mismos, que luego se analizaron en trabajos grupales. Se consideró una metodología descriptiva a partir de un cuestionario individual, con el objeto de completar la evaluación de la experiencia. Los resultados obtenidos evidenciaron un elevado interés por parte de los estudiantes en el abordaje de situaciones problemáticas, con un 89% de aprobación en relación a la importancia de establecer relaciones entre las distintas áreas de conocimiento. La actividad fue diseñada en el marco del proyecto de investigación y desarrollo: "Empleo de problemas interdisciplinarios en asignaturas de matemática en carreras de ingeniería" conjuntamente con el Grupo de Investigación y Desarrollo en Bioingeniería, perteneciente a la misma institución y en virtud de la experticia de sus integrantes en tópicos relacionados con la salud cardiovascular. Efectivamente, los resultados obtenidos demuestran que la implementación de estrategias interdisciplinares de enseñanza basadas en situaciones problemáticas propicia un incremento en la atención por parte del estudiante, una mayor participación y proporciona una aplicación directa de las herramientas matemáticas estudiadas

Predictive Risk Analysis for Liver Transplant Patients — eHealth Model Under National Liver Transplant Program, Uruguay

Recent years have seen a phenomenal change in healthcare paradigms and data analytics clubbed with computational intelligence has been a key player in this field. One of the main objectives of incorporating computational intelligence in healthcare analytics is to obtain better insights about the patients and proffer more efficient treatment. This work is based on liver transplant patients under the National Liver Transplant Program of Uruguay, considering in detail the health parameters of the patients. Applying computational intelligence helped to separate the cohort into clusters, thereby facilitating the efficient risk-group analysis of the patients assessed under the liver transplantation program with respect to their corresponding health parameters, in a predictive pre-transplant perspective. Also, this marks the foundation of Clinical Decision Support Systems in liver transplantation, which act as an assistive tool for the medical personnel in getting a deeper insight to patient health data and thanks to the holistic visualization of the healthcare scenario, also help in choosing a more efficient and personalized treatment strategy.Agencia Nacional de Investigación e Innovación (ANII), UruguayUniversidad Tecnológica Nacional, Buenos Aires, ArgentinaUniversidad de la República, UruguayDirección Nacional de Sanidad de la Fuerzas Armadas, Montevideo, Urugua