Browsing by Autor "Mauricio Peredo Claros"

Now showing 1 - 6 of 6

Advancements in Fourth-Generation Endodontic Apex Locators for Enhanced Precision in Root Canal Treatments
(2024) Facundo Calderon Cavero; Eynar Calle Viles; Mauricio Peredo Claros
This paper presents the comprehensive development and validation of an electronic apex locator designed specifically for endodontic treatments in Cochabamba, Bolivia. The device utilizes advanced impedance measurement techniques to accurately determine the position of dental files within root canals. By integrating cutting-edge electronic technology with specialized dental knowledge, this project aims to significantly enhance the precision and efficiency of root canal treatments in the region. The system incorporates a user-friendly interface, real-time data processing, and multiple output modalities. Extensive experimental results demonstrate high accuracy and repeatability in locating the root apex, validating its potential to substantially improve endodontic procedures and contribute to better oral health outcomes in the local population.
Estimation of Blood Pressure and Glucose through Photoplethysmography and Artificial Intelligence
(2024) James Gonzales; Eynar Calle Viles; Mauricio Peredo Claros
This article presents the development of a system for non-invasive measurement of blood pressure and glucose levels using photoplethysmography (PPG) and machine learning models. The system, called CARDIOPRESS, combines an optical sensor to capture heart rate and oxygen saturation (SpO2) data with machine learning algorithms to predict systolic and diastolic blood pressure, as well as blood glucose levels. Experimental results demonstrate a good approximation in the prediction of both blood pressure and glucose levels, validating its potential for continuous monitoring of cardiovascular and metabolic health.
Plataforma en la nube para la clasificación de objetos utilizando inteligencia artificial
(2022) Mauricio Peredo Claros; Edgar Roberto Ramos Silvestre
La Inteligencia Artificial (IA) es una de las áreas que más interés atrae en el ámbito de las Ciencias de la Computación, tanto desde el punto de vista científico-académico como del de sus múltiples aplicaciones en distintos sectores de actividad. A lo largo de la historia de la Inteligencia Artificial han surgido desarrollos y aplicaciones que la han convertido en un área de conocimiento consolidada e interés económico y social. Sin embargo, durante los últimos años, la IA ha experimentado un desarrollo excepcional, motivado por la aparición de tecnologías que han supuesto un gran avance en la disciplina y por la disponibilidad de recursos en hardware que han hecho viable su aplicación en distintos dominios. El interés de la sociedad en la Inteligencia Artificial ha crecido de forma proporcional a este desarrollo tecnológico. Prueba de ello es que gobiernos y administraciones en todos los niveles del Estado en diferentes países alrededor del mundo han promovido multitud de programas para financiar actividades de investigación, desarrollo e innovación en IA. Además, son muchas las empresas que han decidido llevar a cabo inversiones en IA para aplicar esta tecnología en distintos puntos de su cadena de valor. Aunque no existe una definición oficial y única de la Inteligencia Artificial todas ellas concuerdan en señalar que se trata de un campo de las Ciencias de la Computación que persigue desarrollar sistemas informáticos que exhiban características intelectuales similares a los humanos tales como la capacidad de razonar, aprender, generalizar, solucionar problemas, percibir y utilizar lenguaje natural, en resumen “imitar a los humanos” Este articulo está centrado en explicar el desarrollo de una plataforma en la nube para la clasificación de objetos utilizando Inteligencia Artificial, su principal aplicación será la de incrementar el conocimiento referente a este campo y coadyuvar en diferentes soluciones que se puedan plantear durante el uso de esta.
Prototype of a Portable Chest Compression Device
(Springer Nature, 2025) Marco Fabian Borda Wiegert; Mauricio Peredo Claros; Eynar Calle Viles; Rommer Alex Ortega Martínez
Prototype of innovative device for chest compression at the Universidad Private del Valle in Cochabamba, Bolivia
(2024) Marco Fabian Borda Wiegert; Mauricio Peredo Claros; Eynar Calle Viles; Rommer Alex Ortega Martínez
This article presents the development of a portable automatic chest compressor device using a rod-crank-piston mechanism. The main focus is on assessing the feasibility of manufacturing the device in Bolivia, primarily utilizing 3D printing technology and locally accessible components to create an economical device. The methodology involved reviewing appropriate techniques of Cardiopulmonary Resuscitation (CPR), analyzing the proposed mechanism, and researching chest compression devices available in the market for insights. Using this information as a foundation, a device inspired by the Weil Mini model was designed but implementing a rod-crank-piston mechanism for compressions. The construction of the prototype progressed through different phases, culminating in a portable device with manual control and the ability to store treatment data in a wirelessly connected application, allowing for equipment maintenance by service personnel. The conducted tests yielded satisfactory results, demonstrating that the device correctly compressed a calibrated CPR manikin, meeting all the requirements established by the American Heart Association (AHA) standards. Additionally, the development of software, implemented safety systems, and the creation of the web application for maintenance and data logging represent distinctive features of the prototype
Smartwatch-Based IoT System for Continuous Intravenous Infusion Monitoring with Air Bubble Blockage
(2024) Jhoseline Belen Yapur Pizarro; Eynar Calle Viles; Mauricio Peredo Claros; Elías Chávez Jaldín; Remmy Fuentes Telleria
Manual monitoring of intravenous (IV) infusions can result in errors or interruptions, particularly in healthcare settings with limited resources. This study introduces an Internet of Things (IoT)-based system designed to enhance the safety and efficiency of IV by enabling continuous, remote, and real-time monitoring. The proposed system integrates devices to measure fluid levels, detect blockages, and automatically prevent air bubbles from entering the bloodstream. Alerts are transmitted to healthcare professionals via smartwatches, ensuring prompt interventions. The system's efficacy was substantiated through calculations and laboratory tests, demonstrating its capacity to maintain precise fluid delivery and minimize the risk of medical errors. This innovative approach not only optimizes patient care but also reduces the workload on healthcare staff by automating routine monitoring tasks, thereby representing a significant advancement in healthcare technology.