Revista Mexicana de Ingenieria Biomedica
http://rmib.mx/index.php/rmib
<center> <p><strong>MISSION</strong></p> <p align="left"><em>La Revista Mexicana de Ingeniería Biomédica</em> (The Mexican Journal of Biomedical Engineering, RMIB, for its Spanish acronym) is a publication oriented to the dissemination of papers of the Mexican and international scientific community whose lines of research are aligned to the improvement of the quality of life through engineering techniques.</p> <p align="left">The papers that are considered for being published in the RMIB must be original, unpublished, and first rate, and they can cover the areas of Medical Instrumentation, Biomedical Signals, Medical Information Technology, Biomaterials, Clinical Engineering, Physiological Models, and Medical Imaging as well as lines of research related to various branches of engineering applied to the health sciences.</p> <p align="left">The RMIB is an electronic journal published quarterly ( January, May, September) by the Mexican Society of Biomedical Engineering, founded since 1979. It publishes articles in spanish and english and is aimed at academics, researchers and professionals interested in the subspecialties of Biomedical Engineering.</p> <p><strong>INDEXES</strong></p> <p><em>La Revista Mexicana de Ingeniería Biomédica</em> is a quarterly publication, and it is found in the following indexes:</p> <p><img src="https://www.rmib.mx/public/site/images/administrador/índices_y_repositorios_(1100_×_1000 px).jpg" /></p> </center>Sociedad Mexicana de Ingeniería Biomédica A.C.en-USRevista Mexicana de Ingenieria Biomedica0188-9532<p>Upon acceptance of an article in the RMIB, corresponding authors will be asked to fulfill and sign the copyright and the journal publishing agreement, which will allow the RMIB authorization to publish this document in any media without limitations and without any cost. Authors may reuse parts of the paper in other documents and reproduce part or all of it for their personal use as long as a bibliographic reference is made to the RMIB. However written permission of the Publisher is required for resale or distribution outside the corresponding author institution and for all other derivative works, including compilations and translations.</p>Nonlinear Mathematical Analysis based on an Insulin-Pancreatic Cells Model in the Presence of Epinephrine
http://rmib.mx/index.php/rmib/article/view/1381
<p>In this work, a nonlinear model is studied based on ordinary differential equations that describe the relationship between the mass of cells and the secretion of epinephrine. It analyzes the impact of stress associated with the cause of increased blood pressure and glucose levels in the body. The mathematical analysis is based on the appliance of the nonlinear control theory to define the maximum load capacity for each state variable, establishing a bounded positive invariant domain through the Localization of Compact Invariants Sets (LCIS) method. The objective is to determine the effects of epinephrine secretion on the increase of blood glucose levels; therefore, this analysis's results define the necessary and sufficient conditions in which epinephrine raises insulin and glucose levels in the presence of cells. The interest in studying this type of disease focuses on searching for a treatment or an analysis that guarantees complete control of glucose levels. This work's development and mathematical analysis strengthen current research on insulin-dependent diabetes mellitus around critical epinephrine factors that imply an increase in glucose in the body.</p>Diana GamboaPaúl J. Campos
Copyright (c) 2024 Revista Mexicana de Ingenieria Biomedica
https://creativecommons.org/licenses/by-nc/4.0/
2024-03-122024-03-12451213010.17488/RMIB.45.1.2Preventive Detection of Driver Drowsiness from EEG Signals using Fuzzy Expert Systems
http://rmib.mx/index.php/rmib/article/view/1388
<p>Currently, the percentage of traffic accidents has increased, and according to statistics, this percentage will continue to increase every year, so it is necessary to develop new technologies to prevent this kind of accidents. This paper presents a drowsiness detection system based on electroencephalogram (EEG) signals using a pair of channels (Fp1 and Fp2) applied to drivers before entering their vehicles. First, this model detects the relationship between the area under the curve (AUC) of alpha brain waves, an effective parameter for detecting drowsiness. Then, the extracted information is passed to a fuzzy expert system (FES) that classifies the subject's state as "alert" or "sleepy"; the criterion used was a threshold and training with subjective levels. The proposed system was compared with neural network models, such as support vector machine (SVM), K nearest neighbors (KNN), and random forest (RF). Measurements of one hundred and twenty minutes were performed on each of the ten drivers for two days to test the system. The tests confirm that this system is suitable for preventive measures and that the fuzzy system is superior to traditional neural network methods.</p>Rony AlmironBruno Adolfo CastilloAndrés Montoya AnguloElvis SupoJesús José Fortunato TalaveraDaniel Domingo Yanyachi Aco Cardenas
Copyright (c) 2024 Revista Mexicana de Ingenieria Biomedica
https://creativecommons.org/licenses/by-nc/4.0/
2024-02-292024-02-2945162010.17488/RMIB.45.1.1