Mexican Journal of Biomedical Engineering https://rmib.com.mx/index.php/rmib <center> <div class="page" title="Page 1"> <div class="layoutArea"> <div class="column"> <p>Call for Papers for Special Issue on “Biomedical Engineering Innovations for Coronavirus COVID-19”</p> </div> </div> </div> <p><a href="Call%20for Papers for Special Issue on “Biomedical Engineering Innovations for Coronavirus COVID-19”"><strong>DOWNLOAD FULL INFO HERE</strong></a></p> <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The papers that are considered for being published in the RMIB must be original, unpublished, and first rate, and they can cover the areas of Medical Instrumentation, Biomedical Signals, Medical Information Technology, Biomaterials, Clinical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,&nbsp; founded since 1980. 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>&nbsp;<img src="/public/site/images/administrador/21.jpg" alt="" width="780" height="110"><img src="/public/site/images/administrador/1.jpg" alt="" width="780" height="110"><img src="/public/site/images/administrador/4.jpg" alt="" width="780" height="110"></p> <p><img src="/public/site/images/administrador/Unknown1.png" alt=""></p> </center> Sociedad Mexicana de Ingeniería Biomédica en-US Mexican Journal of Biomedical Engineering 0188-9532 <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 and a copy of the reference is sent. 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> <p>&nbsp;</p> Image-based Glaucoma Classification Using Fundus Images and Deep Learning https://rmib.com.mx/index.php/rmib/article/view/1188 <p>Glaucoma is an eye disease that gradually affects the optic nerve. Intravascular high pressure can be controlled to prevent total vision loss, but early glaucoma detection is crucial. The optic disc has been a notable landmark for finding abnormalities in the retina. The rapid development of computer vision techniques has made it possible to analyze eye conditions from images enabling to help a specialist to make a diagnosis using a technique that is non-invasive in its initial stage through fundus images. We propose a methodology glaucoma detection using deep learning. A convolutional neural network (CNN) is trained to extract multiple features, to classify fundus images. The accuracy, sensitivity, and the area under the curve obtained using the ORIGA database are 93.22%, 94.14%, and 93.98%. The use of the algorithm for the automatic region of interest detection in conjunction with our CNN structure considerably increases the glaucoma detecting accuracy in the ORIGA database.</p> Hiram José Sandoval-Cuellar Gendry Alfonso-Francia Miguel Ángel Vázquez-Membrillo Juan Manuel Ramos-Arreguín Saúl Tovar Arriaga Copyright (c) 2021 Hiram José Sandoval-Cuellar, Gendry Alfonso-Francia, Miguel Ángel Vázquez-Membrillo, Juan Manuel Ramos-Arreguín, Saúl Tovar Arriaga http://creativecommons.org/licenses/by/4.0 2021-11-21 2021-11-21 42 3 28 41 A Practical Review of the Biomechanical Parameters Commonly Used in the Assessment of Human Gait https://rmib.com.mx/index.php/rmib/article/view/1189 <p>The analysis of human gait is a potential diagnostic instrument for the early and timely identification of pathologies and disorders. It can also supply valuable data for the development of biomedical devices such as prostheses, orthoses, and rehabilitation systems. Although various research papers in the literature have used human gait analyses, few studies have focused on the biomechanical parameters used. This paper presents an extensive review and analysis of the main biomechanical parameters commonly used in the human gait study. The aim is to provide a practical guide to support and understand of the choices and selection of the most appropriate biomechanical parameters for gait analysis. A comprehensive search in scientific databases was conducted to identify, review and analyze the academic work related to human gait analysis. From this search, the main biomechanical parameters used in healthy and pathological gait studies were identified and analyzed. The results have revealed that the spatiotemporal and angular gait parameters are the most used in the assessment of healthy and pathological human gait.</p> Juan Carlos Arellano-González Hugo Iván Medellín-Castillo J. Jesús Cervantes-Sánchez Agustín Vidal-Lesso Copyright (c) 2021 Juan Carlos Arellano-González, Hugo Iván Medellín-Castillo, J. Jesús Cervantes-Sánchez, Agustín Vidal-Lesso http://creativecommons.org/licenses/by/4.0 2021-11-21 2021-11-21 42 3 6 27