Mexican Journal of Biomedical Engineering 2021-12-31T21:15:37+00:00 Prof. Cesár Antonio González Díaz Open Journal Systems <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The papers that are considered for being published in the RMIB must be original, unpublished, and first rate, and they can cover the areas of Medical Instrumentation, Biomedical Signals, Medical Information Technology, Biomaterials, Clinical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> Content Vol. 42 No. 3 (2021) 2021-12-31T21:15:37+00:00 Coordinador Editorial <p>E-book edition of the volume 42, number 3, year 2021, of the Revista Mexicana de Ingeniería Biomédica.</p> <p>In this issue:</p> <ul> <li class="show">A Practical Review of the Biomechanical Parameters Commonly Used in the Assessment of Human Gait</li> <li class="show">Image-based Glaucoma Classification Using Fundus Images and Deep Learning</li> <li class="show">Identification of 7 Movements of the Human Hand Using sEMG - 360° on the Forearm</li> <li class="show">The Shielding Volume Reduction in a High Dose Rate Brachytherapy Room</li> </ul> 2021-12-31T00:00:00+00:00 Copyright (c) Image-based Glaucoma Classification Using Fundus Images and Deep Learning 2021-11-21T19:40:58+00:00 Hiram José Sandoval-Cuellar Gendry Alfonso-Francia Miguel Ángel Vázquez-Membrillo Juan Manuel Ramos-Arreguín Saúl Tovar Arriaga <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> 2021-11-21T19:38:11+00:00 Copyright (c) 2021 Hiram José Sandoval-Cuellar, Gendry Alfonso-Francia, Miguel Ángel Vázquez-Membrillo, Juan Manuel Ramos-Arreguín, Saúl Tovar Arriaga Identification of 7 Movements of the Human Hand Using sEMG - 360° on the Forearm 2021-12-13T20:26:13+00:00 Adrian Ibarra Fuentes Eduardo Morales Sánchez <p>This document shows the identification of 7 gestures (movements) of the human hand from sEMG – 360° signals in the forearm. sEMG – 360° is the sEMG measurement through 8 channels every 45° making a total of 360°. When making a hand gesture, there will be 8 independents sEMG signals that will be used to identify the movement. The 7 gestures to identify are: relaxed hand (closed), open hand (fingers extended), flexion and extension of the little finger, the ring finger, the middle finger, the index finger and the thumb separately. 100 samples of each of the gesture were captured and 3 feature extractors were applied in the time domain (mean absolute value (MAV), root mean square value (RMS) and area vale under the curve (CUA)), then a vector support machine (SVM) classifier was applied to each extractor. The movements were identified and the percentage of accuracy in the identification was calculated for each extractor + SVM classifier. The calculation of the percentage of accuracy took into account the 8 channels for each gesture. 97.61 % accuracy was achieved in the identification of human hand gestures by applying sEMG – 360°.</p> 2021-12-13T20:26:12+00:00 Copyright (c) 2021 Adrian Ibarra Fuentes, Eduardo Morales Sánchez The Shielding Volume Reduction in a High Dose Rate Brachytherapy Room 2021-12-30T21:43:42+00:00 Sandra González Guzmán Héctor Miguel Montenegro Monroy Jonathan Pérez Honorato Miguel Angel Martínez Flores Federico Miranda Suárez <p>This paper describes a method to reduce the shielding thickness in a high dose brachytherapy treatment room, with an Iridium-192 source, using the protocols established by the International Atomic Energy Agency in its Safety Report No. 47; calculating the volume of shielding material, without failing to comply with the radiation safety parameters established by the General Radiation Safety Regulations and regulations in force by the <em>Comisión Nacional de Seguridad Nuclear y Salvaguardias</em>, which acts as the regulatory body for the use of radioactive sources in Mexico. The shielding of the walls was determined as a function of room design, source activity, workload, use factor, number of weekly treatments, treatment time, and shielding material properties. The results show that the shielding volume can be reduced by 19.592% and 20.727% for five-point and eleven-point fractionation, respectively, for a Brachytherapy room with a maze.</p> 2021-12-30T21:43:41+00:00 Copyright (c) 2021 Sandra González Guzmán, Héctor Miguel Montenegro Monroy, Jonathan Pérez Honorato, Miguel Angel Martínez Flores, Federico Miranda Suárez A Practical Review of the Biomechanical Parameters Commonly Used in the Assessment of Human Gait 2021-11-21T19:40:59+00:00 Juan Carlos Arellano-González Hugo Iván Medellín-Castillo J. Jesús Cervantes-Sánchez Agustín Vidal-Lesso <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> 2021-11-21T19:39:44+00:00 Copyright (c) 2021 Juan Carlos Arellano-González, Hugo Iván Medellín-Castillo, J. Jesús Cervantes-Sánchez, Agustín Vidal-Lesso