Brieva, Jorge

Main Affiliation

Facultad de Ingeniería - CampCM

Preferred name

Brieva, Jorge

Official Name

Brieva Rico, Jorge Eduardo

ORCID

0000-0002-5430-8778

Researcher ID

GMW-951-2022

Scopus Author ID

7005997081

Web Site

https://www.up.edu.mx/investigacion/jorge-eduardo-brieva-rico/

Now showing 1 - 10 of 86

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A Contactless Respiratory Rate Estimation Method Using a Hermite Magnification Technique and Convolutional Neural Networks
(MDPI, 2020)
Brieva, Jorge
;
Ponce, Hiram
;
Moya-Albor, Ernesto
The monitoring of respiratory rate is a relevant factor in medical applications and day-to-day activities. Contact sensors have been used mostly as a direct solution and they have shown their effectiveness, but with some disadvantages for example in vulnerable skins such as burns patients. For this reason, contactless monitoring systems are gaining increasing attention for respiratory detection. In this paper, we present a new non-contact strategy to estimate respiratory rate based on Eulerian motion video magnification technique using Hermite transform and a system based on a Convolutional Neural Network (CNN). The system tracks chest movements of the subject using two strategies: using a manually selected ROI and without the selection of a ROI in the image frame. The system is based on the classifications of the frames as an inhalation or exhalation using CNN. Our proposal has been tested on 10 healthy subjects in different positions. To compare performance of methods to detect respiratory rate the mean average error and a Bland and Altman analysis is used to investigate the agreement of the methods. The mean average error for the automatic strategy is 3.28± 3.33% with and agreement with respect of the reference of 98%. © 2020 by the authors.
Scopus© Citations 30 1 36
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A fast and bio-inspired optical flow approach in cardiac MRI sequences
(2018)
Moya-Albor, Ernesto
;
Brieva, Jorge
In this paper we present a fast and bio-inspired optical flow estimation method. It uses the Steered Hermite transform into an optimized Horn and Schunck approach. We tested the proposal method in cardiac MRI sequences of the MICCAI 2009 challenge. © 2018 IEEE.
Scopus© Citations 3 1 4
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Stair Climbing Robot Based on Convolutional Neural Networks for Visual Impaired
(2019)
Campos, Guillermo
;
Poza, David
;
Reyes, Moises
;
Zacate, Alma
;
Ponce, Hiram
When a person loses the sense of sight, in general, it is suggested to use a white cane to perform daily activities. However, using a white cane limits the movement of a person. In addition, guide dogs can be served in this impairment. However, the acquisition and maintenance of a guide dog is extremely high for people in development countries. In this regard, this paper presents a proof-of-concept of a low-cost robotic system able to guide a visual impaired, as a guide dog. The robot is specially designed for climbing stairs at indoors, and it uses convolutional neural networks (CNN) for both object detection and hand gesture recognition for special instructions from the user. Experimental results showed that our prototype robot can climb stairs with 86.7% of efficiency in concrete stair surfaces. Also, the visual representation by CNN performed more than 98% accuracy. © 2019 IEEE.
1 29Scopus© Citations 5
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Image analysis applied to a freeze-concentration water purification system
(2017)
Pardo Benito, José Mauricio
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Moya-Albor, Ernesto
;
Ortega Ibarra, Germán
;
Brieva, Jorge
Freeze concentration is a promising water purification technology, specially due to the low levels of energy consumption when compared with other processes such as evaporation. Nevertheless, its development is still at pilot plant scale and more knowledge of the process is needed. One of the important parameters needed for design and control of the process is the growth velocity of the crystal, commonly known as the limit velocity. Above this velocity ice crystals will entrap solids and separation will not be successful. In this work, we describe a non-invasive technique to measure this limit velocity based on image analysis. Photographs were taken every 30 minutes in an experimental rig that allowed to freeze the sample unidirectionally. Back lighting was used in order to observe variations in luminosity at the samples surface. Image processing algorithms were used to segment the image, to identify the freezing front and to model its movement. Under the experimental conditions of this work, it was determined that the limiting freezing front velocity was 1.17 mm/h, which is a valuable information for the design and control of the process. © 2018 IMEKO-International Measurement Federation Secretariat. All rights reserved.
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Modular IoT-based Automated Hydroponic System
(IEEE, 2021)
Aranda, Manlio
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Savage, Alejandra
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San Roman, José Luis
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Noguera, Luis
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Ponce, Hiram
The growth of population and the rapid urbanization have demanded overproduction of food while reducing the water supply, increasing energy consumption, limiting the land, and augmenting the cost of food transportation. Moreover, overproduction comes with food waste and a negative impact on the ecosystem. As an alternative, urban farming has been proposed to mitigate this problem. It includes cultivating in rooftops and residential indoors. In this regard, this work proposes the development of an automatic modular and vertical hydroponic system capable to regulate the water flow, the artificial lights, and the pH of the water. The hydroponic system is made of modules which means the user can upgrade the system depending on the needs like higher production or space reconfiguration. Also, the hydroponic system implements Internet-of-Things to monitor and operate it remotely. A first prototype is presented, and the experimental results validate its potential applicability. ©The authors © 2021 IEEE.
33 5Scopus© Citations 5
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3D Hermite Transform Optical Flow Estimation in Left Ventricle CT Sequences
(2020)
Mira, Carlos
;
Moya-Albor, Ernesto
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Escalante-Ramírez, Boris
;
Olveres, Jimena
;
Brieva, Jorge
Heart diseases are the most important causes of death in the world and over the years, the study of cardiac movement has been carried out mainly in two dimensions, however, it is important to consider that the deformations due to the movement of the heart occur in a three-dimensional space. The 3D + t analysis allows to describe most of the motions of the heart, for example, the twisting motion that takes place on every beat cycle that allows us identifying abnormalities of the heart walls. Therefore, it is necessary to develop algorithms that help specialists understand the cardiac movement. In this work, we developed a new approach to determine the cardiac movement in three dimensions using a differential optical flow approach in which we use the steered Hermite transform (SHT) which allows us to decompose cardiac volumes taking advantage of it as a model of the human vision system (HVS). Our proposal was tested in complete cardiac computed tomography (CT) volumes ( 3D + t), as well as its respective left ventricular segmentation. The robustness to noise was tested with good results. The evaluation of the results was carried out through errors in forwarding reconstruction, from the volume at time t to time t + 1 using the optical flow obtained (interpolation errors). The parameters were tuned extensively. In the case of the 2D algorithm, the interpolation errors and normalized interpolation errors are very close and below the values reported in ground truth flows. In the case of the 3D algorithm, the results were compared with another similar method in 3D and the interpolation errors remained below 0.1. These results of interpolation errors for complete cardiac volumes and the left ventricle are shown graphically for clarity. Finally, a series of graphs are observed where the characteristic of contraction and dilation of the left ventricle is evident through the representation of the 3D optical flow. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
Scopus© Citations 6 2 12
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Neural Architecture Search Using Trajectory Metaheuristics to Classify Coronary Stenosis
(IEEE, 2024)
Franco-Gaona, Erick
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Avila-Garcia, Maria-Susana
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Cruz-Aceves, Ivan
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Orocio-Garcia, Hiram-Efrain
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Escobedo-Gordillo, Andrés
Coronary stenosis is a disease that claims millions of lives each year. Early detection of this condition is crucial for patient survival. Currently, physicians perform detection by x-ray angiograms, however, the variability of diagnoses and the difficulty of access to expertise has led to the need for automated, computer-assisted diagnosis. In this work explores the use of deep learning to classify stenosis or non-stenosis in angiogram images using convolutional neural networks from scratch. A methodology to fine-tuning network architectures automatically using metaheuristic optimization techniques is proposed, demonstrating superior performance to fine-tuning empirically and proposing a new architecture in the literature to classify coronary stenosis. The proposed architectures achieved 86.02% and 95.67% F1-score with simulated annealing and iterated local search techniques, respectively. ©The authors ©IEEE
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From Project-Based Learning to Innovative Technologies in Mechatronics Course: A Case Study in a Private University in Mexico City
(Springer, 2024-01-01)
Ponce, Hiram
;
Moya-Albor, Ernesto
;
Brieva, Jorge
Mechatronics engineering is a challenging discipline that needs different thinking and practices in contrast with traditional engineering. This challenging is mainly due to the demand of integration, collaboration and holistic approaches required during the design methodology. This study examines the transformation from traditional education to an in-deep professional and research focused projects. The key factor in the mechatronics learning practice includes the implementation of a major project focused on positive social impact solutions and the road map developed for this purpose. This work proposes a methodology that allows students develop a major project with a holistic view, including design constraints related to specific contextual aspects as economics, environmental, societal, ethical, health and sustainability. Also, students are able to develop professional and research skills. The methodology also allows students propose a major project focused on positive social impact with design constraints. It also exposes students different engineering and computational tools for collaboration and integration. The study uses data from 69 students enrolled along four years, from 2016 to 2019. Results show that the student learning outcomes increased significantly at the end of the period time, from to (in range between 0 to 4), reaching the satisfactory level (year-2016 as baseline). Also, 100% of the scientific papers derived from the major projects were accepted for publication in international conferences © 2024 Springer Nature
24Scopus© Citations 1
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Metaheuristic Strategy in Automatic Robotics Navigation for Patient Care in Hospitals
(Springer Nature Switzerland, 2025)
Monroy-Rueda, Irvine J.
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Moya-Albor, Ernesto
;
Brieva, Jorge
;
Ponce, Hiram
This chapter presents a novel approach for developing a global automatic navigation strategy for a mobile robot for patient care into health centers and hospitals. The proposal uses a metaheuristic strategy through the Grey Wolf Optimizer algorithm to find the shortest route between the robot’s starting and patient destination points, while also integrating knowledge of the environment acquired through vision. The global navigation tracking is achieved through the use of Fuzzy Logic Rules to control the robot’s wheel velocity according to its current position and orientation. The proposed strategy was implemented in a virtual robotics environment demonstrating that the approach successfully generated optimal paths for various environments with a minimal number of control points and in a relatively short amount of time. In addition, a simulated hospital room with common furniture and tasks was used to evaluate the performance of the global navigation strategy, demonstrating that the robot could successfully generate a global route and navigate within this environment. ©The authors ©Springer.
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Mechatronic Design of a Low-Cost Smart Wheelchair Controlled by Joystick and Voice Commands
(2023)
Bobadilla-Rendón, David
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Monroy-Rueda de León, Irvine J.
;
Salazar-Salinas, Gabriel
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Stefan-Lepe De Soto, Antonio
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Ponce, Hiram
Elderly people have increased at an accelerated rate in recent years. In Mexico, one of the main problems affecting this population are related to disabilities, specifically limited mobility, i.e., arthritis in older adults. Different technological solutions have been proposed, such as electrical wheelchairs. However, for arthritic people, these wheelchairs are difficult to operate, lacking comfortability, and might be very expensive. In this work, we propose the development of a smart wheelchair for arthritic older adults able to move automatically and controlled by using slight manual movements of the hand and by voice commands. We followed the general methodology of a mechatronic design. A proof-of-concept model of the wheelchair was implemented. For validation, we tested the prototype in different real indoor scenarios. Results conclude that our proposed smart wheelchair complies with the user requirements, it is easy to operate, and the cost is reduced considerably. We anticipate this is a low-cost efficient smart wheelchair prototype that can be further considered for real technological solutions.
2 30Scopus© Citations 2

Brieva, Jorge

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