Moya-Albor, Ernesto
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Moya-Albor, Ernesto
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Moya Albor, Ernesto
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emoya
Moya-Albor, E.
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55523223700
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J-1891-2019

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Motion magnification using the Hermite transform

2015 , Brieva, Jorge , Gomez-Coronel, Sandra L. , Moya-Albor, Ernesto , Escalante-Ramírez, Boris , Mora Esquivel, Juan I. , Ponce, Hiram

We present an Eulerian motion magnification technique with a spatial decomposition based on the Hermite Transform (HT). We compare our results to the approach presented in. We test our method in one sequence of the breathing of a newborn baby and on an MRI left ventricle sequence. Methods are compared using quantitative and qualitative metrics after the application of the motion magnification algorithm.

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Portable Device for Monitoring the Respiratory Rate in Home Conditions

2023 , Arizmendi Flores, Sergio Alejandro , Contreras Fernandez Del Castillo, Carlos , Solana Carreón, Diego Santiago , Zenteno Barreiro, Sebastián , Brieva, Jorge , Ponce, Hiram , Moya-Albor, Ernesto

During the last decades, technological advances have escalated at astronomical levels. One of the fields where technology has proven to be the most beneficial is in medicine. The vital signs monitoring is one of the medical areas with greater advances. Despite this technological advance in monitoring vital signs, heart rate and oxygen saturation are the ones that continue to be most used in diagnosis to the detriment of respiratory rate (RR) in medical and non medical environments. In this work we propose a preliminary contact device easy to use in non medical environments for monitoring, measuring and recording the RR. We test our device in controlled conditions in five healthy subjects. Accuracy will be computed through comparison of a visible estimation of the RR and the acquired data. The obtained mean PE% is less than 6% in normal conditions of utilisation for the experiments. Overall, our device has proven a reliable tool for RR measurement in this preliminary version. © 2023 IEEE.

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Non-contact breathing rate monitoring system using a magnification technique and artificial hydrocarbon networks

2020 , Brieva, Jorge , Moya-Albor, Ernesto , Ponce, Hiram

In this paper, we present a new non-contact strategy to estimate the breathing rate based on the Eulerian motion video magnification technique and an Artificial Hydrocarbon Networks (AHN) as classifier. After the magnification procedure, a AHN is trained to detect the inhalation and exhalation frames in the video. From this classification, the respiratory rate is estimated. The magnification procedure was carried out using the Hermite decomposition. The respiratory rate (RR) is estimated from the classified frames. We have tested the method on 10 healthy subjects in different positions. To compare performance of methods to 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 our strategy is 4.46 ± 3.68% with and agreement with respect of the reference of ˜ 98 %. © 2020 SPIE

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A non-contact SpO2 estimation using a video magnification technique

2021 , Brieva, Jorge , Moya-Albor, Ernesto , Ponce, Hiram

In this paper, we present a new non-contact strategy to estimate the Peripheral Oxygen Saturation (SpO2) based on the Eulerian motion video magnification technique and a signal processing technique. The magnification procedure was carried out using two approaches: the Hermite decomposition and the Gaussian decomposition. The SpO2 is estimated from the signals extracted after magnification process using the red and the blue channel of the image frame. We have tested the method on five healthy subjects using videos obtained from the googlemeet video conference platform. Each video includes the subject and the data of the contact pulse oximeter device. To compare the performance of the methods, we compute the mean average error and metrics issues from the Bland and Altman analysis to investigate the agreement of the methods with respect to a contact pulse oximeter device as reference. The proposed solution shows an agreement with respect to the reference of most of 98%. These preliminary results are promising for the implementation in a remote medical consultation setting. © 2021 SPIE.

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Vision-Based Autonomous Navigation with Evolutionary Learning

2020 , Moya-Albor, Ernesto , Ponce, Hiram , Brieva, Jorge , Coronel, Sandra L. , Chávez Domínguez, Rodrigo

In this paper, we propose a vision-based autonomous robotics navigation system, it uses a bio-inspired optical flow approach using the Hermite transform and a fuzzy logic controller, the input membership functions were tuned applying a distributed evolutionary learning based on social wound treatment inspired in the Megaponera analis ant. The proposed method was implemented in a virtual robotics system using the V-REP software and in communication con MATLAB. The results show that the optimization of the input fuzzy membership functions improves the navigation behavior against an empirical tuning of them. © 2020, Springer Nature Switzerland AG.

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SCOMA hand prosthetic

2021 , García, Carlos , Reyes, Arturo , Canul, Monserrat , Gurza, Octavio , Cruzado, Sebastián , Díaz, Joaquín , Brieva, Jorge , Moya-Albor, Ernesto , Ponce, Hiram

SCOMA Prosthetic Hand is a robotic hand that can give to the patient the ability to resume a good part of their daily activities. It is not only designed to resume daily activities, but also to improve the mental health of the patient. Worldwide, each year the number of amputees increases from 150,000 to 200,000 in which 30% of these amputees have suffered an upper limb amputation but only between 27% and 44% of them use arm prostheses. There are many reasons behind this, but some aspects to consider about existing prostheses are: uncomfortable, very expensive, have a robotic appearance, or need invasive procedures to fit patients. In our proposal we used the mechatronic design methodology and the data from the Amputee Coalition to create a new hand prosthesis. We analyzed it through different studies such as SWOT diagrams, quality matrix, goal tree and pairwise comparison matrix and simulation tests. In addition, we tested a 3D printing to find a suitable design and the most assertive components. By building the robotic hand with cheaper, more common components and limited functions, we can offer to the patients a comfortable prosthesis and a new more realistic option than those offer on the market. This prosthesis have limited functions but can be accessible to many people and the design could be improved in the future easily. © 2021 IEEE.

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Modular IoT-based Automated Hydroponic System

2021 , Aranda, Manlio , Savage, Alejandra , San Roman, José Luis , Noguera, Luis , Ponce, Hiram , Brieva, Jorge , Moya-Albor, Ernesto

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. © 2021 IEEE.

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RADAMA: Design of an Intelligent Waste Separator with the Combination of Different Sensors

2021 , Dávila Vega, Raúl Alberto , Hoyo de la Sema, Mauricio del , Meza Herz, David , Jurado Martinon, David , Menéndez Gomory, María de Lourdes , Pérez Martínez, Alan Gerardo , Moya-Albor, Ernesto , Ponce, Hiram , Brieva, Jorge

Nowadays, trash generation is a real problem. It is expected that high-income countries will experience waste generation growth in the future. A forecast shows that by 2050 there will be an exponential increase of close to 3.4 billion tonnes per year. Therefore, it is urgent to reduce the levels of garbage that are produced in the world. A possible solution is to develop recycling systems in all the big cities. In this regard, we propose a mechatronic system to separate solid wastes into four categories. To determine the category to which the inorganic waste belongs, we used a combination of four different sensors: inductive, capacitive, infrared, and ultrasonic sensors. To evaluate the efficiency of this proposal, we carried out tests that showed the individual conduct of every component and the total efficiency of the device, obtaining at least 75 percent in overall efficiency. © 2021 IEEE.

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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 , Brieva, Jorge , Moya-Albor, Ernesto

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.

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Non-contact breathing rate monitoring system using a magnification technique and convolutional networks

2020 , Brieva, Jorge , Ponce, Hiram , Moya-Albor, Ernesto

In this paper, we present a new non-contact strategy to estimate the breathing rate based on the Eulerian motion video magnification technique and a system based on a Convolutional Neural Network (CNN). After the magnification procedure, a CNN is trained to detect the inhalation and exhalation frames in the video. From this classification, the respiratory rate is estimated. The magnification procedure was carried out using the Hermite decomposition. Two strategies are used as input to the CNN. A CNN-ROI proposal where a region of interest is selected manually on the image frame and in the second case, a CNN-Whole-Image proposal where the entire image frame is selected. Finally, the RR is estimated from the classified frames. The CNN-ROI proposal is tested on five subjects in lying face down position and it is compared to a procedure using different image processing steps to tag the frames as inhalation or exhalation. The mean average error in percentage obtained for this proposal is 2.326±1.144%. The CNN-whole-image proposal is tested on eight subjects in lying face down position. The mean average error in percentage obtained for this proposal is 2.115 ± 1.135%. © COPYRIGHT 2020 SPIE. Downloading of the abstract is permitted for personal use ONLY.

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