Ciencias Exactas y Ciencias de la Salud
Permanent URI for this collectionhttps://hdl.handle.net/11285/551039
Pertenecen a esta colección Tesis y Trabajos de grado de las Maestrías correspondientes a las Escuelas de Ingeniería y Ciencias así como a Medicina y Ciencias de la Salud.
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- Vibrotactile feedback for real-time wrist posture correction in conditioning training for weightlifting(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2025-05-23) Peña Cortés, Dafne Vania; González Hernández, Hugo Gustavo; emimmayorquin; Izquierdo Reyes, Javier; School of Engineering and Sciences; Campus Ciudad de México; Cooperstock, Jeremy R.This study investigates the effectiveness of a vibrotactile feedback system in promoting proper wrist posture during bicep curling exercises. A total of 30 university students were divided into three groups depending on the correction method for their wrist angle: control (no feedback), experimental (vibrotactile feedback) and instructed (trainer feedback). The experimental protocol consisted of four sessions, with data collection occurring from the second to the fourth session. The primary metric was the proportion of time the wrist maintained the correct flexion-extension angle, which was individually tailored for each participant with the help of a trainer. The results showed significant interaction effects between feedback type and session number. The vibrotactile system demonstrated higher average percentages of wrist alignment compared to the control (23% more) and trainer (15% more) groups, possibly indicating learning effects. These findings are explained throughout the document and support the use of vibrotactile feedback as an effective tool to monitor and improve wrist posture, highlighting its potential in motor skills learning and haptics research.
- Effects of ASMR on critical thinking in engineering students: insights from EEG studies and chaotic descriptors(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2025-05) Galina Juárez, María Eugenia; González Hernández, Hugo Gustavo; emipsanchez; Izquierdo Reye, Javier; School of Engineering and Sciences; Campus Ciudad de México; Bustamante Bello, Martín RogelioThis research examines the influence of whispers in Autonomous Sensory Meridian Response (ASMR) videos over critical thinking in undergraduate engineering students. A quantitative method is employed, measuring students’ brainwaves with electroencephalography (EEG) while they watch a Problem-Based Learning (PBL) video featuring whispered narration. Chaotic descriptors, including Lyapunov exponent, fractal dimension, Hurst exponent, and approximate entropy, alongsidemachine learning techniques, are used to classify the EEG signals. The videos contain segments of relevant, irrelevant, and false information, which students are expected to distinguish. Two versions of the video are used: one with whispered narration (ASMR) for the experimental group and another with a normal speaking voice for the control group. It also proposes a new method to study the ASMR phenomenom and how it affects cognition and education, by perfectly defining the used stimuli, producing it and exposing the participants to it in a controlled environment and validating the stimuli by questioning the participants about it.
- Advanced path tracking: a study on autonomous vehicle control against different scenarios(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-12-03) Castillo Sánchez, Juan Pablo; González Hernández, Hugo Gustavo; emipsanchez; Moreno Moreno, Jesús; School of Engineering and Sciences; Campus Ciudad de México; Reyes Avendaño, Jorge AntonioAutonomous vehicles have been progressively deployed around the world, bringing numerous challenges remaining in hand due to their intrinsically complex nature. Among them, one of the most critical issues is motion control since it determines the performance of autonomous driving against a wide range of scenarios. This research evaluates the performance of different path tracking control strategies under specific driving conditions and trajectories, along with the exploration of localization algorithms, a fundamental step preceding the motion control stage. The proposed control techniques were simulated based on a single-track 2-DOF vehicle model and then validated through indoor physical tests on a Quanser scaled mobile platform called QCar.
- A transformer-based architecture proposal to drive a self-organizing UAV swarm communication network in emergency scenarios(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024) Medina Gómez, Kevin Javier; González Hernández, Hugo Gustavo; emimmayorquin; Oliart Ros, Alberto; Ramos, Azgard; School of Engineering and Sciences; Campus Monterrey; Izquierdo Reyes, JavierIn the aftermath of a natural disaster, telecommunication infrastructures' integrity could be compromised, leading to an unreliable communication service or even a complete blackout in the affected zone. This undesirable outcome increases victims' distress and panic levels. Quick response deployed systems to alleviate the crisis have the potential to save numerous people in danger. Therefore, this work proposes to deploy a multi-UAV swarm network for network coverage services to victims and rescue members, by connecting it with an infrastructure-based telecommunication system through an access point. This work was done in partial fulfillment of the requirements for the master's degree in Computer Science. This study explores solutions to handle UAV's partial observability constraints. Moreover, an encoder-decoder architecture known as Soft Transformer Recurrent Graph Networks (STRGN) was proposed from the insights of the transformer model, typically used for machine translation tasks, and a novel model called Soft Deep Recurrent Graph Networks (SDRGN). The proposal considers information from the agent's subgraph, including current neighbor and ground user positions, to determine the optimal actions to improve ground user coverage, fairness, and network connectivity. Extensive analysis of a variant of the proposed model, Soft Transformer Graph Networks (STGN), demonstrates its effectiveness in solving the Ground User Coverage Problem, outperforming the benchmarked state-of-the-art models. Additionally, we analyze the scalability of our proposed models for various environmental configurations.
- Autonomous vehicles navigation strategies enforcing safety with control barrier functions(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024) Rodriguez Ramirez, Jesús Orlando; González Hernández, Hugo Gustavo; emimmayorquin; Bustamante Bello, Martín Rogelio; School of Engineering and Sciences; Campus Ciudad de México; Avendaño Reyes, Jorge AntonioAutonomous vehicles have been a constant study area with many different areas to be exploited, one of them being regarding the navigation problem, and in this research we will be focused on certain technique that has been put into the spotlight recently, the proposed method will be tested both on a Matlab simulation and then on a physical platform known as Qcar developed by Quanser. The proposed solution to the safety problem while performing a navigation task was designed to drive our system, in this case an Ackerman steered vehicle through a predefined trajectory while avoiding an obstacle that is not on the original planning of the route, the design of this restriction has the inherent property of being already mathematically proved to enforce safety if designed correctly. The designed solution is to be tested with a simple pure pursuit control algorithm and once it is proven that can drive the system through the desired trajectory on simulation, it will be modified so it can be tested on the platform present on campus, given that the software that runs on it is closed and not open to modifications, it will require the implementation of Python libraries to run correctly, and given the nature of the platform a simplified version of the algorithm will be needed, this is further discussed on this document, video, code and experiments can be found on the results section of this document.
- Physical exertions recognition using surface electromyography and inertial measurements for occupational ergonomics(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2022-12-02) Concha Pérez, Elsa; GONZALEZ HERNANDEZ, HUGO GUSTAVO; 64806; González Hernández, Hugo Gustavo; puemcuervo; Gómez Sánchez, Miguel Angel; School of Engineering and Sciences; Campus Ciudad de México; Reyes Avendaño, Jorge AntonioAutomation of ergonomic risk level assessments using predictive models is limited to the recognition of certain activities with the intention of calculating some ergonomic risk factors, this means that the predictive models are only useful to recognize the activities that were taught. In this thesis, a framework was developed to automatically recognize the physical exertions done by an operator during a manual work task towards the automation of Job Strain Index (JSI) assessment. The framework includes the use of a wearable device that captures surface electromyography (sEMG) signals and inertial measurements called Mindrove armband, and provides the data treatments that maximized the training accuracy of a Cubic Support Vector Machine (CSVM) model, which was responsible for predicting the exertions depending on the behavior of the data. To determine the best data treatments, full factorial experiments were designed and analyses of variance (ANOVA) were performed. Thus, the best data treatments to obtain a maximum average training accuracy of 93.29% and testing accuracy of 94.31% of the CSVM were the filtering of raw signals with a 4th order Butterworth filter, the rectification of sEMG signals, the outliers' removal in data via Hampel identifier, the computation of the RMS envelope and normalization of sEMG, the zero calibration for inertial measurements, and the extraction of 126 statistical features. Additionally, the Visual Signal Analyzer App (SIANA) was developed for data processing, which works under the proposed framework. Automatic recognition of any physical exertion means that an automated JSI can be applied to any manual work task, thereby identifying more quickly the risk level of a work task in order to modify it to avoid occupational diseases and accidents.
- Glucose measurement via noninvasive methods(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2022-12-02) Huerta Ruiz, Samuel Natán; González Hernández, Hugo Gustavo; emipsanchez; Moreno Moreno, Jesús; School of Engineering and Sciences; Campus Ciudad de México; Oliart Ros, AlbertoNoninvasive glucose measurement methods are wide-ranging; they use several different technologies to try and get accurate results. Some try to measure glucose through lacerations on the skin and chemicals, others try to do it analyzing the color of the sclera, and others try to do it analyzing the sweat. For this thesis, a completely noninvasive and chemical free approach is used. Glucose levels are classified into three useful categories (low, medium, and high) trough the use of machine learning and descriptors from chaos theory to obtain a a satisfactory Support Vector Machine (SVM) model. Several classification models are compared by the following metrics: Area Under the Receiver (AUC), accuracy, precision, recall, and their combined information (F1). And lastly, a multipurpose system that uses principles from Internet of Things (IoT) is implemented to integrate a sampling device powered by Arduino with a web app, which in turn uses cloud computing to process data and store it in a remote server to effectively train machine learning models written in Python.
- Integrating natural language instruction with computer vision for collaborative robot programming(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2022-11-25) Agundis García, Lisandro Rodrigo; González Hernández, Hugo Gustavo; puemcuervo, emipsanchez; López Damián, Efraín; School of Engineering and Sciences; Campus Ciudad de México; Santana Díaz, AlfredoIndustry 4.0 is booming due to its multiple benefits ranging from optimizing resources, managing quality, and reducing manufacturing times. Different technologies are combined and implemented to give life to Industry 4.0. Recently the use of collaborative robots, also called cobots, has aroused great interest thanks to their versatility and low cost, bringing with it the automation of processes in a short time, weeks, or even days. However, the great potential that cobots can offer has not yet been exploited, mainly because the programming of cobots is still only for a select group of technical users and experts on the subject due to the complexity of task programming. The consequence of a gap in the development of a straightforward and robust user interface allows intuitive and clear programming, promoting collaborative development in an accessible way to non-technical users. Therefore, this proposal presents a prototype version of a voice user interface (VUI) for non-technical users to program and control collaborative robots. This implementation is planned to reduce the hardship of programming a collaborative robot and, through an experiment, measure the usability of the VUI and the reliability of natural language programming for collaborative robotics.
- Sensor fusion algorithms for autonomous vehicles(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2021-05-19) Osorio Sánchez, Diego; González Hernández, Hugo Gustavo; emipsanchez; Reyes Avendaño, Jorge Antonio; Bustamante Bello, Martin Rogelio; School of Engineering and Sciences; Campus Ciudad de MéxicoAutonomous vehicles are an emerging area with many problems without a definitive solution. One of these problems is the vehicle’s pose estimation which until these days still an open problem. In this research we will propose a sensor fusion strategy that estimates a vehicle’s position and orientation, this algorithm is used for the higher-level tasks of trajectory generation and path following. The VO algorithms that were tested during the research are ORB SLAM2, and the proper VO of the ZED camera by Stereolabs ®. The sensor fusion algorithms that were tested during the research are: Kalman filters, averaging measurements and Neural Networks. The main odometry algorithm was designed in order to function with a GPS, VO, IMU, steering sensor and a speed sensor. This algorithm is compatible with ROS in order to exchange data with sensor and other algorithms with nodes on the ROS network. This and the sub-algorithms that are executed in order to obtain a reliable and accurate pose estimation were tested separately in simulation and experiments and results are included in the results section. The proposed odometry algorithm is used by higher-level algorithms in order to make a simulated Unmanned Ground Vehicle locate itself and navigate to a desired final point, following a previously generated trajectory. Once algorithms were debugged and tested, their behaviour will be observed in an experimental environment using the real UGV designed by our research group in the Tecnologico de Monterrey Campus Puebla. Physical restrictions on the real UGV made the author modify the simulated algorithms in order to work in the real world. These modifications mainly appear in the navigation control law and its behaviour can be found in the Experimental results section. Furthermore links to videos where the behaviour of the UGV, its generated trajectory and some statistics, are included in the experimental results sections.