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Unveiling wearables: exploring the global landscape of biometric applications and vital signs and behavioral impact

2024 , Del-Valle-Soto, Carolina , Briseño, Ramon A. , Valdivia, Leonardo , Juan Arturo Nolazco-Flores

AbstractThe development of neuroscientific techniques enabling the recording of brain and peripheral nervous system activity has fueled research in cognitive science. Recent technological advancements offer new possibilities for inducing behavioral change, particularly through cost-effective Internet-based interventions. However, limitations in laboratory equipment volume have hindered the generalization of results to real-life contexts. The advent of Internet of Things (IoT) devices, such as wearables, equipped with sensors and microchips, has ushered in a new era in behavior change techniques. Wearables, including smartwatches, electronic tattoos, and more, are poised for massive adoption, with an expected annual growth rate of 55% over the next five years. These devices enable personalized instructions, leading to increased productivity and efficiency, particularly in industrial production. Additionally, the healthcare sector has seen a significant demand for wearables, with over 80% of global consumers willing to use them for health monitoring. This research explores the primary biometric applications of wearables and their impact on users’ well-being, focusing on the integration of behavior change techniques facilitated by IoT devices. Wearables have revolutionized health monitoring by providing real-time feedback, personalized interventions, and gamification. They encourage positive behavior changes by delivering immediate feedback, tailored recommendations, and gamified experiences, leading to sustained improvements in health. Furthermore, wearables seamlessly integrate with digital platforms, enhancing their impact through social support and connectivity. However, privacy and data security concerns must be addressed to maintain users’ trust. As technology continues to advance, the refinement of IoT devices’ design and functionality is crucial for promoting behavior change and improving health outcomes. This study aims to investigate the effects of behavior change techniques facilitated by wearables on individuals’ health outcomes and the role of wearables in promoting a healthier lifestyle.

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Affect-Driven VR Environment for Increasing Muscle Activity in Assisted Gait Rehabilitation

2024 , Rodríguez, Jafet , Del-Valle-Soto, Carolina , Gonzalez Sanchez, Javier

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Metaheuristic Algorithms Applied to the Inventory Problem

2021 , Erik Cuevas , Rodríguez Vázquez, Alma Nayeli , Alejo-Reyes, Avelina , Del-Valle-Soto, Carolina

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Usability evaluation of foot-based interfaces for blind travelers

2020 , Velázquez, Ramiro , Edwige Pissaloux , Del-Valle-Soto, Carolina , Aime Lay-Ekuakille , Bruno Ando

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Implications for Serious Game Design: Quantification of Cognitive Stimulation in Virtual Reality Puzzle Games through MSC and SpEn EEG Analysis

2024 , Gomez Romero Borquez, Jesus Alberto , Del-Valle-Soto, Carolina , Del-Puerto-Flores, J. Alberto , Castillo-Soria, Francisco R. , Maciel-Barboza F.M.

This paper investigates the cognitive stimulation experienced by players engaging in virtual reality (VR) puzzle games through the analysis of electroencephalography (EEG) data. The study employs magnitude-square coherence (MSC) and spectral entropy (SpEn) metrics to quantify neural activity patterns associated with problem-solving processes during gameplay. Results reveal unique coherence and entropy profiles across different VR gaming tasks, with Tetris gameplay eliciting heightened coherence and entropy values compared to other games. Specifically, Tetris demonstrates increased coherence between frontal and temporal brain regions, indicative of enhanced visuospatial processing and decision making. These findings underscore the importance of considering both spectral coherence and entropy when assessing the cognitive effects of video game tasks on brain activity. Insights from this study may inform the design of serious VR games aimed at promoting cognitive development and problem-solving skills in players.

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Uncovering the Limitations and Insights of Packet Status Prediction Models in IEEE 802.15.4-Based Wireless Networks and Insights from Data Science

2024 , Arce Rodríguez, Mariana , Pérez-Díaz, Heráclito , Del-Valle-Soto, Carolina , Ramon A. Briseño

Wireless networks play a pivotal role in various domains, including industrial automation, autonomous vehicles, robotics, and mobile sensor networks. This research investigates the critical issue of packet loss in modern wireless networks and aims to identify the conditions within a network’s environment that lead to such losses. We propose a packet status prediction model for data packets that travel through a wireless network based on the IEEE 802.15.4 standard and are exposed to five different types of interference in a controlled experimentation environment. The proposed model focuses on the packetization process and its impact on network robustness. This study explores the challenges posed by packet loss, particularly in the context of interference, and puts forth the hypothesis that specific environmental conditions are linked to packet loss occurrences. The contribution of this work lies in advancing our understanding of the conditions leading to packet loss in wireless networks. Data are retrieved with a single CC2531 USB Dongle Packet Sniffer, whose pieces of information on packets become the features of each packet from which the classifier model will gather the training data with the aim of predicting whether a packet will unsuccessfully arrive at its destination. We found that interference causes more packet loss than that caused by various devices using a WiFi communication protocol simultaneously. In addition, we found that the most important predictors are network strength and packet size; low network strength tends to lead to more packet loss, especially for larger packets. This study contributes to the ongoing efforts to predict and mitigate packet loss, emphasizing the need for adaptive models in dynamic wireless environments.

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Comparison of Collaborative and Cooperative Schemes in Sensor Networks for Non-Invasive Monitoring of People at Home

2023 , Del-Valle-Soto, Carolina , Valdivia, Leonardo , López-Pimentel, Juan Carlos , Paolo Visconti

This paper looks at wireless sensor networks (WSNs) in healthcare, where they can monitor patients remotely. WSNs are considered one of the most promising technologies due to their flexibility and autonomy in communication. However, routing protocols in WSNs must be energy-efficient, with a minimal quality of service, so as not to compromise patient care. The main objective of this work is to compare two work schemes in the routing protocol algorithm in WSNs (cooperative and collaborative) in a home environment for monitoring the conditions of the elderly. The study aims to optimize the performance of the algorithm and the ease of use for people while analyzing the impact of the sensor network on the analysis of vital signs daily using medical equipment. We found relationships between vital sign metrics that have a more significant impact in the presence of a monitoring system. Finally, we conduct a performance analysis of both schemes proposed for the home tracking application and study their usability from the user’s point of view.

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Mapping EEG Alpha Activity: Assessing Concentration Levels during Player Experience in Virtual Reality Video Games

2023 , Gomez Romero Borquez, Jesus Alberto , Del-Puerto-Flores, J. Alberto , Del-Valle-Soto, Carolina

This work presents a study in which the cognitive concentration levels of participants were evaluated using electroencephalogram (EEG) measures while they were playing three different categories of virtual reality (VR) video games: Challenging Puzzlers, Casual Games, and Exergames. Thirty-one voluntary participants between the ages of 17 and 35 were recruited. EEG data were processed to analyze the brain’s electrical activity in the alpha band. The values of power spectral density (PSD) and individual alpha frequency (IAF) of each participant were compared to detect changes that could indicate a state of concentration. Additionally, frontal alpha asymmetry (FAA) between the left and right hemispheres of the brain was compared. The results showed that the Exergame category of video games elicited higher average cognitive concentration in players, as indicated by the IAF and FAA values. These findings contribute to understanding the cognitive effects of VR video games and their implications for designing and developing VR experiences to enhance cognitive abilities.

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Energy Recycling Laboratory Experimental Test Bench for Three-Phase FACTS Devices Prototypes

2019 , Jesus E. Valdez-Resendiz , Mayo Maldonado, Jonathan , Rosas-caro, Julio , Alejo-Reyes, Avelina , Armando Llamas-Terres , Valderrabano-Gonzalez, Antonio , Del-Valle-Soto, Carolina , Valdivia, Leonardo

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Energy-efficiency Model for a Smart Building: A Real Application

2020 , Del-Valle-Soto, Carolina , Velázquez, Ramiro , Claudia L. Garzon-Castro , Valdivia, Leonardo