Facultad de Ingenierías
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Item type:Publication, User Experience in Virtual Reality (VR) Applications for Elderly People with Cognitive Impairment and Dementia: A Scoping Review(2024); ; Guillermo Palacios-NavarroBackground: In recent years, Virtual Reality (VR) has emerged as a promising tool to improve the well-being and functional capabilities of older adults. Although VR applications have shown positive results, their impact on user experience and therapeutic outcomes still needs to be evaluated. Objective: This scoping review aims to analyze existing studies on VR use in older adults with neurodegenerative disorders, focusing on the factors that influence usability, satisfaction, and immersion, as well as the effects on emotional and cognitive well-being. Materials and Methods: Empirical studies in English were included on VR applications applied to older adults with cognitive impairment without study design restrictions. The search was conducted in IEEE Xplore, PubMed, Scopus, and Web of Science, identifying a total of 650 initial results. After screening, 14 studies met the inclusion criteria. Results: Immersive VR tends to generate a greater sense of presence, which contributes to improving emotional well-being and reducing neuropsychiatric symptoms, such as apathy and depression. However, its impact on cognitive functions, including memory and executive skills, varied depending on the level of immersion and participant characteristics. Despite these positive findings, significant heterogeneity was evident in study designs, measurement instruments, and user experience indicators. Conclusion: Virtual environments have great potential as a therapeutic tool for older adults, but their success depends on the personalization of applications and the adaptation of technology to the specific needs of this population. Future research should focus on developing standardized protocols, incorporating adaptive technologies such as artificial intelligence, and evaluating the long-term effects of VR to maximize its benefits and minimize its risks. This review was registered in Open Science Framework (OSF). Registration Number: 10.17605/OSF.IO/PNU3635 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Interfaces and Usability in Digital Flight Logs: Applied Design in the Aeronautical Context(2026)In Ecuador, the management of flight logs is still predominantly conducted in physical format, representing a significant barrier to operational efficiency and aviation safety. This situation highlights an important gap in the availability of digital solutions specifically designed for the local context and validated with real users. This study seeks to address that gap by designing and validating a user interface focused on user experience (UX) principles, aimed at optimizing the flight logging process and improving information quality. The research adopts a qualitative approach with elements of applied research, structured into four phases: requirements gathering through semi-structured interviews, iterative prototyping using Figma, usability testing with the “think aloud” technique, and heuristic evaluation by UX experts. The sample was intentionally selected and included 12 Ecuadorian civilian pilots (6 in training and 6 professionals), all with experience in using physical logbooks and basic familiarity with digital devices. The results show substantial improvements in process efficiency: a 40% reduction in average data entry time, an average of only 1.2 errors per session, and an average System Usability Scale (SUS) score of 89 out of 100, classified as “excellent usability”. 91% of participants expressed high satisfaction with the developed interface, highlighting its intuitive navigation, visual clarity, and offline usability—an essential factor in contexts with limited connectivity. These findings confirm that applying user-centered design principles can produce highly effective and well-accepted digital solutions, even in technical and regulated sectors such as aviation. The study lays the groundwork for future institutional implementations, emphasizing the importance of integrating co-creation processes with end users and planning progressive training and adoption strategies to ensure successful and sustainable technological change. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.4 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, U-Net Models for Breast Cancer Detection: Improving Diagnostic Accuracy and Specificity(2024); Elena Blanco-RomeroBreast cancer remains a critical global health issue, necessitating continuous research and innovative approaches for diagnosis, treatment, and prevention. This study evaluates the effectiveness of U -Net models in enhancing diagnostic precision and efficiency using real hospital samples. We aim to improve key diagnostic metrics such as accuracy, sensitivity, and specificity through the application of U-Net models. Our image classification model, tailored for 256 × 256 × 3 input images, excels in detecting and categorizing tumor cells. The architecture begins with initial convolutional layers featuring 64 filters, progresses to layers with 128 filters, and includes a Dropout layer to prevent overfitting. The deep network for object detection utilizes both region proposal and regression/classification approaches, achieving 92.27% confidence and 100% accuracy. Additionally, our deep learning algorithms accurately segment nuclei in histopathological images, employing a clustering strategy that delivers 88.81% confidence and 100% accuracy. Visual results demonstrate precise tumor cell localization and prediction confidence. Performance metrics from ten experimental runs indicate average confidence levels between 74.19% and 92.31%, with 90.0% accuracy and specificity in benign analysis. The model's ability to classify non-carcinomas versus carcinomas achieved an AUC of 0.78, illustrating its effective differentiation between classes.10 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Design of a load elevator as a measure to reduce ergonomic risks(2024); ; ; 21 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Predicting Academic Performance in Mathematics Using Machine Learning AlgorithmsSeveral factors, directly and indirectly, influence students’ performance in their various activities. Children and adolescents in the education process generate enormous data that could be analyzed to promote changes in current educational models. Therefore, this study proposes using machine learning algorithms to evaluate the variables influencing mathematics achievement. Three models were developed to identify behavioral patterns such as passing or failing achievement. On the one hand, numerical variables such as grades in exams of other subjects or entrance to higher education and categorical variables such as institution financing, student’s ethnicity, and gender, among others, are analyzed. The methodology applied was based on CRISP-DM, starting with the debugging of the database with the support of the Python library, Sklearn. The algorithms used are Decision Tree (DT), Naive Bayes (NB), and Random Forest (RF), the last one being the best, with 92% accuracy, 98% recall, and 97% recovery. As mentioned above, the attributes that best contribute to the model are the entrance exam score for higher education, grade exam, and achievement scores in linguistic, scientific, and social studies domains. This confirms the existence of data that help to develop models that can be used to improve curricula and regional education regulations. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.39 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Design of a Semi-automatic Dough Mixer for the Prevention of Occupational Diseases in Marzipan ArtisansOlder people, due to the natural aging process, are particularly vulnerable to occupational tasks, as they experience a gradual loss of physical capacities, which increases the incidence of occupational diseases in this population. Despite these challenges, their experience and skills acquired over the years make them a valuable resource for society. This study focuses on designing a semi-automatic dough sheeter for the dough making process used by the artisans of Calderón in Ecuador, who currently carry out this work manually, this practice being an integral part of the local culture. The research began with a detailed analysis of modern manual molders, collecting data on shear force, bending moment, and tensile stress, which are fundamental to the design. Subsequently, a simulation of the design was carried out using SolidWorks software. The result was the creation of a prototype kneading machine equipped with AISI 1050 steel rollers, processed by HR. This device was able to significantly reduce repetitive hand movements, reducing the effort during the kneading process by 25,000 TMU, which translates into improved health and work performance for the artisans. The implementation of this technology reduced the risk of occupational diseases such as bursitis, which is caused by inflammation of the bursae in the joints, and carpal tunnel syndrome, which affects the functionality of the hands. In addition to the physical benefits, this project also addresses the psychological aspect, as many older craftsmen and women feel demotivated due to their diminished ability to perform tasks they used to do in their youth. The research aims to provide a better quality of life for these workers, protecting both their physical health and emotional well-being. In short, the semi-automatic laminator not only improves the working conditions of the Calderon artisans but also preserves and promotes an important cultural tradition, ensuring that these valuable knowledge and skills can continue to be practiced in a safe and sustainable manner.11 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Audio-tactile rendering: A review on technology and methods to convey musical information through the sense of touch(2021)Scopus© Citations 26 41 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, VPD Monitoring with ESP32 and Flask API for Early Detection of Powdery Mildew in Rose Greenhouses(2026)Herrera, Vicente-D.In this study, a vapor pressure deficit (VPD) monitoring system was developed using an ESP32 and a Flask-based API for the early detection of powdery mildew in rose greenhouses. The research demonstrated that the integration of intelligent systems and real-time analysis of environmental conditions allows for the rapid identification of factors that favor the development of powdery mildew. The SVM model employed achieved high accuracy, with a classification accuracy rate of 96% in identifying conditions conducive to this disease, which is crucial for reducing unnecessary interventions and optimizing resource management in greenhouses. Additionally, the use of an API facilitates the integration of the system with other management platforms, enhancing data accessibility and decision-making. This approach promotes more responsible agricultural practices aligned with environmental sustainability. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Maneuvers Under Estimation of Human Postures for Autonomous Navigation of Robot KUKA YouBot(2021)14 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Energy Transition in Industry as a Viable Path to Sustainable Decarbonization(2025)15