Avilés-Castillo, Fátima
Preferred name
Avilés-Castillo, Fátima
Main Affiliation
Ambato
Email
faviles@indoamerica.edu.ec
ORCID
0000-0002-0184-8893
Scopus Author ID
57845057800
23 results
Now showing 1 - 10 of 23
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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, Robotics in higher education and its impact on digital learningIn recent years, robotics has transformed various industrial processes but has also influenced teaching methodologies. Although there are literature reviews on its application in professional training, many are outdated or lack a current focus on its impact in higher education. Addressing this gap, the present mini review examines the impact, challenges, and opportunities of this technology in the university setting. To this end, a search was conducted in the PubMed, Scopus, IEEE Xplore, APA PsycNet, and Web of Science databases, selecting 11 studies that addressed diverse applications of robotics, including educational robotics, robotic telepresence, human-robot interaction, and artificial intelligence applications. Their effects on teaching, the factors influencing their adoption, and the strategies used to optimize their implementation were analyzed. The findings show that educational robotics enhances student motivation and engagement, with prediction models reaching an accuracy of 98.78% in assessing academic engagement. Additionally, robotic telepresence emerges as an effective alternative for hybrid education, and social robots and AI-based tutors demonstrated their potential to personalize learning. However, methodological and structural challenges persist, such as the need to develop more accurate evaluation metrics and ensure accessibility and educational equity. Future research should focus on improving these aspects, enabling more efficient integration to enhance teaching processes. This study was registered in the Open Science Framework under the code: 10.17605/OSF.IO/KHDTU.57 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Power Flow Optimization in Electrical Networks using Gekko(2025); ; Riba-Romeva, CarlesPower flow optimization in the electrical grid is critical to improve the stability and performance of power systems. The main challenge lies in finding an optimal distribution of power generation that meets the constraints imposed by the grid, such as voltage limits and power system stability conditions. The objective of this research was to evaluate the performance of Gekko in power flow optimization in electrical grids. To do so, a comparison was made with SciPy, a widely used benchmark framework in numerical optimization in order to assess their relative efficiency in problems with complex constraints. The comparison is based on metrics such as solution accuracy, convergence speed, and number of objective function evaluations. The results showed that both methods achieved the same objective value: SciPy (19.7) and Gekko (19.7). However, SciPy was slightly faster (0.01496 seconds vs. 0.0191 seconds), but required 60 objective function evaluations. In contrast, Gekko demonstrated greater computational efficiency, reducing the number of evaluations required for convergence. While SciPy is more efficient on small problems with explicit constraints, Gekko offers greater flexibility on problems with more complex constraints, making it more suitable for larger power systems.37 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Performance and Real-World Variability of Predictive Maintenance Models for Vehicle Fleets(2024); ; Elena Blanco-RomeroThis study presents a comprehensive evaluation of predictive maintenance models for vehicle fleets, detailing a sequence of systematic steps to ensure model performance and address real-world variability. The process begins with database creation and data preprocessing, where relevant maintenance records are filtered, and datetime columns are converted to facilitate time-based calculations. Grouping and aggregation techniques are then applied to count occurrences of specific maintenance activities and identify common failure types. For model training, we define a neural network architecture comprising dense and dropout layers to mitigate overfitting, compile the model with suitable loss functions and optimizers, and train it using the prepared data. The trained model, along with the scaler and encoder, is saved for future use. To augment the dataset, synthetic data is generated using the Faker library and random distributions, with added noise to mimic real-world variability. Preprocessing steps are reapplied to this synthetic data to ensure consistency. By implementing this neural network, we achieved a sensitivity of 0.93 and an ROC of 0.71. Following these detailed steps, we develop a robust predictive maintenance model that effectively identifies failures and non-failures, ultimately enhancing the reliability and efficiency of vehicle fleet management.27 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Innovative Learning Environments Through Social Media: Evaluation of Their Impact on Secondary Basic Education(2025); Education has evolved with the integration of information technologies, including the use of social media as innovative tools in educational technology. Although initially conceived for social interaction, platforms such as TikTok, WhatsApp, and Facebook have shown potential to enrich the learning environment and teaching-learning processes. In this context, a four-week didactic intervention was designed and implemented in seventh-year basic education students, focused on reinforcing knowledge in natural sciences through activities on social media. The methodology combined a quantitative and qualitative approach, with the application of surveys and pre- and post-intervention evaluations in three areas: electricity and energy, magnetism, atmosphere and climate. The results showed significant improvements in the categories of magnetism (Z = −3.918, p < 0.001) and atmosphere and climate (Z = −3.324, p = 0.001). However, no statistically significant difference was found in the category of electricity and energy (Z = −1.230, p = 0.219). This indicates that the intervention was more effective in certain areas, suggesting the need to adjust strategies for other topics. The effectiveness of using information technologies in education, particularly social media, to improve academic performance in specific areas is highlighted, proposing their potential as complementary teaching tools and the need to continue researching their application in various educational disciplines13 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Influence of continuous navigation modes on the immersive experience in a virtual supermarket(2026); ; 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Predictive Maintenance in Industrial Robotics Using Big Data: Techniques, Challenges, and Opportunities(2024); ; 14 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Defect Reduction in Textile Manufacturing: A Review(2025); The textile industry faces continuous challenges in reducing defects during manufacturing, as quality inconsistencies can lead to financial losses, reduced efficiency, and diminished consumer confidence. Addressing this issue requires a combination of methodological and technological approaches that optimize production while minimizing waste. This review examines various strategies for defect reduction, focusing on process improvement methodologies, predictive technologies, and sustainable practices. A systematic analysis of 12 studies highlights the effectiveness of structured quality management approaches in identifying and eliminating defect sources. Additionally, predictive models based on artificial intelligence have demonstrated significant potential in real-time defect detection and prevention, improving overall product quality. However, challenges such as machinery rigidity and the high variability of textile products complicate the implementation of these strategies. Sustainable manufacturing practices and specialized workforce training have also been identified as key factors in enhancing defect management, as they contribute to resource conservation, waste reduction, and improved working conditions. The findings suggest that a comprehensive approach, integrating advanced process optimization techniques, predictive analytics, and sustainable production methods, is essential for improving efficiency and quality in textile manufacturing. This integration not only reduces defects but also strengthens competitiveness in an industry increasingly driven by quality, sustainability, and technological innovation. The OSF registration can be accessed at: https://doi.org/10.17605/OSF.IO/NAMWY. © 2025 IEEE.14 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Analysis of Natural Lighting in Traditional Homes: Pilahuin Case Study(2024); 37 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Gamification in Inclusive Education for Children with Disabilities: Global Trends and Approaches - A Bibliometric Review(2023); ; ; Palacios-Navarro G.Given the growing attention to the intersection between technology and education, gamification has emerged as a strategy with great benefits. This bibliometric review addresses gamification’s current and future relevance in the educational field, focusing on its use as a pedagogical strategy to improve the learning and engagement of children with disabilities. Sixty-six studies published between 2001 and 2023 were analyzed, evaluating the most influential articles, main keywords, prominent authors, collaborating institutions, and funding sources. The literature suggests that gamification offers inclusive and personalized learning opportunities covering various disabilities. Methodologies and approaches to implement gamification were identified, including game elements, user-centered design techniques, and emerging technologies such as virtual reality, artificial intelligence, and educational robotics. However, challenges and areas for improvement were also found, such as the need for more long-term empirical evidence and the importance of considering individual differences and specific needs when designing gamification strategies. The review highlights the importance of strengthening collaborative networks between researchers and education professionals to disseminate best practices and promote more effective gamification approaches adapted to the needs of children with disabilities. Collaboration between educators, game developers, researchers, and parents are crucial to ensure that gamification efforts are inclusive and meet the diverse needs of students. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.Scopus© Citations 2 24
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