Avilés-Castillo, Fátima
Thumbnail Image
Preferred name
Avilés-Castillo, Fátima
Main Affiliation
Ambato
Email
faviles@indoamerica.edu.ec
ORCID
Scopus Author ID
57845057800

Research Output

Filters

22
Reset filters

Settings
Now showing 1 - 10 of 22
No Thumbnail Available
Publication

Effects of a dual intervention (motor and virtual reality-based cognitive) on cognition in patients with mild cognitive impairment: a single-blind, randomized controlled trial

2024 , Buele, Jorge , Avilés-Castillo, Fátima , Carolina Del-Valle-Soto , Varela Aldas, José , Guillermo Palacios-Navarro

Abstract Background The increase in cases of mild cognitive impairment (MCI) underlines the urgency of finding effective methods to slow its progression. Given the limited effectiveness of current pharmacological options to prevent or treat the early stages of this deterioration, non-pharmacological alternatives are especially relevant. Objective To assess the effectiveness of a cognitive-motor intervention based on immersive virtual reality (VR) that simulates an activity of daily living (ADL) on cognitive functions and its impact on depression and the ability to perform such activities in patients with MCI. Methods Thirty-four older adults (men, women) with MCI were randomized to the experimental group (n = 17; 75.41 ± 5.76) or control (n = 17; 77.35 ± 6.75) group. Both groups received motor training, through aerobic, balance and resistance activities in group. Subsequently, the experimental group received cognitive training based on VR, while the control group received traditional cognitive training. Cognitive functions, depression, and the ability to perform activities of daily living (ADLs) were assessed using the Spanish versions of the Montreal Cognitive Assessment (MoCA-S), the Short Geriatric Depression Scale (SGDS-S), and the of Instrumental Activities of Daily Living (IADL-S) before and after 6-week intervention (a total of twelve 40-minutes sessions). Results Between groups comparison did not reveal significant differences in either cognitive function or geriatric depression. The intragroup effect of cognitive function and geriatric depression was significant in both groups (p < 0.001), with large effect sizes. There was no statistically significant improvement in any of the groups when evaluating their performance in ADLs (control, p = 0.28; experimental, p = 0.46) as expected. The completion rate in the experimental group was higher (82.35%) compared to the control group (70.59%). Likewise, participants in the experimental group reached a higher level of difficulty in the application and needed less time to complete the task at each level. Conclusions The application of a dual intervention, through motor training prior to a cognitive task based on Immersive VR was shown to be a beneficial non-pharmacological strategy to improve cognitive functions and reduce depression in patients with MCI. Similarly, the control group benefited from such dual intervention with statistically significant improvements. Trial registration ClinicalTrials.gov NCT06313931; https://clinicaltrials.gov/study/NCT06313931.

View
No Thumbnail Available
Publication

Gamification in Inclusive Education for Children with Disabilities: Global Trends and Approaches - A Bibliometric Review

2023 , Jadán Guerrero, Janio , Avilés-Castillo, Fátima , Buele, Jorge , 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.

View
No Thumbnail Available
Publication

Defect Reduction in Textile Manufacturing: A Review

2025 , Ángeles Solís-Solís , Sebastián Villacís-Capuz , Marco Centeno-Alarcón , Avilés-Castillo, Fátima , Buele, Jorge

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.

View
No Thumbnail Available
Publication

Robotics in higher education and its impact on digital learning

2025 , Zamora Lascano, Patrick , Lozada, Alan , Buele, Jorge , Avilés-Castillo, Fátima

In 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.

View
No Thumbnail Available
Publication

Digital Animation, Health Education in Post COVID-19 Scenario

2024 , Oleas, J , Aguayza-Mendieta C. , Avilés-Castillo, Fátima , Sanchez D.

In post pandemics scenario, viral respiratory diseases are show up very often in changeable and usually cold weather locations. Ecuadorian cities in Andean region have altitude and unpredictable climate characteristics where respiratory diseases are frequent. COVID-19, influenza, flu and other infections are still present in the environment This research shows a development and application of digital animation, showing the audiovisual production processes developed through digital tools, products in educational contexts, adapted to the global health situation post pandemics. The study shows a mixed-type research divided into two phases. The first stage, for information collection, determined the needs for learning topics that collaborates in COVID-19 prevention in elementary education population through digital cartoons as a tool using social media as broadcast medium. The second stage, the animated product evaluation, inside an application scenario, in elementary schools in Riobamba city, that was exhibited through social networks. Through qualitative and quantitative research approaches, it has been possible to demonstrate the animation (digital cartoons) relevance in educational areas. Likewise, the study shows teachers and parents positive predisposition of digital animation use, as a learning tool and its use for educational content transmission, which is something new in the Ecuadorian school scene. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

View
No Thumbnail Available
Publication

Ethical and Social Challenges in Virtual Reality: A Bibliometric Analysis

2024 , Buele, Jorge , Homero J. Velastegui , Avilés-Castillo, Fátima , Hugo Paz-León , Guillermo Palacios-Navarro

Virtual reality has revolutionized human interaction with digital environments, creating immersive simulations that have significantly impacted sectors such as education, urban planning, and mental health. Along with its transformative potential, VR presents ethical and societal challenges. This study analyzes trends in research addressing these challenges, focusing on articles published through 2023 in the Web of Science database. Visual and statistical analyses reveal a sustained increase in publications since 2013. Patterns in authorship and collaboration networks emphasize the global and interdisciplinary nature of VR research. Dominant themes include the metaverse and therapeutic applications, as well as concerns about data privacy, virtual identity representation, and psychological effects such as cybersickness. Research highlights temporary symptoms such as nausea and eye strain associated with immersive systems, demonstrating the need for ergonomic design and age-specific usage guidelines. Furthermore, active video games using VR have shown promise in promoting physical activity, offering innovative solutions to combat sedentary lifestyles. Looking ahead, efforts must prioritize equitable access, user safety, and robust ethical frameworks to ensure the responsible and sustainable integration of VR technologies.

View
No Thumbnail Available
Publication

Towards Smart Agriculture: An Overview of Big Data in the Agricultural Industry

2025 , Ayala-Chauvin, Manuel Ignacio , Avilés-Castillo, Fátima

Agriculture is currently undergoing progressive diversification and expansion, as demonstrated by the wide range of research topics and methodologies being employed. The growing need for technology to enhance agricultural processes is increasingly evident and prominently highlighted in recent studies. To assess the influence of Big Data on agriculture and its potential to advance Smart Agriculture, this bibliometric study was conducted. The research consolidates bibliometric data from the Scopus database, using the Bibliometrix package to identify trends in this field. The findings show a growing annual publication rate, indicating increasing interest in the integration of data analysis methodologies within agriculture. The collaborative nature of the research, combined with a high citation rate per document and diversity of key terms, underscores the importance of this field and its potential contribution to achieving Smart Agriculture. The convergence of Big Data, the Internet of Things, and agriculture is particularly noteworthy, as these technologies are improving decision-making and efficiency in the agricultural sector. Despite certain limitations, this study highlights the transformative potential of these advancements and suggests areas for future research, thus laying the groundwork for a more sustainable, productive, and intelligent agricultural future.

View
No Thumbnail Available
Publication

Predictive Maintenance in Industrial Robotics Using Big Data: Techniques, Challenges, and Opportunities

2024 , Ayala-Chauvin, Manuel Ignacio , Avilés-Castillo, Fátima , Dayanara Yánez-Arcos , Buele, Jorge

In industrial robotics, predictive maintenance is important to improve efficiency and reduce costs, addressing early detection and diagnosis of failures. The use of Big Data allows us to identify patterns and trends that at first glance are complex. This review examines research on the application of big data in predictive maintenance of industrial robots, which use advanced techniques such as cloud-based architectures, filtering algorithms, and machine learning. The review methodology included an analysis of the big data techniques used, the challenges identified, and the opportunities presented. The results show significant improvements in the accuracy of predictions and fault diagnoses. Key anomaly drivers were identified that improved production performance and enabled accurate fault identification and reduced downtime in industrial robots. Despite the benefits, challenges remain in data security and communications latency, underscoring the need to develop innovative algorithms and techniques to balance computing load and minimize delays. The continuous evolution of these techniques promises to improve the failure management capacity in industrial robotics, thus optimizing the operability and efficiency of robotic systems.

View
No Thumbnail Available
Publication

Optimizing Natural Language Processing: A Comparative Analysis of GPT-3.5, GPT-4, and GPT-4o

2024 , Ayala-Chauvin, Manuel Ignacio , Avilés-Castillo, Fátima

In the last decade, the advancement of artificial intelligence has transformed multiple sectors, with natural language processing standing out as one of the most dynamic and promising areas. This study focused on comparing the GPT-3.5, GPT-4 and GPT-4o language models, evaluating their efficiency and performance in Natural Language Processing tasks such as text generation, machine translation and sentiment analysis. Using a controlled experimental design, the response speed and quality of the outputs generated by each model were measured. The results showed that GPT-4o significantly outperforms GPT-4 in terms of speed, completing tasks 25% faster in text generation and 20% faster in translation. In sentiment analysis, GPT-4o was 30% faster than GPT-4. Additionally, analysis of response quality, assessed using human reviews, showed that while GPT-3.5 delivers fast and consistent responses, GPT-4 and GPT-4o produce higher quality and more de-tailed content. The findings suggest that GPT-4o is ideal for applications that require speed and consistency, while GPT-4, although slower, might be preferred in contexts where text accuracy and quality are important. This study highlights the need to balance efficiency and quality in the selection of language models and suggests implementing additional automatic evaluations in future research to complement the current findings.

View
No Thumbnail Available
Publication

Virtual Reality and User Experience: Current Trends and Future Challenges

2025 , Avilés-Castillo, Fátima , Buele, Jorge , Guillermo Palacios-Navarro

Virtual reality is an emerging and versatile technology that is gaining increasing interest from the scientific community, particularly regarding user experience. A review of the literature highlights the need for updated analyses that comprehensively address current trends in this field. The objective of this study is to analyze the evolution of scientific publications related to virtual reality and user experience, identifying trends, the most influential authors, relevant journals, and international collaborations, to provide a comprehensive overview. A bibliometric analysis was conducted using the Web of Science Core Collection database, identifying a total of 1,848 relevant publications. Network analysis techniques and Bradford’s law were applied, allowing for the examination of the distribution and impact of publications, as well as collaboration between authors and institutions. The results show an exponential growth in scientific output, particularly since 2019. While the United States leads in the number of publications, most of the influential authors are from Europe, with notable scientific output in Spain and Portugal. Current research hotspots include virtual reality applications in education and healthcare (over 70% of the analyzed publications), which align with Sustainable Development Goals, particularly 3 and 4. Trends indicate a shift towards integrating virtual reality with artificial intelligence, adaptive systems, and multisensory interaction to enhance immersion and usability. Challenges include a lack of standardized methodologies to assess immersion, presence, and cognitive load, which limits comparisons across studies and hinders the development of best practices. Future research should focus on refining interaction paradigms, improving accessibility, and developing ethical frameworks that respect data privacy and protect the user from cybersickness and the psychological effects of prolonged virtual reality exposure.

View