Buele, Jorge
Thumbnail Image
Preferred name
Buele, Jorge
Main Affiliation
Ambato
Email
jorgebuele@uti.edu.ec
ORCID
Scopus Author ID
57200380202

Research Output

Filters

56
Reset filters

Settings
Now showing 1 - 10 of 56
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

Telemetry and Video Surveillance System in a UAV for the Control and Monitoring of Long-Distance Missions

2020 , Buele, Jorge , Yánez-Arcos E. , Moscoso M.E. , Huilca J.S. , Jordán E.P. , Urrutia-Urrutia P. , Salazar F.W.

Unmanned aerial vehicles (UAVs) are multidisciplinary technological tools, which are used in the military area for surveillance, reconnaissance and intelligence tasks in conflict zones. Due to its versatility and performance, this manuscript describes the implementation of a telemetry and video surveillance system to develop long-range missions in a UAV prototype. Communications subsystems and a ground station are integrated, with which an unmanned aerial system (UAS) is formed, carrying out the necessary calibrations and configurations. After a set of tests and the necessary adjustments, a long-distance mission is carried out and its energy consumption, height reached and trajectory tracking are analyzed. In addition, the video signal level obtained and the percentage of telemetry signal in each of the tests are established, which managed to be 90% with a distance greater than 4 km. They have good benefits, with a low economic investment, representing an interesting proposal for developing countries with a limited budget for their improvement. © 2020, Springer Nature Switzerland AG.

View
No Thumbnail Available
Publication

Analysis of Musculoskeletal Disorders in University Administrative Staff: A Necessary Ergonomic Assessment

2024 , Cruz-Salazar R. , Buele, Jorge

Musculoskeletal disorders in work environments with repetitive tasks and long-period forced postures are common. A university’s administrative staff presented a high incidence of musculoskeletal disorders in the neck, lower back, shoulder, and wrist. Preventive measures should be taken to improve ergonomic conditions and minimize the risk of chronic injuries. The evaluation using the RULA method, and the Nordic Questionnaire revealed a medium to a high incidence of musculoskeletal discomfort in administrative staff. The position adopted by users strongly influences this situation, and it is recommended to follow ergonomic recommendations to minimize ergonomic risks. Forced postures in specific body areas, such as the neck, shoulder, and wrist, should be corrected with changes in the task and study, even redesigning them. The Nordic Questionnaire found that 100% of the participants feel neck, lower back, and elbow discomfort and 87.5% in the shoulder and hand/wrist. The discomfort lasts over three months, forcing 87.5% of people to change jobs. The intensity of the discomfort is moderate, and its origin has been mainly forced postures in the neck and lower back and repetitive movements in the hand/wrist. This shows the need to take preventive measures to improve ergonomic conditions and reduce the risk of injuries and chronic discomfort in employees. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

View
No Thumbnail Available
Publication

Facial recognition system for people with and without face mask in times of the covid-19 pandemic

2021 , Talahua J.S. , Buele, Jorge , Calvopina P. , Varela Aldas, José

In the face of the COVID-19 pandemic, the World Health Organization (WHO) declared the use of a face mask as a mandatory biosafety measure. This has caused problems in current facial recognition systems, motivating the development of this research. This manuscript describes the development of a system for recognizing people, even when they are using a face mask, from photographs. A classification model based on the MobileNetV2 architecture and the OpenCv's face detector is used. Thus, using these stages, it can be identified where the face is and it can be determined whether or not it is wearing a face mask. The FaceNet model is used as a feature extractor and a feedforward multilayer perceptron to perform facial recognition. For training the facial recognition models, a set of observations made up of 13,359 images is generated; 52.9% images with a face mask and 47.1% images without a face mask. The experimental results show that there is an accuracy of 99.65% in determining whether a person is wearing a mask or not. An accuracy of 99.52% is achieved in the facial recognition of 10 people with masks, while for facial recognition without masks, an accuracy of 99.96% is obtained. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

View
No Thumbnail Available
Publication

Predicting Academic Performance in Mathematics Using Machine Learning Algorithms

2022 , Espinosa Pinos, Carlos Alberto , Ayala-Chauvin, Manuel Ignacio , Buele, Jorge

Several 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.

View
No Thumbnail Available
Publication

Temperature Controller Using the Takagi-Sugeno-Kang Fuzzy Inference System for an Industrial Heat Treatment Furnace

2020 , Buele, Jorge , Ríos-Cando P. , Brito G. , Moreno-P R. , Salazar F.W.

The industrial welding industry has a high energy consumption due to the heating processes carried out. The heat treatment furnaces used for reheating equipment made of steel require a good regulator to control the temperature at each stage of the process, thereby optimizing resources. Considering dynamic and variable temperature behavior inside the oven, this paper proposes the design of a temperature controller based on a Takagi-Sugeno-Kang (TSK) fuzzy inference system of zero order. Considering the reaction curve of the temperature process, the plant model has been identified with the Miller method and a subsequent optimization based on the descending gradient algorithm. Using the conventional plant model, a TSK fuzzy model optimized by the recursive least square’s algorithm is obtained. The TSK fuzzy controller is initialized from the conventional controller and is optimized by descending gradient and a cost function. Applying this controller to a real heat treatment system achieves an approximate minimization of 15 min with respect to the time spent with a conventional controller. Improving the process and integrated systems of quality management of the service provided. © 2020, Springer Nature Switzerland AG.

View
No Thumbnail Available
Publication

Big Data as a Tool for Analyzing Academic Performance in Education

2024 , Ayala-Chauvin, Manuel Ignacio , Chucuri-Real B. , ESCUDERO VILLA, PEDRO FERNANDO , Buele, Jorge

Educational processes are constantly evolving and need upgrading according to the needs of the students. Every day an immense amount of data is generated that could be used to understand children’s behavior. This research proposes using three machine learning algorithms to evaluate academic performance. After debugging and organizing the information, the respective analysis is carried out. Data from eight academic cycles (2014–2021) of an elementary school are used to train the models. The algorithms used were Random Trees, Logistic Regression, and Support Vector Machines, with an accuracy of 93.48%, 96.86%, and 97.1%, respectively. This last algorithm was used to predict the grades of a new group of students, highlighting that most students will have acceptable grades and none with a grade lower than 7/10. Thus, it can be corroborated that the daily stored data of an elementary school is sufficient to predict the academic performance of its students using computational algorithms. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

View
No Thumbnail Available
Publication

Body Composition Evaluation using Bioelectrical Impedance and its Impact on Academic Performance of Nursing Students

2023 , Romero Riaño, Paola , Camaño Carball, Lilian , Yánez-Rueda H. , Buele, Jorge

In the past, nutritional assessment relied on manual measurements that did not allow for the differentiation of body composition components. With technological advancements, the introduction of bioelectrical impedance has provided a more specific approach to obtaining results. This study aims to utilize this innovative method to assess the connection between body composition and academic performance in nursing students. The research focused on a representative sample of 89 participants, utilizing bioelectrical impedance to measure the primary bioelements of the human body. Strong and significant correlations were observed between height and weight, height and muscle mass, and muscle mass and weight. A moderate correlation was found between weight and fat, as well as significant weak correlations between age and fat, and between fat and body mass index. Additionally, a significant weak negative correlation was observed between height and fat. Of the participants, 42.2% of women and 48% of men were classified as overweight. However, the statistical analysis did not reveal significant correlations between academic performance and variables such as weight, muscle mass, fat, and body mass index. Based on this information, it was concluded that most students had a body mass index within the normal range, and no direct relationship between body composition and academic performance was identified. Continuous monitoring of overweight students using this technology is recommended to promote healthy nutritional practices. © 2023 IEEE.

View
No Thumbnail Available
Publication

Virtual Reality applications based on activities of daily living (ADL) for cognitive diagnosis and rehabilitation

2022 , Buele, Jorge , Varela Aldas, José , Palacios-Navarro G.

Traditionally, screening tools are available to help diagnose a person's cognitive problem. Therefore, rehabilitation techniques are lab exercises that lack adequate ecological validity. In this paper, we propose to establish the projection of a methodology for the development of serious games based on activities of daily living (ADL). Both for real and immersive environments, to assess what provides better results when applied in healthy patients at first, but with a focus on those suffering from Alzheimer's disease. It is expected that when this research is completed, precedents will be established for the development of new proposals based on virtual environments. © 2022 IEEE.

View
No Thumbnail Available
Publication

Virtual reality applications based on instrumental activities of daily living (iADLs) for cognitive intervention in older adults: a systematic review

2023 , Buele, Jorge , Varela-Aldás J.L. , Palacios-Navarro G.

Background: In recent years, the use of virtual reality (VR) as a complementary intervention in treating cognitive impairment has significantly increased. VR applications based on instrumental activities of daily living (iADL-VR) could offer a promising approach with greater ecological validity for intervention in groups with cognitive impairments. However, the effectiveness of this approach is still debated. Objective: This systematic review aims to synthesize the effects of iADL-VR interventions to rehabilitate, train, or stimulate cognitive functions in healthy adults and people with mild cognitive impairment (MCI) and different types of dementia. Methods: A systematic search was performed in the Scopus, PubMed, IEEE Xplore, Web of Science, and APA PsycNet databases until September 2022 and repeated in April 2023. The selected studies met the search terms, were peer-reviewed, included an iADL-VR intervention, and were written in English. Descriptive, qualitative studies, reviews, cognitive assessment, non-intervention studies, those unrelated to VR or iADL, those focused on motor aspects, and non-degenerative disorders were excluded. The PEDro scale was used to assess the methodological quality of the controlled studies. To present and synthesize the results, we organized the extracted data into three tables, including PEDro scores, participant characteristics, and study characteristics. Results: Nineteen studies that met the inclusion and exclusion criteria were included. The total sample reached 590 participants, mostly women (72.67%). Approximately 30% were diagnosed with Alzheimer’s disease or dementia, and 20% had mild cognitive impairment. Variables such as authors and year of publication, study design, type of intervention and VR applied, duration of the intervention, main findings, and conclusions were extracted. Regarding demographic characteristics, the sample size, age, sex, years of education, neurological diagnosis, dropouts, and the city and country where the intervention took place were recorded. Almost all studies showed improvements in some or all the outcomes after the intervention, generally greater in the iADL-VR group than in the control group. Conclusion: iADL-VR interventions could be beneficial in improving the performance of cognitive functions in older adults and people with MCI and different types of dementia. The ecological component of these tasks makes them very suitable for transferring what has been learned to the real world. However, such transfer needs to be confirmed by further studies with larger and more homogeneous samples and longer follow-up periods. This review had no primary funding source and was registered with PROSPERO under registration ID: 375166. © 2023, The Author(s).

View