Conference Agenda

The present research aimed to determine the relationship between Emotional Intelligence and Aggressive Behaviors in fourth-year high school students from an educational institution in Pacasmayo, 2024. This study was characterized as applied research with a quantitative nature, adopting a non-experimental design with a descriptive-correlational scope, contributing to the Sustainable Development Goal (SDG) 4 of the 2030 United Nations Agenda: Quality Education, promoting emotional well-being, and reducing school violence. The sample consisted of 67 students, and data was collected through validated questionnaires on Emotional Intelligence and Aggressive Behaviors, demonstrating high reliability according to Cronbach’s Alpha coefficient. The results revealed that 85% of the students exhibited low levels of Emotional Intelligence, with the intrapersonal dimension and stress management being the most affected. Regarding Aggressive Behaviors, 87% showed medium levels, with hostility and anger being predominant. In conclusion, the research revealed a weak but significant negative correlation, indicating that as Emotional Intelligence levels increase, aggressive behaviors decrease. This highlights that developing emotional skills in adolescents can contribute to reducing aggressive behaviors in the school environment

Measuring adherence to medical treatment in diabetic patients can be a costly and time-consuming process, with commonly used methods including pill counts, self-report questionnaires, and daily reminder phone calls. Based on this, we propose a mobile system that utilizes a supervised predictive Machine Learning algorithm. This system reduces the analysis period while identifying the probability of non-compliance with medical treatment. Furthermore, it permits physicians to monitor and control their patients conveniently and intuitively. Our proposal underwent validation with diabetes care and prevention experts, as well as patients. The study findings indicated that 72% of adult diabetes patients were able to enhance their adherence to prescribed treatments through utilizing the mobile application.

Cardiovascular diseases pose significant health challenges in low- and middle-income countries (LMICs), making early detection of heart disease vital to improve outcomes, but access to conventional diagnostic tools. Mobile electrocardiography (MECG) offers a promising solution for remote and resource-limited settings. To evaluate the use of MECG technology to detect cardiac disease in underserved areas of Honduras. It focuses on mobile health technologies' efficacy, challenges, and potential to expand access to cardiovascular diagnosis. MECG devices were deployed in the El Paraíso, Honduras, using Prince 180D devices and a cloud-based mobile application to record and transmit ECG data. A total of 1044 ECGs were collected between November 2023 and January 2024, and the data were analyzed remotely by cardiologists. Among the 1044 ECGs recorded, 262 had abnormalities, such as ischemic heart disease, atrial fibrillation, atrial flutter, and third-degree atrioventricular block. MECG technology demonstrated sensitivity to various cardiac pathologies, and abnormalities were predominantly identified in women and patients aged 41 years or older. MECG technology demonstrated high accuracy and reliability in detecting multiple cardiac pathologies, especially in geographically isolated regions. This system enabled early diagnosis and facilitated timely referrals, offering a scalable solution to health disparities in LMICs.

This study examines the health risks associated with bisphenol A (BPA), a widely used endocrine disruptor found in plastics, particularly its impact on pregnant women and children up to six years of age. The primary objective is to assess the presence of BPA in vulnerable populations and analyze regulatory frameworks from other countries to inform potential policy applications in Peru. A systematic review was conducted using databases such as ScienceDirect, Web of Science, and Nature, alongside legislative documents on Good Agricultural Practices (GAP). The PRISMA method was applied, utilizing keywords including "BPA," "pregnant women," "health," "children," and "regulation." The findings indicate that BPA exposure poses significant health risks, including neurological and metabolic disorders, as identified through urinalysis in pregnant women and young children. Additionally, regulatory measures in countries such as Canada, Brazil, and Spain have effectively reduced BPA exposure, particularly in products like baby bottles. Furthermore, considering plastic resin codes can help identify BPA-free packaging. These results highlight the lack of awareness and research on BPA exposure in Peru, as well as the absence of national studies demonstrating its health impacts on vulnerable groups. Therefore, further research is recommended to support the development and enforcement of BPA-related regulations in Peru.

This paper addresses the evaluation of specific ergonomic methods to prevent Musculoskeletal Disorders (MSDs) in industrial workers. MSDs represent one of the most prevalent conditions globally, particularly in industrial settings where employees are subject to high risks of injury. Ergonomics is fundamental in identifying and correcting high-risk work postures and improving workers' health and work performance. The main purpose of this comprehensive literature review is to examine which ergonomic methods, such as RULA, REBA, and OCRA, are most effective in the industrial setting. These methods are crucial to perform detailed ergonomic risk assessments, allowing accurate identification of problems and implementation of effective solutions. Next, the methods used for the review are described: PICO and PRISMA for selecting and analyzing relevant articles, of which 48 met the inclusion criteria. The findings found in the analysis are presented in section four, followed by a discussion of the findings and their practical implications. Finally, conclusions and recommendations for future research in the industrial ergonomics setting are offered. The implementation of ergonomic methods not only reduces the direct and indirect costs associated with MSDs but also improves employee performance and well-being. This study highlights the relevance of further research and implementation of ergonomic practices in the industrial sector to reduce risks and promote a healthier and safer work environment.

This study presents the development of a low-cost system for real-time monitoring and processing of electromyographic (EMG) signals to study the impact of mechanical vibrations on drill operators, which are known to lead to musculoskeletal disorders and reduced work efficiency. The proposed system comprises an EMG acquisition unit, a vibration generator, and signal processing algorithms to ensure noise reduction and robust data analysis. Signal processing techniques, including notch filtering and Empirical Mode Decomposition (EMD), were employed to ensure high-fidelity signal analysis. Preliminary testing in controlled environments demonstrated the system’s ability to identify changes in muscle activity corresponding to varying vibration intensities. This was achieved using a drill, not the vibration generator. Observed results indicate the system can detect real-time vibration exposure and its intensity. A third-party Motor Unit Action Potential (MUAP) estimation algorithm was implemented, which could allow the preventive detection of musculoskeletal disorders. The proposed system holds potential for broader ergonomics, rehabilitation, and sports science applications. By offering a portable, cost-effective solution, it addresses a critical gap in real-time monitoring technologies. Future directions include enhancing the algorithm’s sensitivity, expanding validation studies to real-time settings, and exploring machine learning applications for more nuanced data analysis.