2025
Autores
Caetano, E; MPM Oliveira, B; Correia, F; Torres, D; Poínhos, R;
Publicação
Acta Portuguesa de Nutrição
Abstract
2025
Autores
Cerqueira, F; Ferreira, MC; Campos, MJ; Fernandes, CS;
Publicação
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
Abstract
Background: The study aims to present and explain the development stages of a mobile app designed to improve health literacy for self-management of oncological diseases. Through the integration of gamification, the app aims to enhance patient engagement and education in an interactive manner. Methods: The methodology of Design Science in Information Systems and Software Engineering was employed, which included stages of needs identification, requirements definition, prototyping, and iterative validation of the developed artifact. A total of 132 participants, consisting of patients and healthcare professionals, were involved in the development of the PocketOnco application. The subsequent implementation of the App, PocketOnco, involved usability testing, System Usability Scale assessment, and the collection of qualitative feedback. Results: The usability testing analysis revealed excellent acceptance of PocketOnco, with the gamified elements such as quizzes and reward systems being particularly appreciated for their ability to consistently engage and motivate users. Conclusion: The various stages in the development of this resource ensure the quality of its purpose. The application proved to be a viable and attractive solution for both patients and healthcare professionals, suggesting a promising path for future digital interventions in the field of oncology.
2025
Autores
Nascimento, R; Ferreira, T; Rocha, CD; Filipe, V; Silva, MF; Veiga, G; Rocha, L;
Publicação
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
Abstract
Quality inspection inspection systems are critical for maintaining product integrity. Being a repetitive task, when performed by operators only, it can be slow and error-prone. This paper introduces an automated inspection system for quality assessment in casting aluminum parts resorting to a robotic system. The method comprises two processes: filing detection and hole inspection. For filing detection, five deep learning modes were trained. These models include an object detector and four instance segmentation models: YOLOv8, YOLOv8n-seg, YOLOv8s-seg, YOLOv8m-seg, and Mask R-CNN, respectively. Among these, YOLOv8s-seg exhibited the best overall performance, achieving a recall rate of 98.10%, critical for minimizing false negatives and yielding the best overall results. Alongside, the system inspects holes, utilizing image processing techniques like template-matching and blob detection, achieving a 97.30% accuracy and a 2.67% Percentage of Wrong Classifications. The system improves inspection precision and efficiency while supporting sustainability and ergonomic standards, reducing material waste and reducing operator fatigue.
2025
Autores
Sylaios, G; Vasilijevic, A; Ristolainen, A; Valle, GG; Margirier, F; Oliveira, MA;
Publicação
OCEANS 2025 BREST
Abstract
ILIAD focuses on developing an ecosystem of interoperable Digital Twins for the Ocean by connecting to existing ocean data infrastructures, enhancing ocean data infrastructures with additional observation technologies and citizen science, employing numerical models and executing AI models, and aiding operational decision-making of marine and maritime activities. This work focuses on the diverse ILIAD Pilots and emphasizes sensors, data collection, and data management. Emphasis is given on new, low-cost sensors, their objectives, the novel technical aspects, the generated data, and how they can be used in the ILIAD project framework and the operation of ILIAD DTs.
2025
Autores
Alexandre, MR; Poinhos, R; Oliveira, BMPM; Correia, F;
Publicação
NUTRIENTS
Abstract
Background/Objectives: Obesity is a major contributor to cardiovascular disease, yet traditional risk assessment methods may overlook behavioral and circadian influences that modulate metabolic health. Chronotype, physical activity, sleep quality, eating speed, and breakfast habits have been increasingly associated with cardiometabolic outcomes. This study aims to evaluate the associations between these behavioral factors and both anthropometric and biochemical markers of cardiovascular risk among obese candidates for bariatric surgery. Methods: A cross-sectional study was conducted in a sample of 286 obese adults (78.3% females, mean 44.3 years, SD = 10.8, mean BMI = 42.5 kg/m2, SD = 6.2) followed at a central Portuguese hospital. Chronotype (reduced Morningness-Eveningness Questionnaire), sleep quality (Pittsburgh Sleep Quality Index), physical activity (Godin-Shephard Questionnaire), eating speed, and breakfast skipping were assessed. Cardiovascular risk markers included waist-to-hip ratio (WHR), waist-to-height ratio, A Body Shape Index (ABSI), Body Roundness Index, atherogenic index of plasma (AIP), triglyceride-glucose index (TyG), and homeostatic model assessment for insulin resistance (HOMA-IR). Results: Men exhibited significantly higher WHR, ABSI, HOMA-IR, TyG, and AIP. Eveningness was associated with higher insulin (r = -0.168, p = 0.006) and HOMA-IR (r = -0.156, p = 0.011). Poor sleep quality was associated with higher body fat mass (r = 0.151, p = 0.013), total cholesterol (r = 0.169, p = 0.005) and LDL cholesterol (r = 0.132, p = 0.030). Faster eating speed was associated with a higher waist circumference (r = 0.123, p = 0.038) and skeletal muscle mass (r = 0.160, p = 0.009). Conclusions: Male sex, evening chronotype, and poor sleep quality were associated with more adverse cardiometabolic profiles in individuals with severe obesity. These findings support the integration of behavioral and circadian factors into cardiovascular risk assessment strategies.
2025
Autores
Amarelo, A; da Mota, MCC; Amarelo, BLP; Ferreira, MC; Fernandes, CS;
Publicação
PAIN MANAGEMENT NURSING
Abstract
Objective: The aim of this systematic review and meta-analysis is to systematically collect, evaluate, and critically synthesize research findings on the effects of physical exercise on chemotherapy-induced peripheral neuropathy (CIPN). Method: The Joanna Briggs Institute (JBI) methodology for systematic reviews was adopted for this study. We searched the Medline (R), CINAHL, SportDiscus, and Scopus databases to identify relevant articles published from inception to March 2024. This review was reported in accordance with the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Results: Twelve studies met the inclusion criteria, totaling 928 participants. Interventions ranged from aerobic and resistance exercises to balance and strength training. A range of physical exercise interventions was explored, including brisk walking, endurance training, weight exercises, and resistance bands, as well as combined programs of aerobics, resistance, and balance training, all tailored to improve symptoms and quality of life in patients with chemotherapy-induced peripheral neuropathy. The meta-analysis focused on five studies that used the FACT/GOG-Ntx scale indicated a standardized mean difference of 0.50 (95% CI: 0.26, 0.74), favoring exercise, reflecting significant improvements in neuropathy symptoms. The heterogeneity among the studies was low (I 2 = 2%), suggesting consistency in the beneficial effects of exercise. Conclusions: From the results analyzed, the descriptive analysis of the 12 included studies shows promising outcomes not only related to individuals' perceptions of CIPN severity but also in terms of physical functioning, balance, ADL (Activities of Daily Living) performance, pain, and quality of life. The findings support the integration of structured exercise programs into oncological treatment plans. (c) 2024 The Authors. Published by Elsevier Inc. on behalf of American Society for Pain Management Nursing. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
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