Cunha, Bruno

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Cunha

First Name

Bruno

Name

Cunha, Bruno

Biography

Bruno Miguel Almeida Cunha. Completed the Doutoramento in Informática in 2021/02 by Universidade de Trás-os-Montes e Alto Douro, Mestrado in Master in Computer Science - Knowledge-based and Decision Support Technologies in 2015 by Instituto Politécnico do Porto Instituto Superior de Engenharia do Porto and Licenciatura in Engenharia Informática in 2013 by Instituto Politécnico do Porto Instituto Superior de Engenharia do Porto. Is Assistant Professor in Universidade Portucalense Infante Dom Henrique and Invited Assistant Professor in Universidade do Porto Faculdade de Ciências. Published 6 articles in journals. Has 6 section(s) of books and 3 book(s). Organized 5 event(s). Participated in 13 event(s). Supervised 1 MSc dissertation(s) e co-supervised 3. Supervised 6 work(s) of course completion of LSc/BSc. Has received 1 awards and/or honors. Participates and/or participated as Principal investigator in 1 project(s) and Researcher in 1 project(s). Works in the area(s) of Engineering and Technology with emphasis on Electrotechnical Engineering, Electronics and Informatics. In his curriculum Ciência Vitae the most frequent terms in the context of scientific, technological and artistic-cultural output are: Mechanical Engineering - Industrial Management; Job Shop Scheduling; Machine Learning; Optimization; Reinforcement Learning; Simulation.

Identifiers

0000-0002-8661-3080
581D-067C-6E6C
56404142800
T-8432-2019

Research Projects

Organizational Units

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Organizational Unit
CINTESIS.UPT - Centro de Investigação em Tecnologias e Serviços de Saúde
Centro de Investigação em Tecnologias e Serviços de Saúde (CINTESIS.UPT), former I2P, is an R&D unit devoted to the study of cognition and behaviour in context. With an interdisciplinary focus, namely on Education, Translational and Applied Psychology
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Organizational Unit
REMIT – Research on Economics, Management and Information Technologies
Centro de investigação que que tem como objetivo principal produzir e disseminar conhecimento teórico e aplicado que possibilite uma maior compreensão das dinâmicas e tendências económicas, empresariais, territoriais e tecnológicas do mundo contemporâneo e dos seus efeitos socioeconómicos. O REMIT adota uma perspetiva multidisciplinar que integra vários domínios científicos: Economia e Gestão; Ciências e Tecnologia; Turismo, Património e Cultura. Founded in 2017, REMIT – Research on Economics, Management and Information Technologies is a research unit of Portucalense University. Based on a multidisciplinary and interdisciplinary perspective it aims at responding to social challenges through a holistic approach involving a wide range of scientific fields such as Economics, Management, Science, Technology, Tourism, Heritage and Culture. Grounded on the production of advanced scientific knowledge, REMIT has a special focus on its application to the resolution of real issues and challenges, having as strategic orientations: - the understanding of local, national and international environment; - the development of activities oriented to professional practice, namely in the business world.

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    PublicationOpen Access
    The influence of artificial breast volume induction on postural stability, postural orientation, and neuromuscular control in healthy Women: A cross-sectional study
    2025-01-09 - Guedes, Diana C.; Carneiro, Daniela F.; Alves, Leonel A. T.; Melo, Ana S. C.; Moreira, Juliana; Cunha, Bruno; Santos, Rubim; Noites, Andreia; Sousa, Andreia S. P.
    (1) Background: The percentage of breast augmentations has increased in recent years alongside the frequency of implant removals. Musculoskeletal and postural disorders are often overlooked during this removal process. Research indicates that excess anterior load from breast implants can disrupt postural control and potentially lead to short- or long-term musculoskeletal dysfunction. This study aims to evaluate the immediate changes in postural control after artificial breast augmentation in healthy female volunteers. (2) Methods: Spinal angles, the center of pressure (CoP), and electromyographic activity of the spinal muscles were recorded in the static position and during the functional reach test (FRT) without and with implants of different volumes (220 mL, 315 mL, and 365 mL). Subjective perceptions of effort, comfort, weight, and performance in the FRT were also assessed. (3) Results: Statistical differences were significant in the scapular elevator during the one-minute standing position (lower activation with the 220 mL implant compared to the control and 315 mL) and in the trapezius muscles during the FRT (lower activation in the upper trapezius in the 315 mL vs. control in the reach phase and 220 mL vs. control in the return phase and higher activation in the lower trapezius in the 315 and 365 mL vs. control in the reach phase). Additionally, significant differences were identified in the performance of the FRT and the associated subjective perceptions. (4) Conclusions: Breast implants with sizes of 220, 315, and 365 mL can alter scapular neuromuscular control, but these differences do not seem substantial enough to result in negative biomechanical effects in the short-term analysis.
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    PublicationRestricted Access
    Providing informative feedback in a low-cost rehabilitation system using machine learning
    2024-11-14 - Rodrigues, Paul; Amorim, Ivone; Cunha, Bruno
    Rehabilitation is a core process in helping people recover from a wide range of health issues, including injuries and diseases. Although advancements in technology and the use of artificial intelligence have facilitated the development of tools to aid in rehabilitation processes, there is a lack of low-cost solutions that patients, without requiring advanced care, can use at home. In this work, we propose a low-cost intelligent system for lower limb rehabilitation that uses machine learning to provide informative feedback to users. Compared to existing solutions, our system offers the advantage of real-time feedback, informing patients whether they are performing exercises correctly. It also suggests posture corrections to prevent injuries and accelerate the recovery process. Moreover, our system can be used at home on a smartphone, tablet, or personal computer, and does not require patients to purchase additional devices, which is a significant benefit. The system includes four exercises: Squat, Romanian Deadlift, Glute Bridge, and Donkey Kick. Validation tests with end-users reinforced the usability of this system and confirmed the importance of real-time feedback. The results were also useful for identifying areas for improvement, particularly with the Squat exercise, which is among the more challenging exercises to perform correctly.