Browsing by Author "Cunha, Bruno"
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- Evaluating the Effectiveness of Bayesian and Neural Networks for Adaptive Schedulling SystemsPublication . Cunha, Bruno; Madureira, Ana Maria; Pereira, João Paulo; Pereira, IvoThe ability to adjust itself to users’ profile is imperative in modern system, given that many people interact with a lot of information in different ways. The creation of adaptive systems is a complex domain that requires very specific methods and the integration of several intelligent techniques, from an intelligent systems development perspective. Designing an adaptive system requires planning and training of user modelling techniques combined with existing system components. Based on the architecture for user modelling on Intelligent and Adaptive Scheduling Systems, this paper presents an analysis of using the mentioned architecture to characterize user’s behaviours and a case study comparing the employment of different user classifiers. Bayesian and Artificial Neural Networks were selected as the elements of the computational study and this paper presents a description on how to prepare them to deal with user information.
- Home-based rehabilitation of the shoulder using auxiliary systems and artificial intelligence: an overviewPublication . Cunha, Bruno; Ferreira, Ricardo; S. P. Sousa, AndreiaAdvancements in modern medicine have bolstered the usage of home-based rehabilitation services for patients, particularly those recovering from diseases or conditions that necessitate a structured rehabilitation process. Understanding the technological factors that can influence the efficacy of home-based rehabilitation is crucial for optimizing patient outcomes. As technologies continue to evolve rapidly, it is imperative to document the current state of the art and elucidate the key features of the hardware and software employed in these rehabilitation systems. This narrative review aims to provide a summary of the modern technological trends and advancements in home-based shoulder rehabilitation scenarios. It specifically focuses on wearable devices, robots, exoskeletons, machine learning, virtual and augmented reality, and serious games. Through an in-depth analysis of existing literature and research, this review presents the state of the art in home-based rehabilitation systems, highlighting their strengths and limitations. Furthermore, this review proposes hypotheses and potential directions for future upgrades and enhancements in these technologies. By exploring the integration of these technologies into home-based rehabilitation, this review aims to shed light on the current landscape and offer insights into the future possibilities for improving patient outcomes and optimizing the effectiveness of home-based rehabilitation programs.
- A Machine Learning App for Monitoring Physical Therapy at HomePublication . Pereira, Bruno; Cunha, Bruno; Viana, Paula; Lopes, Maria; Melo, Ana S. C.; Sousa, Andreia S. P.Shoulder rehabilitation is a process that requires physical therapy sessions to recover the mobility of the affected limbs. However, these sessions are often limited by the availability and cost of specialized technicians, as well as the patient’s travel to the session locations. This paper presents a novel smartphone-based approach using a pose estimation algorithm to evaluate the quality of the movements and provide feedback, allowing patients to perform autonomous recovery sessions. This paper reviews the state of the art in wearable devices and camera-based systems for human body detection and rehabilitation support and describes the system developed, which uses MediaPipe to extract the coordinates of 33 key points on the patient’s body and compares them with reference videos made by professional physiotherapists using cosine similarity and dynamic time warping. This paper also presents a clinical study that uses QTM, an optoelectronic system for motion capture, to validate the methods used by the smartphone application. The results show that there are statistically significant differences between the three methods for different exercises, highlighting the importance of selecting an appropriate method for specific exercises. This paper discusses the implications and limitations of the findings and suggests directions for future research.
- Smart dashboard for Hoffmann reflex analysisPublication . Cunha, Bruno; Ferreira, Ricardo; Carneiro, Ana Sofia; Sousa, AndreiaThe Hoffmann reflex is a is a neurophysiological test that provides insight into the functioning of the human nervous system. It is commonly used in clinical and research settings to evaluate the modulation of the monosynaptic spinal reflex. This paper focus the analysis of the Hoffmann reflex in the trapezius muscle, a muscle of particular interest for researchers and clinicians due to its importance in upper limb function and dynamic stability. However, the Hoffmann reflex analysis of this muscle bring some challenges as the need of applicating burst of electrical square impulses in each current intensity. A web-based smart dashboard, implemented in Python, which allows the user to visualize and analyze the Hoffmann reflex using various signals acquired through a constant current stimulator. The dashboard provides an intuitive and user-friendly interface that facilitates the selection of muscle signals of interest, analysis cycles, and start and end points for the signals. The visualizations offered by the dashboard, including overlapped and mean signal graphics, provide valuable insights into the Hoffmann reflex and its properties. Preliminary experiments with field experts and physiotherapists have yielded positive feedback on the usefulness of this tool, as they seek to gain a deeper understanding of the Hoffmann reflex, and we plan to further improve its capabilities in the future by employing machine learning techniques to automate the reflex detection.
- Smartphone-based video analysis for guiding shoulder therapeutic exercises: concurrent validity for movement quality controlPublication . Lopes, Maria; Melo, Ana S. C.; Cunha, Bruno; Sousa, Andreia S. P.Neuromuscular re-education through therapeutic exercise has a determinant role in chronic shoulder pain rehabilitation. Smartphones are an interesting strategy to extend the rehabilitation to a home-based scenario as it can increase the attraction and involvement of users by providing feedback. Objective: To analyze the concurrent validity of a smartphone’s application based on 2D video analysis against the gold-standard 3D optoelectronic system for assessing movement quality during upper limb therapeutic exercises. Methods: Fifteen young adults were evaluated while executing two different shoulder exercises with a smartphone’s 2D video and a 3D optoelectronic system simultaneously in two conditions: (1) with the supervision and instructions of a physiotherapist (guided exercise), and (2) without the feedback of the physiotherapist (non-guided exercise). The data obtained during the guided and non-guided exercises were compared to calculate the movement quality index based on the approximation of the non-guided exercise to the guided exercise for the head, trunk, and shoulder’s range of movement. The agreement of the movement quality index assessed with the smartphone application and the optoelectronic system was carried out through Bland–Altman analysis. Results: The Bland–Altman analysis indicates the range of agreement and bias tendency. This tendency demonstrates that the percentage of difference between the two methods increases as the movement quality index decreases. Conclusions: There is agreement between the movement quality evaluated by a gold-standard method and the developed application, although the proposed method appears to have less sensitivity for evaluating movements with lower quality index.
- The influence of artificial breast volume induction on postural stability, postural orientation, and neuromuscular control in healthy women: a cross-sectional studyPublication . Guedes, Diana C.; Carneiro, Daniela Ferreira; Alves, Leonel Agostinho Teixeira; Melo, Ana S. C.; Moreira, Juliana; Cunha, Bruno; Santos, Rubim; Noites, Andreia; Sousa, Andreia S. P.; C. Guedes, Diana; Melo, Ana; Santos Moreira, Juliana; Cunha, Bruno; Rubim Silva Santos, Manuel; Noites, Andreia; Pinheiro de Sousa, Andreia SofiaThe 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. 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. 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. 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.