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Polytechnic Institute of Cávado and Ave, Portugal
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4 Papers

Powered Wearable Technologies for Dementia Care: Evaluating Activity Recognition Models and Dataset Challenges

Topics: Wearable Healthcare; “Intelligent” Medical Devices and Systems

Authors: Mariana Carvalho 1 , Inês Rocha 1 , Marcelo Arantes 1 , Ricardo Linhares 1 , José Soares 1 , António Moreira 1 ; 2 , João Vilaça 1 ; 2 , Demétrio Matos 3 , Pedro Morais 1 ; 2 and Vítor Carvalho 1 ; 2

Affiliations: 1 2Ai−School of Technology, Polytechnic University of Cávado and Ave (IPCA), Campus of IPCA, 4750-810 Barcelos, Portugal , 2 LASI−Associate Laboratory of Intelligent Systems, 4800-058 Guimarães, Portugal , 3 Research Institute for Design, Media and Culture (ID+), School of Design, Polytechnic of Cávado and Ave, 4750-810 Barcelos, Portugal

Digital Object Identifier: 10.5220/0013396600003911

Proceedings of WHC 2025, ISBN: 978-989-758-731-3

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Dementia is a progressive neurological condition affecting millions worldwide, posing significant challenges for patients and caregivers. Wearable technologies integrated with artificial intelligence (AI) provide promising solutions for continuous activity monitoring, supporting dementia care. This study evaluates the performance of various AI models, including tree-based methods and deep learning approaches, in recognizing activities relevant to dementia care. While the first excelled in handling class imbalances and recognizing common activities, deep learning models demonstrated superior capabilities in capturing complex temporal and spatial patterns. Additionally, a comprehensive analysis of 30 datasets revealed significant gaps, including limited representation of elderly participants, insufficient activity coverage, short recording durations, and a lack of real-world environmental data. To address these gaps, future work should focus on developing datasets tailored to dementia care, incorporating long-duration recordings, diverse activities, and realistic contexts. This study highlights the potential of AI-powered wearable systems to transform dementia management, enabling accurate activity recognition, early anomaly detection, and improved quality of life for patients and caregivers.

Application to Quantify Fetal Lung Branching on Rat Explants

Topics: Segmentation and Grouping; Features Extraction; Medical Image Applications

Authors: Pedro L. Rodrigues 1 , Sara Granja 2 , António Moreira 1 , Nuno Rodrigues 3 and João L. Vilaça 4

Affiliations: 1 University of Minho and PT Government Associate Laboratory, Portugal , 2 PT Government Associate Laboratory, Portugal , 3 Polytechnic Institute of Cávado and Ave and University of Minho, Portugal , 4 University of Minho and Polytechnic Institute of Cávado and Ave, Portugal

Digital Object Identifier: 10.5220/0004220900670070

Proceedings of VISAPP 2013/VISIGRAPP, ISBN: 978-989-8565-48-8

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Recently, regulating mechanisms of branching morphogenesis of fetal lung rat explants have been an essential tool for molecular research. The development of accurate and reliable segmentation techniques may be essential to improve research outcomes. This work presents an image processing method to measure the perimeter and area of lung branches on fetal rat explants. The algorithm starts by reducing the noise corrupting the image with a pre-processing stage. The outcome is input to a watershed operation that automatically segments the image into primitive regions. Then, an image pixel is selected within the lung explant epithelial, allowing a region growing between neighbouring watershed regions. This growing process is controlled by a statistical distribution of each region. When compared with manual segmentation, the results show the same tendency for lung development. High similarities were harder to obtain in the last two days of culture, due to the increased number of peripheral airway buds and complexity of lung architecture. However, using semiautomatic measurements, the standard deviation was lower and the results between independent researchers were more coherent.
Collapse Button Related Ontology Subjects/Areas/Topics (6)
Applications and Services

Features Extraction

Medical Image Applications

Computer Vision, Visualization and Computer Graphics

Image and Video Analysis

Segmentation and Grouping

Assessment of 3D Scanners for Modeling Pectus Carinatum Corrective Bar

Topics: Image-Based Modeling and 3D Reconstruction; Device Calibration, Characterization and Modeling; Medical Image Applications; Imaging for Cultural Heritage (Modeling/Simulation, Virtual Restoration)

Authors: António H. J. Moreira 1 , João Gomes Fonseca 2 , Pedro L. Rodrigues 1 , Jaime C. Fonseca 3 , A. C. M. Pinho 3 , Jorge Correia-Pinto 2 , Nuno F. Rodrigues 4 and João L. Vilaça 5

Affiliations: 1 University of Minho and PT Government Associate Laboratory, Portugal , 2 PT Government Associate Laboratory, Portugal , 3 University of Minho, Portugal , 4 Polytechnic Institute of Cávado and Ave and University of Minho, Portugal , 5 University of Minho, PT Government Associate Laboratory and Polytechnic Institute of Cávado and Ave, Portugal

Digital Object Identifier: 10.5220/0004300901220125

Proceedings of VISAPP 2013/VISIGRAPP, ISBN: 978-989-8565-48-8

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Pectus Carinatum (PC) is a chest deformity consisting on the anterior protrusion of the sternum and adjacent costal cartilages. Non-operative corrections, such as the orthotic compression brace, require previous information of the patient chest surface, to improve the overall brace fit. This paper focuses on the validation of the Kinect scanner for the modelling of an orthotic compression brace for the correction of Pectus Carinatum. To this extent, a phantom chest wall surface was acquired using two scanner systems – Kinect and Polhemus FastSCAN – and compared through CT. The results show a RMS error of 3.25mm between the CT data and the surface mesh from the Kinect sensor and 1.5mm from the FastSCAN sensor.
Collapse Button Related Ontology Subjects/Areas/Topics (11)
Applications

Geometry and Modeling

Medical Image Applications

Applications and Services

Image Formation and Preprocessing

Pattern Recognition

Computer Vision, Visualization and Computer Graphics

Image-Based Modeling

Software Engineering
Device Calibration, Characterization and Modeling

Imaging for Cultural Heritage (Modeling/Simulation, Virtual Restoration)

Automatic Modeling of an Orthotic Bracing for Nonoperative Correction of Pectus Carinatum

Topics: Image-Based Modeling and 3D Reconstruction; Medical Image Applications

Authors: João L. Vilaça 1 , Pedro L. Rodrigues 2 , António H. J. Moreira 2 , João Gomes Fonseca 3 , A. C. M. Pinho 4 , Jaime C. Fonseca 4 and Nuno Rodrigues 5

Affiliations: 1 PT Government Associate Laboratory and Polytechnic Institute of Cávado and Ave, Portugal , 2 PT Government Associate Laboratory and University of Minho, Portugal , 3 PT Government Associate Laboratory, Portugal , 4 University of Minho, Portugal , 5 Polytechnic Institute of Cávado and Ave and University of Minho, Portugal

Digital Object Identifier: 10.5220/0004221100710074

Proceedings of VISAPP 2013/VISIGRAPP, ISBN: 978-989-8565-48-8

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Pectus Carinatum is a deformity of the chest wall, characterized by an anterior protrusion of the sternum, often corrected surgically due to cosmetic motivation. This work presents an alternative approach to the current open surgery option, proposing a novel technique based on a personalized orthosis. Two different processes for the orthosis’ personalization are presented. One based on a 3D laser scan of the patient chest, followed by the reconstruction of the thoracic wall mesh using a radial basis function, and a second one, based on a computer tomography scan followed by a neighbouring cells algorithm. The axial position where the orthosis is to be located is automatically calculated using a Ray-Triangle intersection method, whose outcome is input to a pseudo Kochenek interpolating spline method to define the orthosis curvature. Results show that no significant differences exist between the patient chest physiognomy and the curvature angle and size of the orthosis, allowing a better cosmetic outcome and less initial discomfort.
Collapse Button Related Ontology Subjects/Areas/Topics (8)
Applications

Geometry and Modeling

Pattern Recognition

Applications and Services

Image-Based Modeling

Software Engineering
Computer Vision, Visualization and Computer Graphics

Medical Image Applications

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