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University of Minho, Portugal

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12 Papers

Development of a Proof-of-Concept Portable Electrostimulation Device for Lower Limbs Blood Flow Enhancement

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

Authors: Ricardo Pinto ¹ , Ana Almeida ¹ , Inês Rocha ¹ , Diogo Carvalho ² , Alexander Oks ³ , Miguel Carvalho ⁴ , João Vilaça ¹ and Vítor Carvalho ¹

Affiliations: ¹ Ai, School of Technology, Polytechnic University Cávado and Ave, Barcelos, Portugal , ² Klinikum Landkreis Tuttlingen, Tuttlingen, Germany , ³ Riga Technical University, Institute of Architecture and Design, Riga, Latvia , ⁴ C2T, School of Engineering, University of Minho, Guimaraes, Portugal

Digital Object Identifier: 10.5220/0013396700003911

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

Quick Abstract

This paper presents the design and implementation of a proof of concept of a wearable electrostimulation device aimed at improving blood flow in the lower limbs. The portable system, integrated into wearable compression socks, delivers electrical pulses for muscular stimulation in specific areas of the leg, using conductive yarns in their structure, promoting better blood flow. This device addresses the growing sedentary lifestyle and the resulting health issues like poor circulation, which can lead to severe complications. It features Bluetooth Low Energy (BLE) communication for real-time session control via a mobile application. The preliminary results demonstrate effective electrical stimulation, validated through testing, ensuring the feasibility of the system.

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

Quick Abstract

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.

A Personalized Rehabilitation System based on Wireless Motion Capture Sensors

Topics: Well-Being and Well-Working; Home Monitoring and Assisted Living Applications; Healthcare

Authors: Pedro Macedo ¹ , José Afonso ¹ and Ricardo Simões ²

Affiliations: ¹ University of Minho, Portugal , ² University of Minho and Polytechnic Institute of Cávado and Ave, Portugal

Digital Object Identifier: 10.5220/0005238202200228

Proceedings of SENSORNETS 2015, ISBN: 978-989-758-086-4

Quick Abstract

We live in an aging society, an issue that will be exacerbated in the coming decades, due to low birth rates and increasing life expectancy. With the decline in physical and cognitive functions with age, it is of the utmost importance to maintain regular physical activity, in order to preserve an individual’s mobility, motor capabilities and coordination. Within this context, this paper describes the development of a wireless sensor network and its application in a human motion capture system based on wearable inertial and magnetic sensors. The goal is to enable, through continuous real-time monitoring, the creation of a personalized home-based rehabilitation system for the elderly population and/or injured people. Within this system, the user can benefit from an assisted mode, in which their movements can be compared to a reference motion model of the same movements, resulting in visual feedback alerts given by the application. This motion model can be created previously, in a ‘learning phase’, under supervision of a caregiver.

Related Ontology Subjects/Areas/Topics (9)

Application Domains	Health Information Systems	Sensor Networks
Applications and Uses	Healthcare	Simulation and Modeling
Biomedical Engineering	Home Monitoring and Assisted Living Applications	Well-Being and Well-Working

A Telerehabilitation System based on Wireless Motion Capture Sensors

Topics: Wearable Sensors and Systems; Assistive Technologies

Authors: Pedro Macedo ¹ , José A. Afonso ¹ , Luis A. Rocha ¹ and Ricardo Simoes ²

Affiliations: ¹ University of Minho, Portugal , ² University of Minho and Polytechnic Institute of Cávado and Ave, Portugal

Digital Object Identifier: 10.5220/0004873800550062

Proceedings of PhyCS 2014, ISBN: 978-989-758-006-2

Quick Abstract

The constant growth of the elderly population in the world creates new challenges and opportunities in health care systems. New technological solutions have to be found in order to meet the needs and demands of our aging society. The welfare and quality of life of the elderly population must be a priority. Continuous physical activity will play an important role, due to the increase of the retirement age. However, physiotherapy can be expensive, even when the desire movements are autonomous and simple, also requires people to move to rehabilitation centres. Within this context, this paper describes the development and preliminary tests of a wireless sensor network, based on wearable inertial and magnetic sensors, applied to the capture of human motion. This will enable a personalized home-based rehabilitation system for the elderly or people in remote physical locations.

Related Ontology Subjects/Areas/Topics (14)

Applications	Health Engineering and Technology Applications	Pattern Recognition
Assistive Technologies	Health Information Systems	Physiological Computing Systems
Biomedical Engineering	Human-Computer Interaction	Software Engineering
Biomedical Signal Processing	Neural Rehabilitation	Wearable Sensors and Systems
Devices	Neurotechnology, Electronics and Informatics

A Wireless EEG Acquisition Platform based on Embedded Systems

Topics: Biomedical Instrumentation; Embedded Signal Processing; Wireless Systems

Authors: F. Pinho ¹ , J. H. Correia ¹ and N. S. Dias ²

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

Digital Object Identifier: 10.5220/0004325601900196

Proceedings of BIODEVICES 2013/BIOSTEC, ISBN: 978-989-8565-34-1

Quick Abstract

This paper proposes a wireless EEG acquisition platform based on Open Multimedia Architecture Platform (OMAP) embedded system. A high-impedance active dry electrode was tested for improving the scalp-electrode interface. It was used the sigma-delta ADS1298 analog-to-digital converter, and developed a “kernelspace” character driver to manage the communications between the converter unit and the OMAP’s ARM core. The acquired EEG signal data is processed by a “userspace” application, which accesses the driver’s memory, saves the data to a SD-card and transmits them through a wireless TCP/IP-socket to a PC. The electrodes were tested through the alpha wave replacement phenomenon. The experimental results presented the expected alpha rhythm (8-13 Hz) reactiveness to the eyes opening task. The driver spends about 725 μs to acquire and store the data samples. The application takes about 244 μs to get the data from the driver and 1.4 ms to save it in the SD-card. A WiFi throughput of 12.8Mbps was measured which results in a transmission time of 5 ms for 512 kb of data. The embedded system consumes about 200 mAh when wireless off and 400 mAh when it is on. The system exhibits a reliable performance to record EEG signals and transmit them wirelessly. Besides the microcontroller-based architectures, the proposed platform demonstrates that powerful ARM processors running embedded operating systems can be programmed with real-time constrains at the kernel level in order to control hardware, while maintaining their parallel processing abilities in high level software applications.

Related Ontology Subjects/Areas/Topics (5)

Biomedical Engineering		Biomedical Instruments and Devices		Wireless Systems
Biomedical Instrumentation		Embedded Signal Processing

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

Quick Abstract

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.

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

Quick Abstract

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.

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

Quick Abstract

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.

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

Needs and Opportunities in Ambient Assisted Living in Portugal

Authors: Ricardo Vardasca ¹ , Liliana Ferreira ² and Ricardo Simoes ³

Affiliations: ¹ University of Minho, Portugal , ² Fraunhofer AICOS Portugal, Portugal , ³ University of Minho and Polytechnic Institute of Cávado and Ave, Portugal

Digital Object Identifier: 10.5220/0003889201000108

Proceedings of AAL 2012/BIOSTEC, ISBN: 978-989-8425-93-5

Quick Abstract

The exponential raise in the age dependency rate together with the difficulties in having conventional care solutions opens the space for the appearance and development of innovative Ambient Assisted Living (AAL) solutions. However, the development of these solutions requires a thorough understanding of user needs and wills. In this paper we present the scenarios being adopted in the context of AAL projects, as well as the products and services current available in each of the considered utilization scenarios. The needs of the Portuguese AAL users are analyzed through the discussion of some preliminary results from a survey targeted at the Portuguese population over 55 years old. These results will be used to characterize the needs and establish the readiness and willingness of elder Portuguese population in using AAL solutions.

Optimizing Electrode Positioning in 3-lead ECG Chest Devices

Authors: Ricardo Simoes ¹ , Joana Sousa ² , Cristina Nogueira-Silva ³ and Hugo Gamboa ⁴

Affiliations: ¹ University of Minho and Polytechnic Institute of Cávado and Ave, Portugal , ² PLUX - Wireless Biosignals and S.A., Portugal , ³ University of Minho, ICVS/3B’s - PT Government Associate Laboratory and Hospital de Braga, Portugal , ⁴ Universidade Nova de Lisboa, Portugal

Digital Object Identifier: 10.5220/0003885800810088

Proceedings of AAL 2012/BIOSTEC, ISBN: 978-989-8425-93-5

Quick Abstract

Although the 12-lead electrocardiogram has become an essential medical and research tool, many current and envisaged applications would benefit from simpler devices, using 3-lead ECG configuration. This is particularly true for Ambient Assisted Living (in a broad perspective). However, the chest anatomy of female patients, namely during pregnancy, can hamper the adequate placement of a 3-lead ECG device and, very often, electrodes are placed below the chest rather than at the precise thoracic landmarks. Thus, the aim of this study was to compare the effect of electrode positioning on the ECG signal of pregnant women and provide guidelines for device development. The effect of breast tissue on the ECG signal was investigated by relating breast size with the signal-to-noise ratio, root mean square and R-wave amplitude. Results show that the 3-lead ECG should be placed on the breast rather than under the breast and indicate positive correlation between breast size and signal-to-noise ratio.

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