Unidade de Investigação - CIIC - Computer Science and Communication Research Centre
URI permanente desta comunidade:
Navegar
Percorrer Unidade de Investigação - CIIC - Computer Science and Communication Research Centre por Objetivos de Desenvolvimento Sustentável (ODS) "03:Saúde de Qualidade"
A mostrar 1 - 9 de 9
Resultados por página
Opções de ordenação
- Blind Guide: An Ultrasound Sensor-based Body Area Network for Guiding Blind PeoplePublication . Pereira, António; Nunes, Nelson; Vieira, Daniel; Costa, Nuno; Fernandes, Hugo; Barroso, JoãoWireless Sensor Networks, in particular Wireless Body Area Networks, is a technology suggested by the research community as allowing elderly people, or people with some kind of disability, to live in a safer, responsive and comfortable environment while at their homes. One of the most active threats to the autonomous life of blind people is the quantity and variety of obstacles they face while moving, whether they are obstacles in the footpath or obstacles coming out from the walls of buildings. Hence, it is necessary to develop a solution that helps or assists blind people while moving either in indoor or outdoor scenarios, simultaneously allowing the use of the use of white cane or the Seeing Eye dog. In this article, the authors propose the use of an ultra-sound based body area network for obstacle detection and warning as a complementary and effective solution for aiding blind people when moving from place to place. According to the cost estimates of the solution and to the negligible setup time, this could be a real effective complementary solution for blind people.
- Body Area Networks in Healthcare: A Brief State of the ArtPublication . Roda-Sanchez, Luis; Olivares, Teresa; Fernández-Caballero, Antonio; Vera, Daniel; Costa, Nuno; Pereira, António Manuel de JesusA body area network (BAN) comprises a set of devices that sense their surroundings, activate and communicate with each other when an event is detected in its environment. Although BAN technology was developed more than 20 years ago, in recent years, its popularity has greatly increased. The reason is the availability of smaller and more powerful devices, more efficient communication protocols and improved duration of portable batteries. BANs are applied in many fields, healthcare being one of the most important through gathering information about patients and their surroundings. A continuous stream of information may help physicians with making well-informed decisions about a patient's treatment. Based on recent literature, the authors review BAN architectures, network topologies, energy sources, sensor types, applications, as well as their main challenges. In addition, the paper focuses on the principal requirements of safety, security, and sustainability. In addition, future research and improvements are discussed. © 2019 by the authors
- A distributed multiagent system architecture for body area networks applied to healthcare monitoringPublication . Felisberto, Filipe; Laza, Rosalía; Fdez-Riverola, Florentino; Pereira, AntónioIn the last years the area of health monitoring has grown significantly, attracting the attention of both academia and commercial sectors. At the same time, the availability of new biomedical sensors and suitable network protocols has led to the appearance of a new generation of wireless sensor networks, the so-called wireless body area networks. Nowadays, these networks are routinely used for continuous monitoring of vital parameters, movement, and the surrounding environment of people, but the large volume of data generated in different locations represents a major obstacle for the appropriate design, development, and deployment of more elaborated intelligent systems. In this context, we present an open and distributed architecture based on a multiagent system for recognizing human movements, identifying human postures, and detecting harmful activities. The proposed system evolved from a single node for fall detection to a multisensor hardware solution capable of identifying unhampered falls and analyzing the users’ movement. The experiments carried out contemplate two different scenarios and demonstrate the accuracy of our proposal as a real distributed movement monitoring and accident detection system. Moreover, we also characterize its performance, enabling future analyses and comparisons with similar approaches.
- Explainable prototype-based image classification using adaptive feature extractors in medical imagesPublication . Vasconcellos, Nicolas; Tavora, Luis M. N.; Miragaia, Rolando; Grilo, Carlos; Thomaz, LucasPrototype-based classifiers are a category of Explainable Artificial Intelligence methods that use representative samples from the data, called prototypes, to classify new inputs based on a similarity criterion. However, these methods often rely on pre-trained Convolutional Neural Networks as feature extractors, which may not be adapted for the specific type of data being used, thus not suited for identifying the most representative prototypes. In this paper, we propose a method named Explainable Prototype-based Image Classification, a cluster-oriented training strategy that enhances the performance and explainability of prototype-based classifiers. Our method uses a novel loss function, called Cluster Density Error, to fine-tune the feature extractor and preserve the most representative feature vectors in the latent space. We also use Principal Component Analysis-based approach to reduce the dimensionality and complexity of the feature vectors. We conduct experiments on four medical image datasets and compare the results with those from different prototype-based classifiers and state-of-the-art non-explainable learning methods. The proposed method demonstrated superior explainable capabilities and comparable classification performance to the compared methods. Specifically, the proposed method achieved up to 95.01% accuracy and 0.992 AUC using only 43 prototypes. This translated to an improvement in accuracy and AUC score of 21.54% and 9.06%, respectively, and a substantial reduction in the number of prototypes by 98,38%
- Explaining the seismic moment of large earthquakes by heavy and extremely heavy tailed modelsPublication . Felgueiras, Miguel MartinsThe search of physical laws that explain the energy released by the great magnitude earthquakes is a relevant question, since as a rule they cause heavy losses. Several statistical distributions have been considered in this process, namely heavy tailed laws, like the Pareto distribution with shape parameter α ≈ 0. 6667. Yet, for the usually considered Californian region (where earthquakes with moment magnitude, MW, greater than 7. 9 were never registered) the Pareto distribution with index near the above mentioned seems to have a "too heavy" tail for explaining the bigger earthquakes seismic moments. Usually an exponential tapper is applied to the distribution right tail (above the so called corner seismic moment), or another distribution is considered to explain these high seismic moment data (like another Pareto with different shape parameter). The situation is different for other regions where seisms of larger magnitudes do occur, leading to data sets for which heavy or even extremely heavy tailed models are appropriated. The purpose of this paper is to reduce the seismic moment, M0, of the very large earthquakes to particular heavy and extremely heavy tailed distributions. Using world seismic moment information, we apply Pareto, Log-Pareto and extended slash Pareto distributions to the data, truncated for M0 ≥ 1021 Nm and for M0 ≥ 1021. 25 Nm. For these great seisms we conclude that extended slash Pareto is a promising alternative to the more traditional Pareto and Log-Pareto distributions as a candidate to the real model underlying the data.
- Filtering Email Addresses, Credit Card Numbers and Searching for Bitcoin Artifacts with the Autopsy Digital Forensics SoftwarePublication . Domingues, Patricio; Frade, Miguel; Parreira, João MotaEmail addresses and credit card numbers found on digital forensic images are frequently an important asset in a forensic casework. However, the automatic harvesting of these data often yields many false positives. This paper presents the Forensic Enhanced Analysis (FEA) module for the Autopsy digital forensic software. FEA aims to eliminate false positives of email addresses and credit card numbers harvested by Autopsy, thus reducing the workload of the forensic examiner. FEA also harvests potential Bitcoin public addresses and private keys and validates them by looking into Bitcoin’s blockchain for the transactions linked to public addresses. FEA explores the report functionality of Autopsy and allows exports in CSV, HTML and XLS formats. Experimental results over four digital forensic images show that FEA eliminates as many as of email addresses and of credit card numbers.
- How Health Literacy impacts Polytechnic of Leiria Students?Publication . Teixeira Ascenso, Rita Margarida; Luis, Luis; Dias, Sara; Gonçalves, DulceIn 2021, aHealth Literacy(HL) evaluation among university students revealed notable limitations in HL. To assess the general HL of populations comprehensively, the European HLSurvey Questionnaire (HLS-EU-Q) was developed, encompassing 12 subdomains to provide a broad perspective on public health. In 2014, the questionnaire was adapted for use in Portugal, resulting in the HLS-EU-PT version, validated through a 16-question survey (HLS-EU-PT-Q16).Global HL andthreedomains’ indexes and levelswere determined, namely Healthcare (HC), Disease prevention (DP), and Health Promotion (HP). The HLSEU-Q16-PT assessment demonstrated satisfactory internal consistency, with 0.8834Cronbach's alpha coefficient.In this study, an online survey distributedbetween 2020-2021among Polytechnic of Leiria academia allowed data collection from various stakeholders, including 251 students, 109 professors, 15 researchers, and 55 other staff. From the430 responses,75 questions were analysed. The saved data wasthefocus of this work, regarding a thesis of the first edition of the master’s in data science to analysethe 251 surveyed studentsand their HL. The results revealed that thesestudents have lower HL index, and, in this case study,health areadegreeor school impactsHL.
- The Influence of Information Systems in the Management of Patients Service in the Hospital of LeiriaPublication . Conceição, Cristiana; Borges, José; Ascenso, Rita M.T.Hospital patients prefer to access the Emergency Department to be treated; this preference leads to some concern by the directors of public hospitals. Though, it is important to understand how consultation management is defined, especially in terms of information technology that can help in patients’ management. Among several Information Systems it was evaluated a specific SMS service, checking if it responded to the patients’ needs, whether patients were satisfied with the service and if it was efficient as expected, to reduce absence in scheduled encounters. So, it was followed a methodology: check faults to medical consultations and rebooking, along October 2014, then conduct questionnaires to patients by telephone, in order to understand if they are satisfied with the SMS service to recall a scheduled medical consultation, and if the service failure has or not to do with their faults. Among 2337 patients that fault in a month, 113 patients were questioned by phone (from 441 selected), 87.6% had received SMS on the mobile phone to alert the consultation day and 79.6% feel satisfied with the messaging service. Thus, the SMS service is expected to have an impact on reducing absence to scheduled consultations once patients are satisfied.
- Usability of Smartbands by the Elderly Population in the Context of Ambient Assisted Living ApplicationsPublication . Correia, Luís; Fuentes, Daniel; Ribeiro, José; Costa, Nuno; Reis, Arsénio; Rabadão, Carlos; Barroso, João; Pereira, AntónioNowadays, the Portuguese population is aging at a fast pace. The situation is more severe in the interior regions of the country, where the rural areas have few people and have been constantly losing population; these are mostly elderly who, in some cases, live socially isolated. They are also often deprived of some types of social, health and technological services. One of the current challenges with respect to the elderly is that of improving the quality of life for those who still have some autonomy and live in their own residences so that they may continue living autonomously, while receiving the assistance of some exterior monitoring and supporting services. The Internet of Things (IoT) paradigm demonstrates great potential for creating technological solutions in this area as it aims to seamlessly integrate information technology with the daily lives of people. In this context, it is necessary to develop services that monitor the activity and health of the elderly in real time and alert caregivers or other family members in the case of an unusual event or behaviour. It is crucial that the technological system is able to collect data in a nonintrusive manner and without requiring much interaction with the elderly. Smartband devices are very good candidates for this purpose and, therefore, this work proposes assessing the level of acceptance of the usage of a smartbands by senior users in their daily activities. By using the definition of an architecture and the development of a prototype, it was possible to test the level of acceptance of smartbands by a sample of the elderly population—with surprising results from both the elderly and the caregivers—which constitutes an important contribution to the research field of Ambient Assisted Living (AAL). The evaluation showed that most users did not feel that the smartband was intrusive to their daily tasks and even considered using it in the future, while caregivers considered that the platform was very intuitive.
