57 resultados para Protec
Resumo:
Elders lose independence and wellbeing, accompanied by decreased functions in terms of hearing, vision, strength and coordination abilities. These factors contribute to balance difficulties that eventually lead to falls. The injuries due to falls, at this age, are risky, since most of the times may cause a significant – and permanent – decrease of quality of life or, in extreme cases, death. In this context, a fall detection system can bring an added value to assist elderly people.This paper describes a system consisting of a wearable sensor unit, a smartphone and a website. When the sensor detects a fall it sends an alert using the smartphone via Bluetooth 4.0, to notify the family members or stakeholders. The sensor device includes an inertial unit, a barometer, and a temperature and humidity sensor. The website displays the log of previous falls and enables the configuration of emergency contact numbers. The proposed fall detection system is one of multiple components within a larger project under development that offers a holistic perspective on falls; the complete wearable solution will also feature, among others, physical protection (minimizing the impact of falls that occur).
Resumo:
In the last decade, population ageing has been registered as a global phenomenon. A relation exists between falling and ageing, since falling frequency increases significantly with age. In fact, one in three older adult falls annually. Although ageing is generically associated with decrease and degeneration of psychological and physical functions, it is still not common for the correct identification of risk factors to lead to a clinical prognosis of the elder being in risk of falling. Therefore, the goal of this review article is to identify, categorise and analyse typical ageing and fall factors mentioned in the literature as well as to quantify the number of times they were referenced. The research considered hundreds of publications, but analysis was then restricted to the 87 most pertinent articles written in English and published in journals or scientific magazines between 1995 and 2010. We concluded that falls among older adults can be characterised by the following: anatomic characteristics and physiological consequences of ageing; the pathologies that induce falls, which can be neurological, musculoskeletal, cardiovascular and other diseases; causes and risk factors of falls that can be behavioural, biological, environmental or socio-economic; type of physical consequences of falls, including fractures, bruises, injuries or other physical consequences; and strategies to prevent, mitigate or rehabilitate, which can be of a physical, environmental or behavioural nature.
Resumo:
In the last decade, population ageing has been registered as a global phenomenon. A relation exists between falling and ageing, since falling frequency increases significantly with age. In fact, one in three older adult falls annually. Although ageing is generically associated with decrease and degeneration of psychological and physical functions, it is still not common for the correct identification of risk factors to lead to a clinical prognosis of the elder being in risk of falling. Therefore, the goal of this review article is to identify, categorise and analyse typical ageing and fall factors mentioned in the literature as well as to quantify the number of times they were referenced. The research considered hundreds of publications, but analysis was then restricted to the 87 most pertinent articles written in English and published in journals or scientific magazines between 1995 and 2010. We concluded that falls among older adults can be characterised by the following: anatomic characteristics and physiological consequences of ageing; the pathologies that induce falls, which can be neurological, musculoskeletal, cardiovascular and other diseases; causes and risk factors of falls that can be behavioural, biological, environmental or socio-economic; type of physical consequences of falls, including fractures, bruises, injuries or other physical consequences; and strategies to prevent, mitigate or rehabilitate, which can be of a physical, environmental or behavioural nature.
Resumo:
A hierarchical matrix is an efficient data-sparse representation of a matrix, especially useful for large dimensional problems. It consists of low-rank subblocks leading to low memory requirements as well as inexpensive computational costs. In this work, we discuss the use of the hierarchical matrix technique in the numerical solution of a large scale eigenvalue problem arising from a finite rank discretization of an integral operator. The operator is of convolution type, it is defined through the first exponential-integral function and, hence, it is weakly singular. We develop analytical expressions for the approximate degenerate kernels and deduce error upper bounds for these approximations. Some computational results illustrating the efficiency and robustness of the approach are presented.
Resumo:
This thesis is dedicated to the study of disclosure about derivative instruments and their determinants, by Portuguese companies. We have defined the following as our main research objectives: to identify the extent of disclosure relating to derivative instruments presented by Portuguese companies; to analyze the developments in the level of disclosure; and to identify the determinants of the level of disclosure. To this end, we have examined the information that has been disclosed by listed companies, for the period 2003–2009, and by companies belonging to the banking sector and insurance sector (hereinafter identified as financial firms), for 2009. We were able to conclude, in our first phase of research, that the number of disclosing firms has evolved positively, during the period 2003–2009, and that the level of disclosure has also evolved positively. On the other hand, the values obtained in the disclosure index indicate that companies are worried about compliance with accounting standards which became mandatory in 2005 and in 2007. This indicates that the adoption of the IASB’s standards since 2005 and the mandatory adoption of International Financial Reporting Standard (IFRS) No. 7, since 2007, have influenced the level of disclosure.
Resumo:
Cerebral vascular disease is the primary cause of permanent disability in Portugal. Impaired stability is considered an important feature after stroke as it is related with higher risk of falls and functional dependence. Physiotherapy intervention usually starts early after stroke in order to direct motor recovery and help patients to improve their ability to perform activities of daily living (ADL). Purpose: to investigate the relationship of balance to functionality in acute stroke patients. Methods: 16 subjects (8 women and 8 men), mean age 63,62 ± 2,16y, with unilateral ischemic stroke in the middle cerebral artery territory, who were admitted to physiotherapy department of Fernando Fonseca Hospital in Portugal, within the first month after stroke were recruited to participate in this study. All subjects have no cognitive impairment according to Mini Mental State, no history of lower extremity orthopedic problems and no other disease that could interfere with treatments. All patients gave their inform consent to participate in this study. Subjects were assessed with the Modified Barthel Index (MBI) and the Berg Balance Scale (BBS).
Resumo:
The study of biosignals has had a transforming role in multiple aspects of our society, which go well beyond the health sciences domains to which they were traditionally associated with. While biomedical engineering is a classical discipline where the topic is amply covered, today biosignals are a matter of interest for students, researchers and hobbyists in areas including computer science, informatics, electrical engineering, among others. Regardless of the context, the use of biosignals in experimental activities and practical projects is heavily bounded by the cost, and limited access to adequate support materials. In this paper we present an accessible, albeit versatile toolkit, composed of low-cost hardware and software, which was created to reinforce the engagement of different people in the field of biosignals. The hardware consists of a modular wireless biosignal acquisition system that can be used to support classroom activities, interface with other devices, or perform rapid prototyping of end-user applications. The software comprehends a set of programming APIs, a biosignal processing toolbox, and a framework for real time data acquisition and postprocessing. (C) 2014 Elsevier Ireland Ltd. All rights reserved.
Resumo:
The first and second authors would like to thank the support of the PhD grants with references SFRH/BD/28817/2006 and SFRH/PROTEC/49517/2009, respectively, from Fundação para a Ciência e Tecnol ogia (FCT). This work was partially done in the scope of the project “Methodologies to Analyze Organs from Complex Medical Images – Applications to Fema le Pelvic Cavity”, wi th reference PTDC/EEA- CRO/103320/2008, financially supported by FCT.
Resumo:
This paper presents a micro power light energy harvesting system for indoor environments. Light energy is collected by amorphous silicon photovoltaic (a-Si:H PV) cells, processed by a switched capacitor (SC) voltage doubler circuit with maximum power point tracking (MPPT), and finally stored in a large capacitor. The MPPT fractional open circuit voltage (V-OC) technique is implemented by an asynchronous state machine (ASM) that creates and dynamically adjusts the clock frequency of the step-up SC circuit, matching the input impedance of the SC circuit to the maximum power point condition of the PV cells. The ASM has a separate local power supply to make it robust against load variations. In order to reduce the area occupied by the SC circuit, while maintaining an acceptable efficiency value, the SC circuit uses MOSFET capacitors with a charge sharing scheme for the bottom plate parasitic capacitors. The circuit occupies an area of 0.31 mm(2) in a 130 nm CMOS technology. The system was designed in order to work under realistic indoor light intensities. Experimental results show that the proposed system, using PV cells with an area of 14 cm(2), is capable of starting-up from a 0 V condition, with an irradiance of only 0.32 W/m(2). After starting-up, the system requires an irradiance of only 0.18 W/m(2) (18 mu W/cm(2)) to remain operating. The ASM circuit can operate correctly using a local power supply voltage of 453 mV, dissipating only 0.085 mu W. These values are, to the best of the authors' knowledge, the lowest reported in the literature. The maximum efficiency of the SC converter is 70.3 % for an input power of 48 mu W, which is comparable with reported values from circuits operating at similar power levels.
Resumo:
With the advent of wearable sensing and mobile technologies, biosignals have seen an increasingly growing number of application areas, leading to the collection of large volumes of data. One of the difficulties in dealing with these data sets, and in the development of automated machine learning systems which use them as input, is the lack of reliable ground truth information. In this paper we present a new web-based platform for visualization, retrieval and annotation of biosignals by non-technical users, aimed at improving the process of ground truth collection for biomedical applications. Moreover, a novel extendable and scalable data representation model and persistency framework is presented. The results of the experimental evaluation with possible users has further confirmed the potential of the presented framework.
Resumo:
The Check Your Biosignals Here initiative (CYBHi) was developed as a way of creating a dataset and consistently repeatable acquisition framework, to further extend research in electrocardiographic (ECG) biometrics. In particular, our work targets the novel trend towards off-the-person data acquisition, which opens a broad new set of challenges and opportunities both for research and industry. While datasets with ECG signals collected using medical grade equipment at the chest can be easily found, for off-the-person ECG data the solution is generally for each team to collect their own corpus at considerable expense of resources. In this paper we describe the context, experimental considerations, methods, and preliminary findings of two public datasets created by our team, one for short-term and another for long-term assessment, with ECG data collected at the hand palms and fingers. (C) 2013 Elsevier Ireland Ltd. All rights reserved.
Resumo:
Electrocardiography (ECG) biometrics is emerging as a viable biometric trait. Recent developments at the sensor level have shown the feasibility of performing signal acquisition at the fingers and hand palms, using one-lead sensor technology and dry electrodes. These new locations lead to ECG signals with lower signal to noise ratio and more prone to noise artifacts; the heart rate variability is another of the major challenges of this biometric trait. In this paper we propose a novel approach to ECG biometrics, with the purpose of reducing the computational complexity and increasing the robustness of the recognition process enabling the fusion of information across sessions. Our approach is based on clustering, grouping individual heartbeats based on their morphology. We study several methods to perform automatic template selection and account for variations observed in a person's biometric data. This approach allows the identification of different template groupings, taking into account the heart rate variability, and the removal of outliers due to noise artifacts. Experimental evaluation on real world data demonstrates the advantages of our approach.
Resumo:
Applications involving biosignals, such as Electrocardiography (ECG), are becoming more pervasive with the extension towards non-intrusive scenarios helping targeting ambulatory healthcare monitoring, emotion assessment, among many others. In this study we introduce a new type of silver/silver chloride (Ag/AgCl) electrodes based on a paper substrate and produced using an inkjet printing technique. This type of electrodes can increase the potential applications of biosignal acquisition technologies for everyday life use, given that there are several advantages, such as cost reduction and easier recycling, resultant from the approach explored in our work. We performed a comparison study to assess the quality of this new electrode type, in which ECG data was collected with three types of Ag/AgCl electrodes: i) gelled; ii) dry iii) paper-based inkjet printed. We also compared the performance of each electrode when acquired using a professional-grade gold standard device, and a low cost platform. Experimental results showed that data acquired using our proposed inkjet printed electrode is highly correlated with data obtained through conventional electrodes. Moreover, the electrodes are robust to high-end and low-end data acquisition devices. Copyright © 2014 SCITEPRESS - Science and Technology Publications. All rights reserved.
Resumo:
Discrete data representations are necessary, or at least convenient, in many machine learning problems. While feature selection (FS) techniques aim at finding relevant subsets of features, the goal of feature discretization (FD) is to find concise (quantized) data representations, adequate for the learning task at hand. In this paper, we propose two incremental methods for FD. The first method belongs to the filter family, in which the quality of the discretization is assessed by a (supervised or unsupervised) relevance criterion. The second method is a wrapper, where discretized features are assessed using a classifier. Both methods can be coupled with any static (unsupervised or supervised) discretization procedure and can be used to perform FS as pre-processing or post-processing stages. The proposed methods attain efficient representations suitable for binary and multi-class problems with different types of data, being competitive with existing methods. Moreover, using well-known FS methods with the features discretized by our techniques leads to better accuracy than with the features discretized by other methods or with the original features. (C) 2013 Elsevier B.V. All rights reserved.
Resumo:
Physical computing has spun a true global revolution in the way in which the digital interfaces with the real world. From bicycle jackets with turn signal lights to twitter-controlled christmas trees, the Do-it-Yourself (DiY) hardware movement has been driving endless innovations and stimulating an age of creative engineering. This ongoing (r)evolution has been led by popular electronics platforms such as the Arduino, the Lilypad, or the Raspberry Pi, however, these are not designed taking into account the specific requirements of biosignal acquisition. To date, the physiological computing community has been severely lacking a parallel to that found in the DiY electronics realm, especially in what concerns suitable hardware frameworks. In this paper, we build on previous work developed within our group, focusing on an all-in-one, low-cost, and modular biosignal acquisition hardware platform, that makes it quicker and easier to build biomedical devices. We describe the main design considerations, experimental evaluation and circuit characterization results, together with the results from a usability study performed with volunteers from multiple target user groups, namely health sciences and electrical, biomedical, and computer engineering. Copyright © 2014 SCITEPRESS - Science and Technology Publications. All rights reserved.