Ambient assisted living technology: comparative perspectives of users and caregivers

Developed societies are currently facing severe demographic changes: the world population is ageing at an unprecedented rate. This demographic trend will be also followed by an increase of people with physical limitations. New challenges are being raised to the traditional health care systems, not only in Portugal, but also in all other European states. There is an urgent need to find solutions that allow extending the time people can live in their preferred environment by increasing their autonomy, self-confidence and mobility. AAL4ALL is a project currently being developed in cooperation with 34 Portuguese interdisciplinary partners, from industry to academia, R&D and social disciplines, which employs a novel conceptual approach through the development of an ecosystem of products and services for Ambient Assisted Living (AAL) associated to a business model and validated through large scale trial. This paper presents a comparative perspective of the needs and attitudes towards technology of the AAL users and caregivers identified in the analysis of a set of three different surveys: a users survey targeted at the Portuguese seniors and pre-seniors; an informal caregivers survey targeted at the family, friends and neighbours who provide care without any financial compensation; and a formal caregivers survey targeted at physicians, nurses,psychologists, social workers, and direct-care workers providing care to elders. The first results indicate that AAL solutions must be affordable,user friendly and have a true perceived benefit to their users.

Physical consequences of falls in the elderly: a literature review from 1995 to 2010

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.

Physical consequences of falls in the elderly: a literature review from 1995 to 2010

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.

Integration of Individualized Management Systems (MSs) as an Aggregating Factor of Sustainable Value for Organizations: An Overview Through a Review of the Literature

Nowadays, there exist various standards for individual management systems (MSs), at least, one for each stakeholder. New ones will be published. An integrated management system (IMS) aims to integrate some or all components of the business into one coherent and efficient MS. Maximizing integration is more and more a strategic priority in that it constitutes an opportunity to eliminate and/or reduce potential factors of destruction of value for the organizations and also to be more competitive and consequently promote its sustainable success. A preliminary investigation was conducted on a Portuguese industrial company which, over the years, has been adopting gradually, in whole or in part, individualized management system standards (MSSs). A research, through a questionnaire, was performed with the objective to develop, in a real business environment, an adequate and efficient IMS-QES (quality, environment, and safety) model and to potentiate for the future a generic IMS model to integrate other MSSs. The strategy and research methods have taken into consideration the case study. It was obtained a set of relevant conclusions resulting from the statistical analyses of the responses to the survey. Globally, the investigation results, by themselves, justified and prioritized the conception of a model of development of the IMS-QES and consequent definition and validation of a structure of an IMS-QES model, to be implemented at the small- and medium-sized enterprise (SME) where the investigation was conducted.

Comparative analysis between statistical and artificial intelligence models in business failure prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Comparative Analysis between Statistical and Artificial Intelligence Models in Business Failure Prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.