Distributed Computing and Monitoring Technologies for Older Patients

This book summarizes various approaches for the automatic detection of health threats to older patients at home living alone. The text begins by briefly describing those who would most benefit from healthcare supervision. The book then summarizes possible scenarios for monitoring an older patient at home, deriving the common functional requirements for monitoring technology. Next, the work identifies the state of the art of technological monitoring approaches that are practically applicable to geriatric patients. A survey is presented on a range of such interdisciplinary fields as smart homes, telemonitoring, ambient intelligence, ambient assisted living, gerontechnology, and aging-in-place technology. The book discusses relevant experimental studies, highlighting the application of sensor fusion, signal processing and machine learning techniques. Finally, the text discusses future challenges, offering a number of suggestions for further research directions

Review of technology‐supported multimodal solutions for people with dementia

Funding Information: This research was partially funded by FAITH project (H2020?SC1?DTH?2019?875358), CARELINK project (AAL?CALL?2016?049), and Funda??o para a Ci?ncia e Tecnologia through the program UIDB/00066/2020 (CTS?Center of Technology and Systems).Acknowledgments: The authors acknowledge the European Commission for its support and partial funding; the partners of the research project FAITH project (H2020?SC1?DTH?2019?875358); and CARELINK, AAL?CALL?2016?049 funded by AAL JP and co?funded by the European Commission and National Funding Authorities of Ireland, Belgium, Portugal, and Switzerland. Partial support also comes from Funda??o para a Ci?ncia e Tecnologia through the program UIDB/00066/2020 (CTS?Center of Technology and Systems). Funding Information: Acknowledgments: The authors acknowledge the European Commission for its support and partial funding; the partners of the research project FAITH project (H2020‐SC1‐DTH‐2019‐875358); and CARELINK, AAL‐CALL‐2016‐049 funded by AAL JP and co‐funded by the European Commission and National Funding Authorities of Ireland, Belgium, Portugal, and Switzerland. Partial support also comes from Fundação para a Ciência e Tecnologia through the program UIDB/00066/2020 (CTS—Center of Technology and Systems). Funding Information: Funding: This research was partially funded by FAITH project (H2020‐SC1‐DTH‐2019‐875358), CARELINK project (AAL‐CALL‐2016‐049), and Fundação para a Ciência e Tecnologia through the program UIDB/00066/2020 (CTS—Center of Technology and Systems). Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.The number of people living with dementia in the world is rising at an unprecedented rate, and no country will be spared. Furthermore, neither decisive treatment nor effective medicines have yet become effective. One potential alternative to this emerging challenge is utilizing supportive technologies and services that not only assist people with dementia to do their daily activities safely and independently, but also reduce the overwhelming pressure on their caregivers. Thus, for this study, a systematic literature review is conducted in an attempt to gain an overview of the latest findings in this field of study and to address some commercially available supportive technologies and services that have potential application for people living with dementia. To this end, 30 potential supportive technologies and 15 active supportive services are identified from the literature and related websites. The technologies and services are classified into different classes and subclasses (according to their functionalities, capabilities, and features) aiming to facilitate their understanding and evaluation. The results of this work are aimed as a base for designing, integrating, developing, adapting, and customizing potential multimodal solutions for the specific needs of vulnerable people of our societies, such as those who suffer from different degrees of dementia.publishersversionpublishe

Review of the current status of research on smart homes and other domestic assistive technologies in support of the TAHI trials

The study provides an overview of developments in smart home technology and its use in the assistive technology sector. It includes an extensive literature review and detailed descriptions of current smart home installations in the UK and Europe. The report highlights the complexity of providing products and services in this area, and the relative immaturity of smart home technology in this sector. Many of the available products have emerged from office automation technologies developed for use in building control applications or from small niche markets in the assistive sector. Smart home developments have also concentrated on home control applications, but larger potential markets are also now being identified in other areas. Many of the trials described use technology to improve the safety and security of older and disabled people, concentrating more on the monitoring rather than home environment control. The report also demonstrates the practical difficulties faced in developing services in this sector. For many organisations these have been exploratory first steps in the use of technology to support care, and this lack of experience is reflected in common difficulties in specification and installation of equipment especially when retrofitting installations into buildings. Many developments have suffered from the lack of relevant experience of electrical and other contractors, so that it has proved difficult for organisations to identify both suppliers of equipment and people with the skills to install the technology. In the majority of cases there has been no formal evaluation of the developments, and it is therefore difficult to obtain evidence of the costs and benefits of using such technology to provide care and support independent living

Exploring the Landscape of Ubiquitous In-home Health Monitoring: A Comprehensive Survey

Ubiquitous in-home health monitoring systems have become popular in recent years due to the rise of digital health technologies and the growing demand for remote health monitoring. These systems enable individuals to increase their independence by allowing them to monitor their health from the home and by allowing more control over their well-being. In this study, we perform a comprehensive survey on this topic by reviewing a large number of literature in the area. We investigate these systems from various aspects, namely sensing technologies, communication technologies, intelligent and computing systems, and application areas. Specifically, we provide an overview of in-home health monitoring systems and identify their main components. We then present each component and discuss its role within in-home health monitoring systems. In addition, we provide an overview of the practical use of ubiquitous technologies in the home for health monitoring. Finally, we identify the main challenges and limitations based on the existing literature and provide eight recommendations for potential future research directions toward the development of in-home health monitoring systems. We conclude that despite extensive research on various components needed for the development of effective in-home health monitoring systems, the development of effective in-home health monitoring systems still requires further investigation.Comment: 35 pages, 5 figure

Mobile activity recognition and fall detection system for elderly people using Ameva algorithm

Currently, the lifestyle of elderly people is regularly monitored in order to establish guidelines for rehabilitation processes or ensure the welfare of this segment of the population. In this sense, activity recognition is essential to detect an objective set of behaviors throughout the day. This paper describes an accurate, comfortable and efficient system, which monitors the physical activity carried out by the user. An extension to an awarded activity recognition system that participated in the EvAAL 2012 and EvAAL 2013 competitions is presented. This approach uses data retrieved from accelerometer sensors to generate discrete variables and it is tested in a non-controlled environment. In order to achieve the goal, the core of the algorithm Ameva is used to develop an innovative selection, discretization and classification technique for activity recognition. Moreover, with the purpose of reducing the cost and increasing user acceptance and usability, the entire system uses only a smartphone to recover all the information requiredMinisterio de Economía y Competitividad HERMES TIN2013-46801-C4-1-rJunta de Andalucía Simon P11-TIC-8052Junta de Andalucía M-Learning P11-TIC-712

Events of daily living classification on an ambient assisted living environment

Dissertação de mestrado em Engenharia Eletrónica Industrial e ComputadoresPopulation ageing is a global demographic challenge and countries all around the world are facing significant pressure on their health and social care systems in order to mitigate the effects of it. The emerging social aspect introduced some crucial challenges to society and greater demands on the actual health care sector, which led to the emergence and increased integration of agefriendly innovative welfare technological-based care services for safe and independent ageing, including the assisted living technologies based on Ambient Intelligence (AmI) paradigm and Pervasive HealthCare. The Ambient Assisted Living (AAL) systems intend to provide caregivers with a detailed overview of their Events of Daily Living (EDL), which constitutes a clinical criteria to evaluate activity limitations. This dissertation addresses these challenges and contributes to the Ambient Assisted Living research, by means of a holistic solution composed of a beyond the state-of-the-art AAL technologies, representing a novel approach to assist in the investigation and on the modeling of a subset of Events of Daily Living (EDL), for sustaining independent living and a continual naturalistic assessment of health. The investigation was focused on 1) developing a multisensorial pervasive Research Data Acquistion (RDA) Platform with embedded Ambient Intelligence (AmI), 2) COTS to verify their validity and reliability for healthcare applications. The proposed solution has been thoroughly evaluated in the Ambient Assisted Living Laboratory that showed its effectiveness classifying EDL through the application of the AAL paradigm in the real world.O envelhecimento populacional é um desafio demográfico global e os países em todo o mundo estão sob com enorme pressão nos seus sistemas de saúde a fim de mitigar os efeitos que poderão advir. O aspecto social emergente introduziu alguns desafios cruciais para a sociedade e uma maior sobrecarga no setor de saúde, o que levou ao surgimento e aumento da integração de serviços inovadores de assistência social, de modo a que haja um envelhecimento seguro e independente, incluindo as tecnologias de assistência à vida com base no paradigma de Ambient Intelligence (AmI) e no Pervasive HealthCare, os sistemas de Ambient Assisted Living (AAL). Eles pretendem fornecer aos profissionais de saúde uma visão detalhada de seu Events of Daily Living (EDL), que constitui um critério clínico para avaliar as limitações da atividade. Para enfrentar estes desafios, esta dissertação contribui para a pesquisa na área de Ambient Assisted Living, por meio de uma solução holística composta por uma tecnologia além das tecnologias state-of-the-art, representando uma nova abordagem para auxiliar na investigação e na modelação de um subconjunto de Events of Daily Living (EDL), para sustentar uma vida independente e uma avaliação naturalística contínua da saúde. A investigação foi focada em 1) desenvolver uma plataforma multisensorial pervasiva Research Data Acquistion (RDA) com Ambient Intelligence (AmI), 2) COTS para verificar a sua validade e fiabilidade para aplicações de assistência médica. A solução proposta foi avaliada no Ambient Assisted Living Laboratory, que mostrou bastante eficácia ao classificar EDL através da aplicação do paradigma AAL no mundo real

Ultra-Wideband Radar-Based Activity Recognition Using Deep Learning

With recent advances in the field of sensing, it has become possible to build better assistive technologies. This enables the strengthening of eldercare with regard to daily routines and the provision of personalised care to users. For instance, it is possible to detect a person’s behaviour based on wearable or ambient sensors; however, it is difficult for users to wear devices 24/7, as they would have to be recharged regularly because of their energy consumption. Similarly, although cameras have been widely used as ambient sensors, they carry the risk of breaching users’ privacy. This paper presents a novel sensing approach based on deep learning for human activity recognition using a non-wearable ultra-wideband (UWB) radar sensor. UWB sensors protect privacy better than RGB cameras because they do not collect visual data. In this study, UWB sensors were mounted on a mobile robot to monitor and observe subjects from a specific distance (namely, 1.5–2.0 m). Initially, data were collected in a lab environment for five different human activities. Subsequently, the data were used to train a model using the state-of-the-art deep learning approach, namely long short-term memory (LSTM). Conventional training approaches were also tested to validate the superiority of LSTM. As a UWB sensor collects many data points in a single frame, enhanced discriminant analysis was used to reduce the dimensions of the features through application of principal component analysis to the raw dataset, followed by linear discriminant analysis. The enhanced discriminant features were fed into the LSTMs. Finally, the trained model was tested using new inputs. The proposed LSTM-based activity recognition approach performed better than conventional approaches, with an accuracy of 99.6%. We applied 5-fold cross-validation to test our approach. We also validated our approach on publically available dataset. The proposed method can be applied in many prominent fields, including human–robot interaction for various practical applications, such as mobile robots for eldercare.publishedVersio

A Mobile Healthcare Solution for Ambient Assisted Living Environments

Elderly people need regular healthcare services and, several times, are dependent of physicians’ personal attendance. This dependence raises several issues to elders, such as, the need to travel and mobility support. Ambient Assisted Living (AAL) and Mobile Health (m-Health) services and applications offer good healthcare solutions that can be used both on indoor and in mobility environments. This dissertation presents an ambient assisted living (AAL) solution for mobile environments. It includes elderly biofeedback monitoring using body sensors for data collection offering support for remote monitoring. The used sensors are attached to the human body (such as the electrocardiogram, blood pressure, and temperature). They collect data providing comfort, mobility, and guaranteeing efficiency and data confidentiality. Periodic collection of patients’ data is important to gather more accurate measurements and to avoid common risky situations, like a physical fall may be considered something natural in life span and it is more dangerous for senior people. One fall can out a life in extreme cases or cause fractures, injuries, but when it is early detected through an accelerometer, for example, it can avoid a tragic outcome. The presented proposal monitors elderly people, storing collected data in a personal computer, tablet, or smartphone through Bluetooth. This application allows an analysis of possible health condition warnings based on the input of supporting charts, and real-time bio-signals monitoring and is able to warn users and the caretakers. These mobile devices are also used to collect data, which allow data storage and its possible consultation in the future. The proposed system is evaluated, demonstrated and validated through a prototype and it is ready for use. The watch Texas ez430-Chronos, which is capable to store information for later analysis and the sensors Shimmer who allow the creation of a personalized application that it is capable of measuring biosignals of the patient in real time is described throughout this dissertation

A Conceptual Model using Ambient Assisted Living to Provide a Home Proactive Monitoring System for Elderly People in the Kingdom of Saudi Arabia

The growth in the ageing population is rapidly increasing and their care cost will be a challenging issue in the future. The number of elderly people worldwide (defined as those aged 60 years and older) was 202 million in 1950; this number has since quadrupled to reach 901 million and is expected to triple again by 2100. In particular, the number of elderly people in the Kingdom of Saudi Arabia (KSA) is increasing rapidly, from 5% of the total population in 2015 to a forecasted 20.9% by 2050. Clearly, the cost of taking care of elderly people is already a challenge, but it will be very difficult to meet in the future, when it will lead to a much higher expenditure on healthcare facilities. Furthermore, although elderly people are vulnerable to a decline in their health, they do not wish to live as they did in the 1970s to 1990s. Instead, their desire is to live independently in their own homes and continue to practice normal activities. In fact, Saudi culture is changing, and the children tend not to live with their parents as they used to. However, the literature review indicates that there is a lack of professionally designed systems that can fulfil the growing needs or requirements of elderly people in the KSA. These demographic changes raise a number of challenges related to the elderly people’s quality of life, including health, autonomy, care, social communication, and the utilisation of institutional services. These challenges require novel approaches to provide dependable self-adapting technological innovations. The era of Information and Communication Technology (ICT) has changed the world of the ageing population. Ambient Assisted Living (AAL) aims to improve the quality of life of elderly people, and to provide them with technologies and services that support their daily activities, help them to live longer and remain independently at home. The aims and objectives of this research are to review Ambient Assisted Living Technology, to provide examples of relevant technologies and applications, and to examine attitudes and perceptions of elderly people towards using AAL technologies in the KSA. This research also explores the factors of AAL, identifying those that affect the adoption of these technologies in the KSA, by conducting a systematic review, and using quantitative and qualitative analyses. The questionnaire results showed that elderly Saudi Arabians are willing and intending to accept and use AAL technologies, and that there are many factors that influence their adoption and use of AAL technologies. This provides an insight for solutions to the provision of support for their independent living. Thus, we developed a conceptual model using AAL to provide a Home Proactive Monitoring System (AALHPMS) that supports the stakeholders in adopting AAL technologies. We envisage that the AALHPMS can fulfil the needs and requirements of elderly people, motivate healthcare providers to implement AAL technologies, and assist the Saudi Government to make suitable provision for issues associated with the ageing population. In addition, a knowledge-based-system was built using a rule-based system. Experiments using Smart watches were conducted to monitor the heart rates. Further experiments using ZigBee, Bluetooth beacons, and surveillance cameras technology were also undertaken for monitoring the movement of elderly persons at their home. A website was also developed to disseminate knowledge related to ageing population and AAL technology in Saudi Arabia