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

Monitoring elderly behavior via indoor position-based stigmergy

In this paper we present a novel approach for monitoring elderly people living alone and independently in their own homes. The proposed system is able to detect behavioral deviations of the routine indoor activities on the basis of a generic indoor localization system and a swarm intelligence method. For this reason, an in-depth study on the error modeling of state-of-the-art indoor localization systems is presented in order to test the proposed system under different conditions in terms of localization error. More specifically, spatiotemporal tracks provided by the indoor localization system are augmented, via marker-based stigmergy, in order to enable their self-organization. This allows a marking structure appearing and staying spontaneously at runtime, when some local dynamism occurs. At a second level of processing, similarity evaluation is performed between stigmergic marks over different time periods in order to assess deviations. The purpose of this approach is to overcome an explicit modeling of user's activities and behaviors that is very inefficient to be managed, as it works only if the user does not stray too far from the conditions under which these explicit representations were formulated. The effectiveness of the proposed system has been experimented on real-world scenarios. The paper includes the problem statement and its characterization in the literature, as well as the proposed solving approach and experimental settings

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

SHELDON Smart habitat for the elderly.

An insightful document concerning active and assisted living under different perspectives: Furniture and habitat, ICT solutions and Healthcare

When technology cares for people with dementia:A critical review using neuropsychological rehabilitation as a conceptual framework

Clinicians and researchers have become increasingly interested in the potential of technology in assisting persons with dementia (PwD). However, several issues have emerged in relation to how studies have conceptualized who the main technology user is (PwD/carer), how technology is used (as compensatory, environment modification, monitoring or retraining tool), why it is used (i.e., what impairments and/or disabilities are supported) and what variables have been considered as relevant to support engagement with technology. In this review we adopted a Neuropsychological Rehabilitation perspective to analyse 253 studies reporting on technological solutions for PwD. We analysed purposes/uses, supported impairments and disabilities and how engagement was considered. Findings showed that the most frequent purposes of technology use were compensation and monitoring, supporting orientation, sequencing complex actions and memory impairments in a wide range of activities. The few studies that addressed the issue of engagement with technology considered how the ease of use, social appropriateness, level of personalization, dynamic adaptation and carers' mediation allowed technology to adapt to PWD's and carers' preferences and performance. Conceptual and methodological tools emerged as outcomes of the analytical process, representing an important contribution to understanding the role of technologies to increase PwD's wellbeing and orient future research.University of Huddersfield, under grants URF301-01 and URF506-01

A Sensing Platform to Monitor Sleep Efficiency

Sleep plays a fundamental role in the human life. Sleep research is mainly focused on the understanding of the sleep patterns, stages and duration. An accurate sleep monitoring can detect early signs of sleep deprivation and insomnia consequentially implementing mechanisms for preventing and overcoming these problems. Recently, sleep monitoring has been achieved using wearable technologies, able to analyse also the body movements, but old people can encounter some difficulties in using and maintaining these devices. In this paper, we propose an unobtrusive sensing platform able to analyze body movements, infer sleep duration and awakenings occurred along the night, and evaluating the sleep efficiency index. To prove the feasibility of the suggested method we did a pilot trial in which several healthy users have been involved. The sensors were installed within the bed and, on each day, each user was administered with the Groningen Sleep Quality Scale questionnaire to evaluate the user’s perceived sleep quality. Finally, we show potential correlation between a perceived evaluation with an objective index as the sleep efficiency.</p

Enhanced Living Environments

This open access book was prepared as a Final Publication of the COST Action IC1303 “Algorithms, Architectures and Platforms for Enhanced Living Environments (AAPELE)”. The concept of Enhanced Living Environments (ELE) refers to the area of Ambient Assisted Living (AAL) that is more related with Information and Communication Technologies (ICT). Effective ELE solutions require appropriate ICT algorithms, architectures, platforms, and systems, having in view the advance of science and technology in this area and the development of new and innovative solutions that can provide improvements in the quality of life for people in their homes and can reduce the financial burden on the budgets of the healthcare providers. The aim of this book is to become a state-of-the-art reference, discussing progress made, as well as prompting future directions on theories, practices, standards, and strategies related to the ELE area. The book contains 12 chapters and can serve as a valuable reference for undergraduate students, post-graduate students, educators, faculty members, researchers, engineers, medical doctors, healthcare organizations, insurance companies, and research strategists working in this area

State of the art of audio- and video based solutions for AAL

Working Group 3. Audio- and Video-based AAL ApplicationsIt is a matter of fact that Europe is facing more and more crucial challenges regarding health and social care due to the demographic change and the current economic context. The recent COVID-19 pandemic has stressed this situation even further, thus highlighting the need for taking action. Active and Assisted Living (AAL) technologies come as a viable approach to help facing these challenges, thanks to the high potential they have in enabling remote care and support. Broadly speaking, AAL can be referred to as the use of innovative and advanced Information and Communication Technologies to create supportive, inclusive and empowering applications and environments that enable older, impaired or frail people to live independently and stay active longer in society. AAL capitalizes on the growing pervasiveness and effectiveness of sensing and computing facilities to supply the persons in need with smart assistance, by responding to their necessities of autonomy, independence, comfort, security and safety. The application scenarios addressed by AAL are complex, due to the inherent heterogeneity of the end-user population, their living arrangements, and their physical conditions or impairment. Despite aiming at diverse goals, AAL systems should share some common characteristics. They are designed to provide support in daily life in an invisible, unobtrusive and user-friendly manner. Moreover, they are conceived to be intelligent, to be able to learn and adapt to the requirements and requests of the assisted people, and to synchronise with their specific needs. Nevertheless, to ensure the uptake of AAL in society, potential users must be willing to use AAL applications and to integrate them in their daily environments and lives. In this respect, video- and audio-based AAL applications have several advantages, in terms of unobtrusiveness and information richness. Indeed, cameras and microphones are far less obtrusive with respect to the hindrance other wearable sensors may cause to one’s activities. In addition, a single camera placed in a room can record most of the activities performed in the room, thus replacing many other non-visual sensors. Currently, video-based applications are effective in recognising and monitoring the activities, the movements, and the overall conditions of the assisted individuals as well as to assess their vital parameters (e.g., heart rate, respiratory rate). Similarly, audio sensors have the potential to become one of the most important modalities for interaction with AAL systems, as they can have a large range of sensing, do not require physical presence at a particular location and are physically intangible. Moreover, relevant information about individuals’ activities and health status can derive from processing audio signals (e.g., speech recordings). Nevertheless, as the other side of the coin, cameras and microphones are often perceived as the most intrusive technologies from the viewpoint of the privacy of the monitored individuals. This is due to the richness of the information these technologies convey and the intimate setting where they may be deployed. Solutions able to ensure privacy preservation by context and by design, as well as to ensure high legal and ethical standards are in high demand. After the review of the current state of play and the discussion in GoodBrother, we may claim that the first solutions in this direction are starting to appear in the literature. A multidisciplinary 4 debate among experts and stakeholders is paving the way towards AAL ensuring ergonomics, usability, acceptance and privacy preservation. The DIANA, PAAL, and VisuAAL projects are examples of this fresh approach. This report provides the reader with a review of the most recent advances in audio- and video-based monitoring technologies for AAL. It has been drafted as a collective effort of WG3 to supply an introduction to AAL, its evolution over time and its main functional and technological underpinnings. In this respect, the report contributes to the field with the outline of a new generation of ethical-aware AAL technologies and a proposal for a novel comprehensive taxonomy of AAL systems and applications. Moreover, the report allows non-technical readers to gather an overview of the main components of an AAL system and how these function and interact with the end-users. The report illustrates the state of the art of the most successful AAL applications and functions based on audio and video data, namely (i) lifelogging and self-monitoring, (ii) remote monitoring of vital signs, (iii) emotional state recognition, (iv) food intake monitoring, activity and behaviour recognition, (v) activity and personal assistance, (vi) gesture recognition, (vii) fall detection and prevention, (viii) mobility assessment and frailty recognition, and (ix) cognitive and motor rehabilitation. For these application scenarios, the report illustrates the state of play in terms of scientific advances, available products and research project. The open challenges are also highlighted. The report ends with an overview of the challenges, the hindrances and the opportunities posed by the uptake in real world settings of AAL technologies. In this respect, the report illustrates the current procedural and technological approaches to cope with acceptability, usability and trust in the AAL technology, by surveying strategies and approaches to co-design, to privacy preservation in video and audio data, to transparency and explainability in data processing, and to data transmission and communication. User acceptance and ethical considerations are also debated. Finally, the potentials coming from the silver economy are overviewed.publishedVersio

Ambient assisted living systems for older people with Alzheimer’s

The older people population in the world is increasing as a result of advances in technology, public health, nutrition and medicine. People aged sixty or over were more than 11.5% of the global population in 2012. By 2050, this percentage is expected to be doubled to two billion and around thirty-three countries will have more than ten million people aged sixty or more each. With increasing population age around the word, medical and everyday support for the older people, especially those who live with Alzheimer’s who can't be trusted for consistence interaction with their environment, attract the attention of scientists and health care providers. Existing provisions are often deemed inadequate; e.g.; current UK housing services for the older people are inadequate for an aging population both in terms of quality and quantity. Many older people prefer to spend their remaining life in their home environment; over 40% of the older people have concerns about having to move into a care home when they become old and nearly 70% of them worry about losing their independence or becoming dependent on others. There is, therefore, a growing interest in the design and implementation of smart and intelligent Ambient Assisted Living (AAL) systems that can provide everyday support to enable the older people to live independently in their homes. Moreover, such systems will reduce the cost of health care that governments have to tackle in providing assistance for this category of citizens. It also relieves relatives from continuous and often tedious supervision of these people around the clock, so that their life and commitments are not severely affected. Hence, recognition, categorization, and decision-making for such peoples’ everyday life activities is very important to the design of proper and effective intelligent support systems that are able to provide the necessary help for them in the right manner and time. Consequently, the collection of monitoring data for such people around the clock to record their vital signs, environmental conditions, health condition, and activities is the entry level to design such systems. This study aims to capture everyday activities using ambient sensory II information and proposes an intelligent decision support system for older people living with Alzheimer’s through conducting field study research in the Kingdom of Saudi Arabia within their homes and health care centres. The study considers the older people, who live with Alzheimer’s in Kingdom of Saudi Arabia. Since Alzheimer’s is a special form of dementia that can be supported in early stages with the ambient assistive systems. Further, the results of the field study can also be generalized to societies, which are interested in the mental and cognitive behaviour of older people. This generalization is related to the existence of common similarities in their daily life. Moreover, the approach is a generalized approach. Hence it can also be utilized on a new society which is conducting the same field study. This study initially presents a real-life observation process to identify the most common activities for these patients’ group. Then, a survey analysis is carried out to identify the daily life activities based on the observation. The survey analysis is accomplished using a U-test (Mann-Whitney). According to the analysis, it has been found that these people have fourteen common activities. However, three of these activities such as sleeping, walking (standing) and sitting cover about 72% of overall activities. Therefore, this study focuses on the recognition of these three common activities to demonstrate the effectiveness of the research. The activity recognition is carried out using a common image processing technique, called Phase-Correlation and Log-Polar (PCLP) transformation. According to results, the techniques predicted human activities of about 43.7%. However, this ratio is low to utilise for further analysis. Therefore, an Artificial Neural Network (ANN)- based PCLP model is developed to increase the accuracy of activity recognition. The enhanced PCLP transformation method can predict nearly 80% of the evaluated activities. Moreover, this study also presents a decision support system for Alzheimer’s people, which will provide these people with a safe environment. The decision support system utilises an extended sensory-based system, including a vision sensor, vital signs sensor and environmental sensor with expert rules. The proposed system was implemented on an older people patient with 87.2% accuracy