M-health review: joining up healthcare in a wireless world

In recent years, there has been a huge increase in the use of information and communication technologies (ICT) to deliver health and social care. This trend is bound to continue as providers (whether public or private) strive to deliver better care to more people under conditions of severe budgetary constraint

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

Future bathroom: A study of user-centred design principles affecting usability, safety and satisfaction in bathrooms for people living with disabilities

Research and development work relating to assistive technology 2010-11 (Department of Health) Presented to Parliament pursuant to Section 22 of the Chronically Sick and Disabled Persons Act 197

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

State of the art on ethical, legal, and social issues linked to audio- and video-based AAL solutions - Uploaded on December 29, 2021

Ambient assisted living (AAL) technologies are increasingly presented and sold as essential smart additions to daily life and home environments that will radically transform the healthcare and wellness markets of the future. An ethical approach and a thorough understanding of all ethics in surveillance/monitoring architectures are therefore pressing. AAL poses many ethical challenges raising questions that will affect immediate acceptance and long-term usage. Furthermore, ethical issues emerge from social inequalities and their potential exacerbation by AAL, accentuating the existing access gap between high-income countries (HIC) and low and middle-income countries (LMIC). Legal aspects mainly refer to the adherence to existing legal frameworks and cover issues related to product safety, data protection, cybersecurity, intellectual property, and access to data by public, private, and government bodies. Successful privacy-friendly AAL applications are needed, as the pressure to bring Internet of Things (IoT) devices and ones equipped with artificial intelligence (AI) quickly to market cannot overlook the fact that the environments in which AAL will operate are mostly private (e.g., the home). The social issues focus on the impact of AAL technologies before and after their adoption. Future AAL technologies need to consider all aspects of equality such as gender, race, age and social disadvantages and avoid increasing loneliness and isolation among, e.g. older and frail people. Finally, the current power asymmetries between the target and general populations should not be underestimated nor should the discrepant needs and motivations of the target group and those developing and deploying AAL systems. Whilst AAL technologies provide promising solutions for the health and social care challenges, they are not exempt from ethical, legal and social issues (ELSI). A set of ELSI guidelines is needed to integrate these factors at the research and development stage

State of the art on ethical, legal, and social issues linked to audio- and videobased AAL solutions

Working Group 1. Social responsibility: Ethical, legal, social, data protection and privacy issuesAbstract Ambient assisted living (AAL) technologies are increasingly presented and sold as essential smart additions to daily life and home environments that will radically transform the healthcare and wellness markets of the future. An ethical approach and a thorough understanding of all ethics in surveillance/monitoring architectures are therefore pressing. AAL poses many ethical challenges raising questions that will affect immediate acceptance and long-term usage. Furthermore, ethical issues emerge from social inequalities and their potential exacerbation by AAL, accentuating the existing access gap between high-income countries (HIC) and low and middle-income countries (LMIC). Legal aspects mainly refer to the adherence to existing legal frameworks and cover issues related to product safety, data protection, cybersecurity, intellectual property, and access to data by public, private, and government bodies. Successful privacy-friendly AAL applications are needed, as the pressure to bring Internet of Things (IoT) devices and ones equipped with artificial intelligence (AI) quickly to market cannot overlook the fact that the environments in which AAL will operate are mostly private (e.g., the home). The social issues focus on the impact of AAL technologies before and after their adoption. Future AAL technologies need to consider all aspects of equality such as gender, race, age and social disadvantages and avoid increasing loneliness and isolation among, e.g. older and frail people. Finally, the current power asymmetries between the target and general populations should not be underestimated nor should the discrepant needs and motivations of the target group and those developing and deploying AAL systems. Whilst AAL technologies provide promising solutions for the health and social care challenges, they are not exempt from ethical, legal and social issues (ELSI). A set of ELSI guidelines is needed to integrate these factors at the research and development stage. Keywords Ethical principles, Privacy, Assistive Living Technologies, Privacy by Design, General Data Protection Regulation.publishedVersio

Place Experience of Nursing Home Courtyards: a Holistic Approach to Understanding Institutional Outdoor Environments

This dissertation research investigates place experience of three nursing home courtyards. Based on systemic place theories, each nursing home courtyard is conceptualized as place or a system consisting of three major subsystems: physical settings, people and rules of place uses. Place experience as the center of conceptualization is the result of interactions between them. Place experience is thus characterized by objective, subjective and consensual qualities of people-environment relationships. The research design follows the premises of pragmatic case study methodology; a mixed research method is employed that includes archival research of floor plans, photo documentation, a physical setting checklist and instrumented measures for physical environments; staff interviews, surveys and auditing evaluations for organizational and staff contexts; and resident interviews and behavior mapping for individual contexts and place rules. Through synthesizing different sources of data into experiential descriptions, this study suggests that each courtyard is a compound of nine desired experiential attributes including 1) privacy, 2) social interactions, 3) accessible space and built features, 4) safety & security, 5) sensory stimulation, 6) information awareness and spatial orientation, 7) familiarity, 8) sense of ownership and 9) participation in meaningful activities. Each courtyard is unique in its distinct composition of these attributes and arrangements of the three subsystems. Experience of social interactions is the shared experiential quality across the cases. The three courtyards are programmed as a social space but are not meant to be a place to mark ownership, show identities and create meaningful engagement. The shared nature is incongruent with residents’ experience of home gardens and gardening collected from the interviews. A relatively successful case is selected; it is a place with more equal emphases on the nine attributes. Its patterns of the three subsystems may guide a less effective case to make future improvement. Implications of the findings are considered at three levels. First, this study applied a pragmatic approach, which offers a means to generate a holistic understanding of institutional outdoor environments; this study may complement the current research dominated by a positivist approach. Second, the approach recognizes and acknowledges the multifaceted phenomenon of the courtyards; it describes sets of variables or quality indicators that may help further theoretical construction or the development of quality measure. Third, this comparative research highlights the importance of establishing a database of cases reports. The accumulation of successful cases would help identify effective patterns of the three subsystems. Shared features emerging from successful cases may represent findings with high generalizability

Development and Evaluation of an Assistive Prompting System for People with Traumatic Brain Injury

Cognitive deficits in executive functioning are among the most frequent sequelae after traumatic brain injury (TBI) at all levels of severity. Due to these functional deficits in cognition, individuals with TBI often experience difficulties in performing instrumental activities of daily living (IADL), especially those IADLs that involve a sequence of goal-directed actions. We obtained updated information on the use of assistive technology for cognition (ATC) through a survey study among twenty-nine participants with TBI. Results highlighted the needs to support the development and evaluation of ATC in assisting multi-step tasks. Cooking tasks were selected as a representative for they are cognitively demanding and have been identified essential for living independently. With the recent advance in sensing and smart home technologies, it’s possible to provide context-aware prompts with minimal user inputs. However, limited information is known regarding what types of context-aware prompts are really needed by people with TBI in completing cooking tasks. We compared the effectiveness and usability of current available prompting methods (e.g. paper-based prompting method and user-controlled method) among ten individuals with TBI in their home kitchens. We categorized the nature of problems faced by end-users with both prompting methods in cooking tasks and proposed relevant context-aware solutions. A test-bed Cueing Kitchen with sensing and prompting elements was developed to address these identified needs and to evaluate the feasibility of context-aware ATC interventions in assisting people with TBI with kitchen activities. Sixteen individuals with TBI participated in the study. Results showed that comparing to the conventional user-controlled method, the automatic method decreased the amount of external assistance required by participants, received higher ratings in perceived ease-of-use, and was helpful for decreasing user stress levels. However, the user-controlled method showed strengths in offering participants more flexibility and control on the timing of prompts. The contributions from this dissertation not only developed a context-aware prompting testbed and evaluated the feasibility of an automatic system, but also advanced the guidelines and potential solutions for future development of assistive prompting technology for people with cognitive impairments in sequential tasks