The « Intelligent Wardrobe »

In an ageing society technical systems that support the residents at home are becoming increasingly important. Many of the technologies available today focus on detecting falls or monitoring the health of residents. There are a few projects that focus the « smart home for the elderly » and offer support for the daily activities. The Institute of Medical Informatics of the Bern University of Applied Sciences has developed a prototype of an intelligent wardrobe. Based on sensor data from the apartment like inside temperature, weather forecast and todays events suggestions for appropriate clothes are generated and shown on a display. To facilitate the search, the garments are marked in the closet with colored LEDs

A Tailored Smart Home for Dementia Care

Dementia refers to a group of chronic conditions that cause the permanent and gradual cognitive decline. Therefore, a Person with Dementia (PwD) requires constant care from various classes of caregivers. The care costs of PwDs bear a tremendous burden on healthcare systems around the world. It is commonly accepted that utilising Smart Homes (SH), as an instance of Ambient Assisted Living (AAL) technologies, can facilitate the care, and consequently improve the quality of PwDs well-being. Nevertheless, most of the existing platforms assume dementia care is a straight application of standard SH technology without accommodating the specific requirements of dementia care. A consequence of this approach is the inadequacy and unacceptability of generic SH systems in the context of dementia care. Contrary to most of the existing SH systems proposed for dementia care, this study considers the specific requirements of PwDs and their care circle in all development steps of an SH. In addition, it investigates how utilising novel design and computing approaches can enhance the quality of SHs for dementia care. To do so, the requirements of dementia care stakeholders are collected, analysed and reflected on in an SH system design. Extensions and adaptation of existing frameworks and technologies are proposed to implement a prototype based on the resulting design. Finally, thorough evaluations and validation of the prototype are carried out. The evaluations by a group of stakeholders show the suitability of the proposed methodology and consequently the resulting prototypes for reducing dementia care difficulties as well as its potential for deployment in the real-world environment

AnAbEL: Towards empowering people living with dementia in ambient assisted living

Ambient assisted living aims to support the well-being of people with special needs by offering assistive solutions. Systems focused on dementia increase the autonomy of people living with dementia by monitoring their activities. Topics such as activity recognition and specific solutions such as reminders and tracking users by Global Positioning System offer great advances in user safety and help them preserve a healthier lifestyle. However, these solutions are often addressed to secondary parties, providing them activity logs or alerts, but excluding the main user, the person living with dementia. Although the primary users are taken into consideration at some design stages using user-centred design frameworks, the final products tend to not fully address user needs. This paper presents an ambient intelligent system aimed at reducing this limitation by providing reminders and advice to the person living with dementia in the first instance. The system still involves caregivers if unusual or unhealthy behaviour continues. The solution is deployed in order to be validated by professionals from London city boroughs who work in housing and dementia related services, with an emphasis on enhancing healthy lifestyles by empowering the user in the early stages of dementia with autonomy. Through continued activity monitoring in real-time, the system can provide reminders and warnings to users to keep healthy routines. Continuous monitoring provides user behaviour tracking, and the context-aware logic used involves caregivers through alerts when necessary to ensure user safety. This article describes the process followed in developing the system, and covers previous concerns and practical feedback from health professionals over the deployment of the system in a real environment. Our approach also includes a novelty indoor localization system to distinguish users and allows a more specific delivery of services in multi-occupancy scenarios

Intelligent sensing technologies for the diagnosis, monitoring and therapy of alzheimer’s disease:A systematic review

Alzheimer’s disease is a lifelong progressive neurological disorder. It is associated with high disease management and caregiver costs. Intelligent sensing systems have the capability to provide context-aware adaptive feedback. These can assist Alzheimer’s patients with, continuous monitoring, functional support and timely therapeutic interventions for whom these are of paramount importance. This review aims to present a summary of such systems reported in the extant literature for the management of Alzheimer’s disease. Four databases were searched, and 253 English language articles were identified published between the years 2015 to 2020. Through a series of filtering mechanisms, 20 articles were found suitable to be included in this review. This study gives an overview of the depth and breadth of the efficacy as well as the limitations of these intelligent systems proposed for Alzheimer’s. Results indicate two broad categories of intelligent technologies, distributed systems and self-contained devices. Distributed systems base their outcomes mostly on long-term monitoring activity patterns of individuals whereas handheld devices give quick assessments through touch, vision and voice. The review concludes by discussing the potential of these intelligent technologies for clinical practice while highlighting future considerations for improvements in the design of these solutions for Alzheimer’s disease

Night optimised care technology for users needing assisted lifestyles

There is growing interest in the development of ambient assisted living services to increase the quality of life of the increasing proportion of the older population. We report on the Night Optimised Care Technology for UseRs Needing Assisted Lifestyles project, which provides specialised night time support to people at early stages of dementia. This article explains the technical infrastructure, the intelligent software behind the decision-making driving the system, the software development process followed, the interfaces used to interact with the user, and the findings and lessons of our user-centred approach

Night optimised care technology for users needing assisted lifestyles

There is growing interest in the development of ambient assisted living services to increase the quality of life of the increasing proportion of the older population. We report on the Night Optimised Care Technology for UseRs Needing Assisted Lifestyles project, which provides specialised night time support to people at early stages of dementia. This article explains the technical infrastructure, the intelligent software behind the decision-making driving the system, the software development process followed, the interfaces used to interact with the user, and the findings and lessons of our user-centred approach

MAISON -- Multimodal AI-based Sensor platform for Older Individuals

There is a global aging population requiring the need for the right tools that can enable older adults' greater independence and the ability to age at home, as well as assist healthcare workers. It is feasible to achieve this objective by building predictive models that assist healthcare workers in monitoring and analyzing older adults' behavioral, functional, and psychological data. To develop such models, a large amount of multimodal sensor data is typically required. In this paper, we propose MAISON, a scalable cloud-based platform of commercially available smart devices capable of collecting desired multimodal sensor data from older adults and patients living in their own homes. The MAISON platform is novel due to its ability to collect a greater variety of data modalities than the existing platforms, as well as its new features that result in seamless data collection and ease of use for older adults who may not be digitally literate. We demonstrated the feasibility of the MAISON platform with two older adults discharged home from a large rehabilitation center. The results indicate that the MAISON platform was able to collect and store sensor data in a cloud without functional glitches or performance degradation. This paper will also discuss the challenges faced during the development of the platform and data collection in the homes of older adults. MAISON is a novel platform designed to collect multimodal data and facilitate the development of predictive models for detecting key health indicators, including social isolation, depression, and functional decline, and is feasible to use with older adults in the community

UnderstAID, an ICT platform to help informal caregivers of people with dementia: a pilot randomized controlled study

[Abstract] Information and communications technology (ICT) could support ambient assisted living (AAL) based interventions to provide support to informal caregivers of people with dementia, especially when they need to cope with their feelings of overburden or isolation. An e-learning platform (understAID application) was tested by informal caregivers from Denmark, Poland, and Spain to explore the technical and the pedagogical specifications, as well as evaluating the impact of its use on the psychological status of the participants. 61 informal caregivers completed the study taking part in the experimental (n=30) or control (n=31) groups. 33.3% of the caregivers were satisfied with the application and around 50% of the participants assessed it as technically and pedagogically acceptable. After using understAID the caregivers in the experimental group significantly decreased their depressive symptomatology according to the Center for Epidemiologic Studies Depression scale, but a possible benefit on their feelings of competence and satisfaction with the caring experience was also observed. The low scores obtained for satisfaction were highlighting issues that need to be modified to meet the informal caregivers’ needs in national, social, and cultural context. Some possible biases are also considered and discussed to be taken into account in future improvements of understAID application.European Commission; AAL-2012-5-10

Cognitive assisted living ambient system: a survey

The demographic change towards an aging population is creating a significant impact and introducing drastic challenges to our society. We therefore need to find ways to assist older people to stay independently and prevent social isolation of these population. Information and Communication Technologies (ICT) provide various solutions to help older adults to improve their quality of life, stay healthier, and live independently for a time. Ambient Assisted Living (AAL) is a field to investigate innovative technologies to provide assistance as well as healthcare and rehabilitation to impaired seniors. The paper provides a review of research background and technologies of AAL

A review of smart homes in healthcare

The technology of Smart Homes (SH), as an instance of ambient assisted living technologies, is designed to assist the homes’ residents accomplishing their daily-living activities and thus having a better quality of life while preserving their privacy. A SH system is usually equipped with a collection of inter-related software and hardware components to monitor the living space by capturing the behaviour of the resident and understanding his activities. By doing so the system can inform about risky situations and take actions on behalf of the resident to his satisfaction. The present survey will address technologies and analysis methods and bring examples of the state of the art research studies in order to provide background for the research community. In particular, the survey will expose infrastructure technologies such as sensors and communication platforms along with artificial intelligence techniques used for modeling and recognizing activities. A brief overview of approaches used to develop Human–Computer interfaces for SH systems is given. The survey also highlights the challenges and research trends in this area