Co-creating connected and intelligent care homes for people with dementia

Connected Care aims to address three main challenges that care homes face with regards to people living with dementia 1. Care homes are increasingly challenged by a rising number of people living with dementia and a simultaneous demand to improve quality of care amidst limited funding and staff shortages. 2. Although innovation is associated with better quality of care, there is limited research looking into the ways in which digital technology, including the Internet of Things and sensors, could help care homes deliver better care for people with dementia. 3. Scholarly research has highlighted that top-down implementations of technology fail to deliver their potential benefits when there is limited user buy-in. In the context of care homes, care workers, residents and their families are often under-represented in technological developments

Multimodal Wearable Intelligence for Dementia Care in Healthcare 4.0: A Survey

As a new revolution of Ubiquitous Computing and Internet of Things, multimodal wearable intelligence technique is rapidly becoming a new research topic in both academic and industrial fields. Owning to the rapid spread of wearable and mobile devices, this technique is evolving healthcare from traditional hub-based systems to more personalised healthcare systems. This trend is well-aligned with recent Healthcare 4.0 which is a continuous process of transforming the entire healthcare value chain to be preventive, precise, predictive and personalised, with significant benefits to elder care. But empowering the utility of multimodal wearable intelligence technique for elderly care like people with dementia is significantly challenging considering many issues, such as shortage of cost-effective wearable sensors, heterogeneity of wearable devices connected, high demand for interoperability, etc. Focusing on these challenges, this paper gives a systematic review of advanced multimodal wearable intelligence technologies for dementia care in Healthcare 4.0. One framework is proposed for reviewing the current research of wearable intelligence, and key enabling technologies, major applications, and successful case studies in dementia care, and finally points out future research trends and challenges in Healthcare 4.0

A Novel IoT Based Positioning and Shadowing System for Dementia Training.

A rapid increase in the number of patients with dementia, particularly memory decline or impairment, has led to the loss of self-care ability in more individuals and increases in medical and social costs. Numerous studies, and clinical service experience, have revealed that the intervention of nonpharmacological management for people with dementia is effective in delaying the degeneration caused by dementia. Due to recent rapid developments in information and communications technology, many innovative research and development and cross-domain applications have been effectively used in the dementia care environment. This study proposed a new short-term memory support and cognitive training application technology, a "positioning and shadowing system," to delay short-term memory degeneration in dementia. Training courses that integrate physical and digital technologies for the indoor location of patients with dementia were constructed using technologies such as Bluetooth Low Energy, fingerprint location algorithm, and short-range wireless communication. The Internet of Things was effectively applied to a clinical training environment for short-term memory. A pilot test verified that the results demonstrated learning effects in cognitive training and that the system can assist medical personnel in training and nursing work. Participants responded with favorable feedback regarding course satisfaction and system usability. This study can be used as a reference for future digital smart cognitive training that allows observation of the performance of patients with dementia in activities of daily living

Awareness, requirements and barriers to use of Assistive Technology designed to enable independence of people suffering from Dementia (ATD)

This article is available through the Brunel Open Access Publishing Fund. Copyright @ 2012 IOS PressThis study investigated the awareness and use of assistive technology for people with dementia. The aim of the study was to explore barriers to the uptake of, and the unmet needs for, assistive technology for dementia (ATD) The work was carried out with family carers of people with dementia because carers are often the purchasers, end users and main beneficiaries of this type of technology. Focus groups were used to explore carers’ views on ATD use, and the problems that might be addressed by ATD, in order to develop a questionnaire for dementia carers. The questionnaire was administered at Alzheimer’s Society carer support groups in South Bucks and in Hillingdon Borough (UK). None of the 16 focus group participants or the 42 respondents to the questionnaire had any personal experience of ATD. The dementia carers reported a number of concerns, problems and unmet needs that could be addressed by existing, commercially available ATD products. Some needs for new technology development were identified in the study, but the lack of awareness of ATD appears to be the most important barrier to technology adoption

Medical data processing and analysis for remote health and activities monitoring

Recent developments in sensor technology, wearable computing, Internet of Things (IoT), and wireless communication have given rise to research in ubiquitous healthcare and remote monitoring of human\u2019s health and activities. Health monitoring systems involve processing and analysis of data retrieved from smartphones, smart watches, smart bracelets, as well as various sensors and wearable devices. Such systems enable continuous monitoring of patients psychological and health conditions by sensing and transmitting measurements such as heart rate, electrocardiogram, body temperature, respiratory rate, chest sounds, or blood pressure. Pervasive healthcare, as a relevant application domain in this context, aims at revolutionizing the delivery of medical services through a medical assistive environment and facilitates the independent living of patients. In this chapter, we discuss (1) data collection, fusion, ownership and privacy issues; (2) models, technologies and solutions for medical data processing and analysis; (3) big medical data analytics for remote health monitoring; (4) research challenges and opportunities in medical data analytics; (5) examples of case studies and practical solutions

Machine learning methods for detecting urinary tract infection and analysing daily living activities in people with dementia

Dementia is a neurological and cognitive condition that affects millions of people around the world. At any given time in the United Kingdom, 1 in 4 hospital beds are occupied by a person with dementia, while about 22% of these hospital admissions are due to preventable causes. In this paper we discuss using Internet of Things (IoT) technologies and in-home sensory devices in combination with machine learning techniques to monitor health and well-being of people with dementia. This will allow us to provide more effective and preventative care and reduce preventable hospital admissions. One of the unique aspects of this work is combining environmental data with physiological data collected via low cost in-home sensory devices to extract actionable information regarding the health and well-being of people with dementia in their own home environment. We have worked with clinicians to design our machine learning algorithms where we focused on developing solutions for real-world settings. In our solutions, we avoid generating too many alerts/alarms to prevent increasing the monitoring and support workload. We have designed an algorithm to detect Urinary Tract Infections (UTI) which is one of the top five reasons of hospital admissions for people with dementia (around 9% of hospital admissions for people with dementia in the UK). To develop the UTI detection algorithm, we have used a Non-negative Matrix Factorisation (NMF) technique to extract latent factors from raw observation and use them for clustering and identifying the possible UTI cases. In addition, we have designed an algorithm for detecting changes in activity patterns to identify early symptoms of cognitive decline or health decline in order to provide personalised and preventative care services. For this purpose, we have used an Isolation Forest (iForest) technique to create a holistic view of the daily activity patterns. This paper describes the algorithms and discusses the evaluation of the work using a large set of real-world data collected from a trial with people with dementia and their caregivers

The impact of information and communication technology on family carers of older people and professionals in Sweden

Government policy in Sweden, as in other developed countries, pays increasing attention as to how best to support the family carers of older people. New and innovative means of support, such as information and communication technology, are emerging. This paper explores the perceived benefits of, and barriers to, information technology as a means of supporting family carers of older people. Following a brief overview of the care-giving literature, with particular reference to the Swedish context, interview and questionnaire data collected from 34 families who took part in the Swedish ACTION project are used to explore the role of user-friendly information and communication technology to inform and enable family carers of older people to exercise choice, to care more effectively and to work in partnership with professionals. Interview data from two groups of professionals that utilised ACTION are also examined to throw light on its potential benefits for both carers and professionals. Consideration is given to the barriers to using information technology, and to identifying those carers most likely to benefit. Areas for further development are the need for practitioners' education and a wider range of programmes to address carers' diverse needs. Clearly, lessons learned from the Swedish project have wider relevance, given that new forms of support are being developed in most technically advanced countries

Enriched elderly virtual profiles by means of a multidimensional integrated assessment platform

The pressure over Healthcare systems is increasing in most developed countries. The generalized aging of the population is one of the main causes. This situation is even worse in underdeveloped, sparsely populated regions like Extremadura in Spain or Alentejo in Portugal. The authors propose to use the Situational-Context, a technique to seamlessly adapt Internet of Things systems to the needs and preferences of their users, for virtually modeling the elderly. These models could be used to enhance the elderly experience when using those kind of systems without raising the need for technical skills or the costs of implementing such systems by the regional healthcare systems. In this paper, the integration of a multidimensional integrated assessment platform with such virtual profiles is presented. The assessment platform provides and additional source of information for the virtual profiles that is used to better adapt existing systems to the elders needs