Wireless sensor networks are becoming popular in the field of ambient assisted living. In this paper we report our study on the relationship between a functional health metric and features derived from the sensor data. Sensor systems are installed in the houses of nine people who are also quarterly visited by an occupational therapist for functional health assessments. Different features are extracted and these are correlated with a metric of functional health (the AMPS). Though the sample is small, the results indicate that some features are better in describing the functional health in the population, but individual differences should also be taken into account when developing a sensor system for functional health assessment.
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This paper describes a participatory design-oriented study of an ambient assisted living system for monitoring the daily activities of elderly residents. The work presented addresses these questions 1) What daily activities the elderly participants like to be monitored, 2) With whom they would want to share this monitored data and 3) How a monitoring system for the elderly should be designed. For this purpose, this paper discusses the study results and participatory design techniques used to exemplify and understand desired ambient-assisted living scenarios and information sharing needs. Particularly, an interactive dollhouse is presented as a method for including the elderly in the design and requirements gathering process for residential monitoring. The study results indicate the importance of exemplifying ambient-assisted living scenarios to involve the elderly and so to increase acceptance and utility of such systems. The preliminary studies presented show that the participants were willing to have most of their daily activities monitored. However, they mostly wanted to keep control over their own data and share this information with medical specialists and particularly not with their fellow elderly neighbours.
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Ambient monitoring systems offer great possibilities for health trend analysis in addition to anomaly detection. Health trend analysis helps care professionals to evaluate someones functional health and direct or evaluate the choice of interventions. This paper presents one case study of a person that was followed with an ambient monitoring system for almost three years and another of a person that was followed for over a year. A simple algorithm is applied to make a location based data representation. This data is visualized for care professionals, and used for inspecting the regularity of the pattern with means of principal component analysis (PCA). This paper provides a set of tools for analyzing longitudinal behavioral data for health assessments. We advocate a standardized data collection procedure, particularly the health metrics that could be used to validate health focused sensor data analyses.
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As interactive systems become increasingly complex and entwined with the environment, technology is becoming more and more invisible. This means that much of the technology that people come across every day goes unnoticed and that the (potential) workings of ambient systems are not always clearly communicated to the user. The projects discussed in this paper are aimed at increasing public understanding of the existence, workings and potential of screens and ambient technology by visualizing its potential. To address issues and implications of visibility and system transparency, this paper presents work in progress as example cases for engaging people in ambient monitoring and public screening. This includes exploring desired scenarios for ambient monitoring with users as diverse as elderly people or tourists and an interactive tool for mapping public screens.
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Purpose Building services technologies such as home automation systems and remote monitoring are increasingly used to support people in their own homes. In order for these technologies to be fully appreciated by the endusers (mainly older care recipients, informal carers and care professionals), user needs should be understood1,2. In other words, supply and demand should match. Steele et al.3 state that there is a shortage of studies exploring perceptions of older users towards technology and the acceptance or rejection thereof. This paper presents an overview of user needs in relation to ambient assisted living (AAL) projects, which aim to support ageing-in-place in The Netherlands. Method A literature survey was made of Dutch AAL projects, focusing on user needs. A total of 7 projects concerned with older persons, with and without dementia, were included in the overview. Results & Discussion By and large technology is considered to be a great support in enabling people to age-in-place. Technology is, therefore, accepted and even embraced by many of the end-users and their relatives. Technology used for safety, security, and emergency response is most valued. Involvement of end-users improves the successful implementation of ambient technology. This is also true for family involvement in the case of persons with dementia. Privacy is mainly a concern for care professionals. This group is also key to successful implementation, as they need to be able to work with the technology and provide information to the end-users. Ambient technologies should be designed in an unobtrusive way, in keeping with indoor design, and be usable by persons with sensory of physical impairments. In general, user needs, particularly the needs of informal carers and care professionals, are an understudied topic. These latter two groups play an important role in implementation and acceptance among care recipients. They should, therefore, deserve more attention from the research community.
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Ambient intelligence technologies are a means to support ageing-in-place by monitoring clients in the home. In this study, monitoring is applied for the purpose of raising an alarm in an emergency situation, and thereby, providing an increased sense of safety and security. Apart from these technological solutions, there are numerous environmental interventions in the home environment that can support people to age-in-place. The aim of this study was to investigate the needs and motives, related to ageing-in-place, of the respondents receiving ambient intelligence technologies, and to investigate whether, and how, these technologies contributed to aspects of ageing-in-place. This paper presents the results of a qualitative study comprised of interviews and observations of technology and environmental interventions in the home environment among 18 community-dwelling older adults with a complex demand for care.
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This paper describes the approach used to identify elderly people’s needs and attitudes towards applying ambient sensor systems for monitoring daily activities in the home. As elderly are typically unfamiliar with such ambient technology, interactive tools for explicating sensor monitoring –an interactive dollhouse and iPad applications for displaying live monitored sensor activity data– were developed and used for this study. Furthermore, four studies conducted by occupational therapists with more than 60 elderly participants –including questionnaires (n=41), interviews (n=6), user sessions (n=14) and field studies (n=2)– were conducted. The experiences from these studies suggest that this approach helped to democratically engage the elderly as end-user and identify acceptance issues.
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The project discussed in this paper is aimed at increasing people’s understanding of the existence and desired workings of ambient technology in the home by demonstrating its potential. For this purpose, an interactive dollhouse is presented. The dollhouse, a miniature model of a sensor-equipped home, was developed and used to engage elderly users in the design of an ambient monitoring system. This paper explains the design of the interactive dollhouse and the ways it was used as an elderly-centered design method for increasing understanding of the desired workings of ambient monitoring in the home.
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Ambient activity monitoring systems produce large amounts of data, which can be used for health monitoring. The problem is that patterns in this data reflecting health status are not identified yet. In this paper the possibility is explored of predicting the functional health status (the motor score of AMPS = Assessment of Motor and Process Skills) of a person from data of binary ambient sensors. Data is collected of five independently living elderly people. Based on expert knowledge, features are extracted from the sensor data and several subsets are selected. We use standard linear regression and Gaussian processes for mapping the features to the functional status and predict the status of a test person using a leave-oneperson-out cross validation. The results show that Gaussian processes perform better than the linear regression model, and that both models perform better with the basic feature set than with location or transition based features. Some suggestions are provided for better feature extraction and selection for the purpose of health monitoring. These results indicate that automated functional health assessment is possible, but some challenges lie ahead. The most important challenge is eliciting expert knowledge and translating that into quantifiable features.
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Technology has a major impact on the way nurses work. Data-driven technologies, such as artificial intelligence (AI), have particularly strong potential to support nurses in their work. However, their use also introduces ambiguities. An example of such a technology is AI-driven lifestyle monitoring in long-term care for older adults, based on data collected from ambient sensors in an older adult’s home. Designing and implementing this technology in such an intimate setting requires collaboration with nurses experienced in long-term and older adult care. This viewpoint paper emphasizes the need to incorporate nurses and the nursing perspective into every stage of designing, using, and implementing AI-driven lifestyle monitoring in long-term care settings. It is argued that the technology will not replace nurses, but rather act as a new digital colleague, complementing the humane qualities of nurses and seamlessly integrating into nursing workflows. Several advantages of such a collaboration between nurses and technology are highlighted, as are potential risks such as decreased patient empowerment, depersonalization, lack of transparency, and loss of human contact. Finally, practical suggestions are offered to move forward with integrating the digital colleague
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