Computing Technologies for Reflective and Creative Care for People with Dementia

Digital technologies have much to offer the care for people with dementia. However, their uptake so far has been slow. In this article, we report the introduction of sensor and mobile technologies and applications to support carers of people with dementia in residential homes to be more reflective and creative. Results revealed that carers can and want to use these technologies, but more effective app alignment with different dementia care strategies will be needed to achieve widespread technology take‐up

From Context to Content: Designing Sensor Support for Reflective Learning

This thesis examines how wearable sensor systems can support reflective learning by monitoring work experiences. A design space is defined that guides designers to build systems that can provide content for reflection. Wearable sensors and applications have been developed and evaluated to capture the affective and social context in workplace settings. It is a first step towards the generation of learning content from sensor data

Using mobile devices and apps to support reflective learning about older people with dementia

There has been little research to develop computing technologies to support the care of people with dementia, in spite of the growing challenges that the condition poses for society. To design such technologies, an existing model of computer-support reflective learning was instantiated with findings from a pre-design study in one residential home. The result was a mobile device running an adapted enterprise social media app to support person-centred care. Evaluations of the device and app in two residential homes revealed that use of the app both motivated and increased different styles of care note recording, but little reflective learning was identified or reported. The results suggest the need for more comprehensive and flexible computer-based support for reflective learning about residents in their care – and new designs of this more comprehensive support are also introduced

Context-awareness for mobile sensing: a survey and future directions

The evolution of smartphones together with increasing computational power have empowered developers to create innovative context-aware applications for recognizing user related social and cognitive activities in any situation and at any location. The existence and awareness of the context provides the capability of being conscious of physical environments or situations around mobile device users. This allows network services to respond proactively and intelligently based on such awareness. The key idea behind context-aware applications is to encourage users to collect, analyze and share local sensory knowledge in the purpose for a large scale community use by creating a smart network. The desired network is capable of making autonomous logical decisions to actuate environmental objects, and also assist individuals. However, many open challenges remain, which are mostly arisen due to the middleware services provided in mobile devices have limited resources in terms of power, memory and bandwidth. Thus, it becomes critically important to study how the drawbacks can be elaborated and resolved, and at the same time better understand the opportunities for the research community to contribute to the context-awareness. To this end, this paper surveys the literature over the period of 1991-2014 from the emerging concepts to applications of context-awareness in mobile platforms by providing up-to-date research and future research directions. Moreover, it points out the challenges faced in this regard and enlighten them by proposing possible solutions

A Reference Software Architecture for Social Robots

Social Robotics poses tough challenges to software designers who are required to take care of difficult architectural drivers like acceptability, trust of robots as well as to guarantee that robots establish a personalised interaction with their users. Moreover, in this context recurrent software design issues such as ensuring interoperability, improving reusability and customizability of software components also arise. Designing and implementing social robotic software architectures is a time-intensive activity requiring multi-disciplinary expertise: this makes difficult to rapidly develop, customise, and personalise robotic solutions. These challenges may be mitigated at design time by choosing certain architectural styles, implementing specific architectural patterns and using particular technologies. Leveraging on our experience in the MARIO project, in this paper we propose a series of principles that social robots may benefit from. These principles lay also the foundations for the design of a reference software architecture for Social Robots. The ultimate goal of this work is to establish a common ground based on a reference software architecture to allow to easily reuse robotic software components in order to rapidly develop, implement, and personalise Social Robots

Exploring factors that impact the decision to use assistive telecare: perspectives of family care-givers of older people in the United Kingdom

In the United Kingdom (UK), an ageing population met with the reduction of social care funding has led to reduced support for older people marked with an increased demand on family care-givers. Assistive telecare (AT) devices are viewed as an innovative and effective way to support older people. However, there is limited research which has explored adoption of AT from the perspectives of family care-givers. In-depth, semi-structured interviews were conducted with 14 family care-givers of patients who used the Assistive Telehealth and Telecare service in Cambridgeshire, UK. Family care-givers were either the spouse (N = 8) or child of the patient (N = 6). The patients' age ranged from 75 to 98, and either received a telecare standalone device or connected service. Framework analysis was used to analyse the transcripts. This study revealed that family care-givers play a crucial role in supporting the patient's decision to adopt and engage with AT devices. Knowledge and awareness, perceived responsibility, usefulness and usability, alongside functionality of the equipment, were influential factors in the decision-making process. AT devices were viewed positively, considered easy to use, useful and functional, with reassurance of the patient's safety being a core reason for adoption. Efforts to increase adoption and engagement should adapt recruitment strategies and service pathways to support both the patient and their care-giver

Design of a Predictive Scheduling System to Improve Assisted Living Services for Elders

International audienceAs the number of older adults increases, and with it the demand for dedicated care, geriatric residences face a shortage of caregivers, who themselves experience work overload, stress and burden. We conducted a long-term field study in three geriatric residences to understand the work conditions of caregivers with the aim of developing technologies to assist them in their work and help them deal with their burden. From this study we obtained relevant requirements and insights of design that were used to design, implement and evaluate two prototypes for supporting caregivers' tasks (e.g. electronic recording and automatic notifications), in order to validate the feasibility of their implementation in-situ and the technical requirements. The evaluation in-situ of the prototypes was conducted for a period of four weeks. The results of the evaluation, together with the data collected from six months of use, motivated the design of a predictive schedule. Such design was iteratively improved and evaluated in participative sessions with caregivers. PRESENCE, the predictive schedule we propose, triggers real-time alerts of risky situations (e.g. falls, entering off-limits areas such as the infirmary or the kitchen) and, informs caregivers of routine tasks that need to be performed (e.g. medication administration, diaper change, etc.). Moreover, PRESENCE helps caregivers to record caring tasks (such as diaper changes or medication) and wellbeing assessments (such as the mood), which are difficult to automatize. This facilitates caregiver's shift handover, and can help to train new caregivers by suggesting routine tasks and by sending reminders and timely information about the residents. It can be seen as a tool to reduce the workload of caregivers and medical staff. Instead of trying to substitute the caregiver with an automatic caring system, as proposed by others, we propose the design of our predictive schedule system that blends caregiver's assessments and measurements from sensors. We show the feasibility of predicting caregiver's tasks and a formative evaluation with caregivers that provides preliminary evidence of its utility