14 research outputs found

    Detecting elderly behavior shift via smart devices and stigmergic receptive fields

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    Smart devices are increasingly used for health monitoring. We present a novel connectionist architecture to detect elderly behavior shift from data gathered by wearable or ambient sensing technology. Behavior shift is a pattern used in many applications: it may indicate initial signs of disease or deviations in performance. In the proposed architecture, the input samples are aggregated by functional structures called trails. The trailing process is inspired by stigmergy, an insects’ coordination mechanism, and is managed by computational units called Stigmergic Receptive Fields (SRFs), which provide a (dis-)similarity measure between sample streams. This paper presents the architectural view, and summarizes the achievements related to three application case studies, i.e., indoor mobility behavior, sleep behavior, and physical activity behavior

    Digital health technology: factors affecting implementation in nursing homes.

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    BACKGROUND: Digital health technology (DHT), which includes digital algorithms and digital records, is transforming the way healthcare services are delivered. In nursing homes, DHT can enhance communication and improve the identification of residents' health risks, but its implementation has so far been inconsistent. Therefore, the LAUNCH (Leadership of digitAl health technology Uptake among Nurses in Care Homes) study was undertaken to identify factors that may affect DHT implementation in these settings. AIM: To identify the factors that enable nurses to implement DHT in nursing homes and to co-design a nurse-led stepped process supporting the effective implementation of DHT innovations in nursing homes. METHOD: An appreciative inquiry methodology was used. A total of 20 interviews with managers, residents and relatives, and nurses from five nursing homes in England were undertaken. The interview questions focused on their understanding of DHT, their experiences of it, and its potential benefits in nursing homes. Data from the interviews were thematically analysed and the emerging themes were used to inform two co-creation workshops, during which participating nurses discussed a practical, evidence-based process for DHT implementation in nursing homes. FINDINGS: Three broad themes emerged from the interviews: improving communication; engaging with DHT and retaining humanised care; and introducing DHT and protecting data security. The co-creation workshop participants formulated the LAUNCH process model, a nurse-led, stepped approach supporting DHT implementation in nursing homes. CONCLUSION: The LAUNCH study identified factors enabling staff in nursing homes to introduce and sustain DHT innovations. Participating nurses co-created a three-step process for the effective implementation of DHT innovations in nursing homes, which have the potential to release staff time, improve quality of care, and have positive effects on staff recruitment and retention

    GreenMed: A sustainable physical activity tracking application

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    Evidence suggests that physical activity brings substantial health benefits while its absence causes several health issues. As people become more aware of negative health outcomes associated with physical inactivity, the shift from sedentary lifestyles to healthier ones occurs, and physical activity tracking apps may help in this regard. While mobile applications for tracking physical activity are abundant, most of of them fail to deliver evidence-based recommendations. This is a major drawback especially when these apps are designed to guide users towards healthy lifestyles. This paper presents a prototype application that could provide evidence-based recommendations about how much physical activity adults should do to stay healthy according to the user’s current activity level. A new visualisation approach which uses animal representations for activity levels is also introduced to enhance user experience, increase motivation and create a good base for further integration of gamification principles. Early testing showed that users found the prototype very useful and expressed great interest towards the animal representations

    I'll Be Back: On the Multiple Lives of Users of a Mobile Activity Tracking Application

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    Mobile health applications that track activities, such as exercise, sleep, and diet, are becoming widely used. While these activity tracking applications have the potential to improve our health, user engagement and retention are critical factors for their success. However, long-term user engagement patterns in real-world activity tracking applications are not yet well understood. Here we study user engagement patterns within a mobile physical activity tracking application consisting of 115 million logged activities taken by over a million users over 31 months. Specifically, we show that over 75% of users return and re-engage with the application after prolonged periods of inactivity, no matter the duration of the inactivity. We find a surprising result that the re-engagement usage patterns resemble those of the start of the initial engagement period, rather than being a simple continuation of the end of the initial engagement period. This evidence points to a conceptual model of multiple lives of user engagement, extending the prevalent single life view of user activity. We demonstrate that these multiple lives occur because the users have a variety of different primary intents or goals for using the app. We find evidence for users being more likely to stop using the app once they achieved their primary intent or goal (e.g., weight loss). However, these users might return once their original intent resurfaces (e.g., wanting to lose newly gained weight). Based on insights developed in this work, including a marker of improved primary intent performance, our prediction models achieve 71% ROC AUC. Overall, our research has implications for modeling user re-engagement in health activity tracking applications and has consequences for how notifications, recommendations as well as gamification can be used to increase engagement

    A Transparency Index Framework for AI in Education

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    Numerous AI ethics checklists and frameworks have been proposed focusing on different dimensions of ethical AI such as fairness, explainability, and safety. Yet, no such work has been done on developing transparent AI systems for real-world educational scenarios. This paper presents a Transparency Index framework that has been iteratively co-designed with different stakeholders of AI in education, including educators, ed-tech experts, and AI practitioners. We map the requirements of transparency for different categories of stakeholders of AI in education and demonstrate that transparency considerations are embedded in the entire AI development process from the data collection stage until the AI system is deployed in the real world and iteratively improved. We also demonstrate how transparency enables the implementation of other ethical AI dimensions in Education like interpretability, accountability, and safety. In conclusion, we discuss the directions for future research in this newly emerging field. The main contribution of this study is that it highlights the importance of transparency in developing AI-powered educational technologies and proposes an index framework for its conceptualization for AI in education

    Usability, Efficiency and Security of Personal Computing Technologies

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    New personal computing technologies such as smartphones and personal fitness trackers are widely integrated into user lifestyles. Users possess a wide range of skills, attributes and backgrounds. It is important to understand user technology practices to ensure that new designs are usable and productive. Conversely, it is important to leverage our understanding of user characteristics to optimize new technology efficiency and effectiveness. Our work initially focused on studying older users, and personal fitness tracker users. We applied the insights from these investigations to develop new techniques improving user security protections, computational efficiency, and also enhancing the user experience. We offer that by increasing the usability, efficiency and security of personal computing technology, users will enjoy greater privacy protections along with experiencing greater enjoyment of their personal computing devices. Our first project resulted in an improved authentication system for older users based on familiar facial images. Our investigation revealed that older users are often challenged by traditional text passwords, resulting in decreased technology use or less than optimal password practices. Our graphical password-based system relies on memorable images from the user\u27s personal past history. Our usability study demonstrated that this system was easy to use, enjoyable, and fast. We show that this technique is extendable to smartphones. Personal fitness trackers are very popular devices, often worn by users all day. Our personal fitness tracker investigation provides the first quantitative baseline of usage patterns with this device. By exploring public data, real-world user motivations, reliability concerns, activity levels, and fitness-related socialization patterns were discerned. This knowledge lends insight to active user practices. Personal user movement data is captured by sensors, then analyzed to provide benefits to the user. The dynamic time warping technique enables comparison of unequal data sequences, and sequences containing events at offset times. Existing techniques target short data sequences. Our Phase-aware Dynamic Time Warping algorithm focuses on a class of sinusoidal user movement patterns, resulting in improved efficiency over existing methods. Lastly, we address user data privacy concerns in an environment where user data is increasingly flowing to manufacturer remote cloud servers for analysis. Our secure computation technique protects the user\u27s privacy while data is in transit and while resident on cloud computing resources. Our technique also protects important data on cloud servers from exposure to individual users

    Smart technologies and beyond: exploring how a smart band can assist in monitoring children’s independent mobility & well-being

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    The problem which is being investigated through this thesis is not having a device(s) or method(s) which are appropriate for monitoring a child’s vital and tracking a child’s location. This aspect is being explored by other researchers which are yet to find a viable solution. This work focuses on providing a solution that would consider using the Internet of Things for measuring and improving children’s health. Additionally, the focus of this research is on the use of technology for health and the needs of parents who are concerned about their child’s physical health and well-being. This work also provides an insight into how technology is used during the pandemic. This thesis will be based on a mixture of quantitative and qualitative research, which will have been used to review the following areas covering key aspects and focuses of this study which are (i) Children’s Independent Mobility (ii) Physical activity for children (iii) Emotions of a child (iv) Smart Technologies and (v) Children’s smart wearables. This will allow a review of the problem in detail and how technology can help the health sector, especially for children. The deliverable of this study is to recommend a suitable smart band device that enables location tracking of the child, activity tracking as well as monitoring the health and wellbeing of the child. The research also includes an element of practical research in the form of (i) Surveys, the use of smart technology and a perspective on the solution from parents. (ii) Focus group, in the form of a survey allowing opinions and collection of information on the child and what the parents think of smart technology and how it could potentially help with their fears. (iii) Observation, which allows the collection of data from children who were given six activities to conduct while wearing the Fitbit Charge HR. The information gained from these elements will help provide guidelines for a proposed solution. In this thesis, there are three frameworks which are about (i) Research process for this study (ii) Key Performance Indicators (KPIs) which are findings from the literature review and (iii) Proposed framework for the solution, all three combined frameworks can help health professionals and many parents who want an efficient and reliable device, also deployment of technologies used in the health industry for children in support of independent mobility. Current frameworks have some considerations within the technology and medical field but were not up to date with the latest elements such as parents fears within today’s world and the advanced features of technology
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