Fall prevention intervention technologies: A conceptual framework and survey of the state of the art

In recent years, an ever increasing range of technology-based applications have been developed with the goal of assisting in the delivery of more effective and efficient fall prevention interventions. Whilst there have been a number of studies that have surveyed technologies for a particular sub-domain of fall prevention, there is no existing research which surveys the full spectrum of falls prevention interventions and characterises the range of technologies that have augmented this landscape. This study presents a conceptual framework and survey of the state of the art of technology-based fall prevention systems which is derived from a systematic template analysis of studies presented in contemporary research literature. The framework proposes four broad categories of fall prevention intervention system: Pre-fall prevention; Post-fall prevention; Fall injury prevention; Cross-fall prevention. Other categories include, Application type, Technology deployment platform, Information sources, Deployment environment, User interface type, and Collaborative function. After presenting the conceptual framework, a detailed survey of the state of the art is presented as a function of the proposed framework. A number of research challenges emerge as a result of surveying the research literature, which include a need for: new systems that focus on overcoming extrinsic falls risk factors; systems that support the environmental risk assessment process; systems that enable patients and practitioners to develop more collaborative relationships and engage in shared decision making during falls risk assessment and prevention activities. In response to these challenges, recommendations and future research directions are proposed to overcome each respective challenge.The Royal Society, grant Ref: RG13082

Fog Computing in Medical Internet-of-Things: Architecture, Implementation, and Applications

In the era when the market segment of Internet of Things (IoT) tops the chart in various business reports, it is apparently envisioned that the field of medicine expects to gain a large benefit from the explosion of wearables and internet-connected sensors that surround us to acquire and communicate unprecedented data on symptoms, medication, food intake, and daily-life activities impacting one's health and wellness. However, IoT-driven healthcare would have to overcome many barriers, such as: 1) There is an increasing demand for data storage on cloud servers where the analysis of the medical big data becomes increasingly complex, 2) The data, when communicated, are vulnerable to security and privacy issues, 3) The communication of the continuously collected data is not only costly but also energy hungry, 4) Operating and maintaining the sensors directly from the cloud servers are non-trial tasks. This book chapter defined Fog Computing in the context of medical IoT. Conceptually, Fog Computing is a service-oriented intermediate layer in IoT, providing the interfaces between the sensors and cloud servers for facilitating connectivity, data transfer, and queryable local database. The centerpiece of Fog computing is a low-power, intelligent, wireless, embedded computing node that carries out signal conditioning and data analytics on raw data collected from wearables or other medical sensors and offers efficient means to serve telehealth interventions. We implemented and tested an fog computing system using the Intel Edison and Raspberry Pi that allows acquisition, computing, storage and communication of the various medical data such as pathological speech data of individuals with speech disorders, Phonocardiogram (PCG) signal for heart rate estimation, and Electrocardiogram (ECG)-based Q, R, S detection.Comment: 29 pages, 30 figures, 5 tables. Keywords: Big Data, Body Area Network, Body Sensor Network, Edge Computing, Fog Computing, Medical Cyberphysical Systems, Medical Internet-of-Things, Telecare, Tele-treatment, Wearable Devices, Chapter in Handbook of Large-Scale Distributed Computing in Smart Healthcare (2017), Springe

Smartphones

Many of the research approaches to smartphones actually regard them as more or less transparent points of access to other kinds of communication experiences. That is, rather than considering the smartphone as something in itself, the researchers look at how individuals use the smartphone for their communicative purposes, whether these be talking, surfing the web, using on-line data access for off-site data sources, downloading or uploading materials, or any kind of interaction with social media. They focus not so much on the smartphone itself but on the activities that people engage in with their smartphones

New Frontiers of Quantified Self 3: Exploring Understudied Categories of Users

Quantified Self (QS) field needs to start thinking of how situated needs may affect the use of self-tracking technologies. In this workshop we will focus on the idiosyncrasies of specific categories of users

In the palm of your hand: supporting rural teacher professional development and practice through the use of mobile phones and other handheld digital devices

Given the huge growth of mobile phone access in Sub Saharan Africa (Minges, 2004) some of the most innovative uses of mobile devices are now to be found in the development context (Economist, 2005). Reviews of the use of mobile technologies point to a range of current and potential development for learning in classrooms, homes and the community (e.g. Naismith et al). This paper draws on the experience of two projects: a large scale project for SMS mediated school administration in Kenya and a small scale research project using eBooks and other digital tools for teacher professional development and practice, carried out in predominantly rural schools in the Eastern Cape, South Africa. This research is set in the wider context of the emerging theory, practice and evaluation of the use of mobile technologies for improving teaching and learning (Leach 2006, Power & Thomas 2006, Traxler & Kukulska-Hulme 2006). The paper considers the potential of currently common mobile phones to aid communication and break down isolation amongst rural teachers and the design, use and evaluation of e-book learning resources on handheld mobile devices, such as current ‘smart-phones’, which the authors anticipate will soon be the ‘normal’ ubiquitous mobile phone. Whilst there is only a small body of evidence on the application of mobile technologies to teacher learning, impacts on teacher development remain a matter for debate. Findings suggest that given the right conditions, uses of mobile technology can significantly enhance teacher professional learning and practice

A Smartphone-Based Tool for Rapid, Portable, and Automated Wide-Field Retinal Imaging.

Purpose:High-quality, wide-field retinal imaging is a valuable method for screening preventable, vision-threatening diseases of the retina. Smartphone-based retinal cameras hold promise for increasing access to retinal imaging, but variable image quality and restricted field of view can limit their utility. We developed and clinically tested a smartphone-based system that addresses these challenges with automation-assisted imaging. Methods:The system was designed to improve smartphone retinal imaging by combining automated fixation guidance, photomontage, and multicolored illumination with optimized optics, user-tested ergonomics, and touch-screen interface. System performance was evaluated from images of ophthalmic patients taken by nonophthalmic personnel. Two masked ophthalmologists evaluated images for abnormalities and disease severity. Results:The system automatically generated 100° retinal photomontages from five overlapping images in under 1 minute at full resolution (52.3 pixels per retinal degree) fully on-phone, revealing numerous retinal abnormalities. Feasibility of the system for diabetic retinopathy (DR) screening using the retinal photomontages was performed in 71 diabetics by masked graders. DR grade matched perfectly with dilated clinical examination in 55.1% of eyes and within 1 severity level for 85.2% of eyes. For referral-warranted DR, average sensitivity was 93.3% and specificity 56.8%. Conclusions:Automation-assisted imaging produced high-quality, wide-field retinal images that demonstrate the potential of smartphone-based retinal cameras to be used for retinal disease screening. Translational Relevance:Enhancement of smartphone-based retinal imaging through automation and software intelligence holds great promise for increasing the accessibility of retinal screening

Attitudes towards the use and acceptance of eHealth technologies : a case study of older adults living with chronic pain and implications for rural healthcare

Acknowledgements The research described here is supported by the award made by the RCUK Digital Economy programme to the dot.rural Digital Economy Hub; award reference: EP/G066051/1. MC’s time writing the paper is funded by the Scottish Government’s Rural and Environmental Science and Analytical Services Division (RESAS) under Theme 8 ‘Vibrant Rural Communities’ of the Food, Land and People Programme (2011–2016). MC is also an Honorary Research Fellow at the Division of Applied Health Sciences, University of Aberdeen. The input of other members of the TOPS research team, Alastair Mort, Fiona Williams, Sophie Corbett, Phil Wilson and Paul MacNamee who contributed to be wider study and discussed preliminary findings reported here with the authors of the paper is acknowledged. We acknowledge the feedback on earlier versions of this paper provided by members of the Trans-Atlantic Rural Research Network, especially Stefanie Doebler and Carmen Hubbard. We also thank Deb Roberts for her comments.Peer reviewedPublisher PD