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

Fall Prediction and Prevention Systems: Recent Trends, Challenges, and Future Research Directions.

Fall prediction is a multifaceted problem that involves complex interactions between physiological, behavioral, and environmental factors. Existing fall detection and prediction systems mainly focus on physiological factors such as gait, vision, and cognition, and do not address the multifactorial nature of falls. In addition, these systems lack efficient user interfaces and feedback for preventing future falls. Recent advances in internet of things (IoT) and mobile technologies offer ample opportunities for integrating contextual information about patient behavior and environment along with physiological health data for predicting falls. This article reviews the state-of-the-art in fall detection and prediction systems. It also describes the challenges, limitations, and future directions in the design and implementation of effective fall prediction and prevention systems

Finger tracking and hand recognition technologies in virtual reality maritime safety training applications

The competitiveness and development of the maritime sector together with the continuous effort on increasing operations performance while reducing operations costs, drives the needs for on-board effective and qualitative training safety related issues. Virtual reality (VR) has been considered by classification societies and training organizations as a technology that can significantly improve seafarer's performance and competence with the adaptation of maritime applications developed for design simulation and gaming. This paper presents the evolution of the MarSEVR (Maritime Safety Education with VR) technology as a new concept and technology by integrating finger tracking and hand recognition technologies that increase immersiveness and user engagement within the MarISOT technology, a Green Ocean innovation composed of VR safety applications. The paper approaches this integration by addressing game design, pedagogic and cognitive neuroscience principles and challenges on the use of hand recognition and finger tracking in the MarSEVR learning episodes

Towards a global participatory platform: Democratising open data, complexity science and collective intelligence

The FuturICT project seeks to use the power of big data, analytic models grounded in complexity science, and the collective intelligence they yield for societal benefit. Accordingly, this paper argues that these new tools should not remain the preserve of restricted government, scientific or corporate élites, but be opened up for societal engagement and critique. To democratise such assets as a public good, requires a sustainable ecosystem enabling different kinds of stakeholder in society, including but not limited to, citizens and advocacy groups, school and university students, policy analysts, scientists, software developers, journalists and politicians. Our working name for envisioning a sociotechnical infrastructure capable of engaging such a wide constituency is the Global Participatory Platform (GPP). We consider what it means to develop a GPP at the different levels of data, models and deliberation, motivating a framework for different stakeholders to find their ecological niches at different levels within the system, serving the functions of (i) sensing the environment in order to pool data, (ii) mining the resulting data for patterns in order to model the past/present/future, and (iii) sharing and contesting possible interpretations of what those models might mean, and in a policy context, possible decisions. A research objective is also to apply the concepts and tools of complexity science and social science to the project's own work. We therefore conceive the global participatory platform as a resilient, epistemic ecosystem, whose design will make it capable of self-organization and adaptation to a dynamic environment, and whose structure and contributions are themselves networks of stakeholders, challenges, issues, ideas and arguments whose structure and dynamics can be modelled and analysed. Graphical abstrac

The development and applications of serious games in the public services: defence and health

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.The latest advances of Virtual Reality technologies and three-dimensional graphics, as well as the developments in Gaming Technologies in the recent years, have stemmed the proliferation of Serious Games in a broader spectrum of research applications. Among the most popular areas of application are public services such as Defence and Health, where digital technologies realise new challenges and opportunities for research and development of Serious Games and for a variety of contexts. As with all games, the user engagement is elevated and apart from the entertaining aspect, Serious Games serve as a novel and promising alternative experience to knowledge transfer. Furthermore, Serious Games bring to the end user and the overall society a series of attractive benefits. These benefits include safety, cost-effectiveness, increased motivation and personalisation. Hence, this Thesis aims to investigate novel approaches of developing Serious Games that utilise the recent advances of Virtual Reality and Gaming Technology and facilitate the aforementioned benefits. The process of design and development of the novel tools and applications follow an iterative manner and are driven by the review of the available literature as well as end-user feedbackEPSRC (Engineering and Physical Sciences Research Council ) , MOD (UK), NHS (UK

Health Promotion for Childhood Obesity: An Approach Based on Self-Tracking of Data

[EN]At present, obesity and overweight are a global health epidemic. Traditional interventions for promoting healthy habits do not appear to be e ective. However, emerging technological solutions based on wearables and mobile devices can be useful in promoting healthy habits. These applications generate a considerable amount of tracked activity data. Consequently, our approach is based on the quantified-self model for recommending healthy activities. Gamification can also be used as a mechanism to enhance personalization, increasing user motivation. This paper describes the quantified-self model and its data sources, the activity recommender system, and the PROVITAO App user experience model. Furthermore, it presents the results of a gamified program applied for three years in children with obesity and the process of evaluating the quantified-self model with experts. Positive outcomes were obtained in children’s medical parameters and health habits

Train vs. play: Evaluating the effects of gamified and non-gamified wheelchair skills training using virtual reality

This study compares the influence of a gamified and a non-gamified virtual reality (VR) environment on wheelchair skills training. In specific, the study explores the integration of gamification elements and their influence on wheelchair driving performance in VR-based training. Twenty-two non-disabled participants volunteered for the study, of whom eleven undertook the gamified VR training, and eleven engaged in the non-gamified VR training. To measure the efficacy of the VR-based wheelchair skills training, we captured the heart rate (HR), number of joystick movements, completion time, and number of collisions. In addition, an adapted version of the Wheelchair Skills Training Program Questionnaire (WSTP-Q), the Igroup Presence Questionnaire (IPQ), and the Simulator Sickness Questionnaire (SSQ) questionnaires were administered after the VR training. The results showed no differences in wheelchair driving performance, the level of involvement, or the ratings of presence between the two environments. In contrast, the perceived cybersickness was statistically higher for the group of participants who trained in the non-gamified VR environment. Remarkably, heightened cybersickness symptoms aligned with increased HR, suggesting physiological connections. As such, while direct gamification effects on the efficacy of VR-based wheelchair skills training were not statistically significant, its potential to amplify user engagement and reduce cybersickness is evident