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

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

A 360 VR and Wi-Fi Tracking Based Autonomous Telepresence Robot for Virtual Tour

This study proposes a novel mobile robot teleoperation interface that demonstrates the applicability of a robot-aided remote telepresence system with a virtual reality (VR) device to a virtual tour scenario. To improve realism and provide an intuitive replica of the remote environment for the user interface, the implemented system automatically moves a mobile robot (viewpoint) while displaying a 360-degree live video streamed from the robot to a VR device (Oculus Rift). Upon the user choosing a destination location from a given set of options, the robot generates a route based on a shortest path graph and travels along that the route using a wireless signal tracking method that depends on measuring the direction of arrival (DOA) of radio signals. This paper presents an overview of the system and architecture, and discusses its implementation aspects. Experimental results show that the proposed system is able to move to the destination stably using the signal tracking method, and that at the same time, the user can remotely control the robot through the VR interface

A Novel Design of Vitual and Mixed Reality Scenarios for Automation Training

A thesis presented to the faculty of the College of Business and Technology at Morehead State University in partial fulfillment of the requirements for the Degree Master of Science by Andrés Salinas-Hernández on April 23, 2021

Privacy in Gaming

Video game platforms and business models are increasingly built on collection, use, and sharing of personal information for purposes of both functionality and revenue. This paper examines privacy issues and explores data practices, technical specifications, and policy statements of the most popular games and gaming platforms to provide an overview of the current privacy legal landscape for mobile gaming, console gaming, and virtual reality devices. The research observes how modern gaming aligns with information privacy notions and norms and how data practices and technologies specific to gaming may affect users and, in particular, child gamers. After objectively selecting and analyzing major players in gaming, the research notes the many different ways that game companies collect data from users, including through cameras, sensors, microphones, and other hardware, through platform features for social interaction and user-generated content, and by means of tracking technologies like cookies and beacons. The paper also notes how location and biometric data are collected routinely through game platforms and explores issues specific to mobile gaming and pairing with smartphones and other external hardware devices. The paper concludes that transparency as to gaming companies’ data practices could be much improved, especially regarding sharing with third party affiliates. In addition, the research considers how children’s privacy may be particularly affected while gaming, determining that special attention should be paid to user control mechanisms and privacy settings within games and platforms, that social media and other interactive features create unique privacy and safety concerns for children which require gamer and parent education, and that privacy policy language is often incongruent with age ratings advertised to children and parents. To contribute additional research value and resources, the paper attaches a comprehensive set of appendices, on which the research conclusions are in part based, detailing the technical specifications and privacy policy statements of popular games and gaming platforms for mobile gaming, console gaming, and virtual reality devices

Wearable and mobile devices

Information and Communication Technologies, known as ICT, have undergone dramatic changes in the last 25 years. The 1980s was the decade of the Personal Computer (PC), which brought computing into the home and, in an educational setting, into the classroom. The 1990s gave us the World Wide Web (the Web), building on the infrastructure of the Internet, which has revolutionized the availability and delivery of information. In the midst of this information revolution, we are now confronted with a third wave of novel technologies (i.e., mobile and wearable computing), where computing devices already are becoming small enough so that we can carry them around at all times, and, in addition, they have the ability to interact with devices embedded in the environment. The development of wearable technology is perhaps a logical product of the convergence between the miniaturization of microchips (nanotechnology) and an increasing interest in pervasive computing, where mobility is the main objective. The miniaturization of computers is largely due to the decreasing size of semiconductors and switches; molecular manufacturing will allow for “not only molecular-scale switches but also nanoscale motors, pumps, pipes, machinery that could mimic skin” (Page, 2003, p. 2). This shift in the size of computers has obvious implications for the human-computer interaction introducing the next generation of interfaces. Neil Gershenfeld, the director of the Media Lab’s Physics and Media Group, argues, “The world is becoming the interface. Computers as distinguishable devices will disappear as the objects themselves become the means we use to interact with both the physical and the virtual worlds” (Page, 2003, p. 3). Ultimately, this will lead to a move away from desktop user interfaces and toward mobile interfaces and pervasive computing

When Internet of Things meets Metaverse: Convergence of Physical and Cyber Worlds

In recent years, the Internet of Things (IoT) is studied in the context of the Metaverse to provide users immersive cyber-virtual experiences in mixed reality environments. This survey introduces six typical IoT applications in the Metaverse, including collaborative healthcare, education, smart city, entertainment, real estate, and socialization. In the IoT-inspired Metaverse, we also comprehensively survey four pillar technologies that enable augmented reality (AR) and virtual reality (VR), namely, responsible artificial intelligence (AI), high-speed data communications, cost-effective mobile edge computing (MEC), and digital twins. According to the physical-world demands, we outline the current industrial efforts and seven key requirements for building the IoT-inspired Metaverse: immersion, variety, economy, civility, interactivity, authenticity, and independence. In addition, this survey describes the open issues in the IoT-inspired Metaverse, which need to be addressed to eventually achieve the convergence of physical and cyber worlds.info:eu-repo/semantics/publishedVersio

Quantifying User Reputation Scores, Data Trustworthiness, and User Incentives in Mobile Crowd-Sensing

Ubiquity of mobile devices with rich sensory capabilities has given rise to the mobile crowd-sensing (MCS) concept, in which a central authority (the platform) and its participants (mobile users) work collaboratively to acquire sensory data over a wide geographic area. Recent research in MCS highlights the following facts: 1) a utility metric can be defined for both the platform and the users, quantifying the value received by either side; 2) incentivizing the users to participate is a non-trivial challenge; 3) correctness and truthfulness of the acquired data must be verified, because the users might provide incorrect or inaccurate data, whether due to malicious intent or malfunctioning devices; and 4) an intricate relationship exists among platform utility, user utility, user reputation, and data trustworthiness, suggesting a co-quantification of these inter-related metrics. In this paper, we study two existing approaches that quantify crowd-sensed data trustworthiness, based on statistical and vote-based user reputation scores. We introduce a new metric - collaborative reputation scores - to expand this definition. Our simulation results show that collaborative reputation scores can provide an effective alternative to the previously proposed metrics and are able to extend crowd sensing to applications that are driven by a centralized as well as decentralized control