13 research outputs found

    Experiential Perspectives on Sound and Music for Virtual Reality Technologies

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    This thesis examines the intersection of sound, music, and virtuality within current and next-generation virtual reality technologies, with a specific focus on exploring the experiential perspectives of users and participants within virtual experiences. The first half of the thesis constructs a new theoretical model for examining intersections of sound and virtual experience. In Chapter 1, a new framework for virtual experience is constructed consisting of three key elements: virtual hardware (e.g., displays, speakers); virtual software (e.g., rules and systems of interaction); and virtual externalities (i.e., physical spaces used for engaging in virtual experiences). Through using and applying this new model, methodical examinations of complex virtual experiences are possible. Chapter 2 examines the second axis of the thesis through constructing an understanding of how sound is designed, implemented, and received within virtual reality. The concept of soundscapes is explored in the context of experiential perspectives, serving as a useful approach for describing received auditory phenomena. Auditory environments are proposed as a new model for exploring how auditory phenomena can be broadcast to audiences. Chapter 3 explores how inauthenticity within sound can impact users in virtual experience and uses authenticity to critically examine challenges surrounding sound in virtual reality. Constructions of authenticity in music performance are used to illustrate how authenticity is constructed within virtual experience. Chapter 4 integrates music into the understanding of auditory phenomena constructed throughout the thesis: music is rarely part of the created world in a virtual experience. Rather, it is typically something which only the audience – as external observers of the created world – can hear. Therefore, music within immersive virtual reality may be challenging as the audience is placed within the created world.The second half of this thesis uses this theoretical model to consider contemporary and future approaches to virtual experiences. Chapter 5 constructs a series of case studies to demonstrate the use of the framework as a trans-medial and intra/inter-contextual tool of analysis. Through use of the framework, varying approaches to implementation of sound and music in virtual reality technologies are considered, which reveals trans-medial commonalities of immersion and engagement with virtual experiences through sound. Chapter 6 examines near-future technologies, including brain-computer interfaces and other full-immersion technologies, to identify key issues in the design and implementation of future virtual experiences and suggest how interdisciplinary collaboration may help to develop solutions to these issues. Chapter 7 considers how the proposed model for virtuality might allow for methodical examination of similar issues within other fields, such as acoustics and architecture, and examines the ethical considerations that may become relevant as virtual technology develops within the 21st Century.This research explores and rationalises theoretical models of virtuality and sound. This permits designers and developers to improve the implementation of sound and music in virtual experiences for the purpose of improving user outcomes.<br/

    Biosensors for Diagnosis and Monitoring

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    Biosensor technologies have received a great amount of interest in recent decades, and this has especially been the case in recent years due to the health alert caused by the COVID-19 pandemic. The sensor platform market has grown in recent decades, and the COVID-19 outbreak has led to an increase in the demand for home diagnostics and point-of-care systems. With the evolution of biosensor technology towards portable platforms with a lower cost on-site analysis and a rapid selective and sensitive response, a larger market has opened up for this technology. The evolution of biosensor systems has the opportunity to change classic analysis towards real-time and in situ detection systems, with platforms such as point-of-care and wearables as well as implantable sensors to decentralize chemical and biological analysis, thus reducing industrial and medical costs. This book is dedicated to all the research related to biosensor technologies. Reviews, perspective articles, and research articles in different biosensing areas such as wearable sensors, point-of-care platforms, and pathogen detection for biomedical applications as well as environmental monitoring will introduce the reader to these relevant topics. This book is aimed at scientists and professionals working in the field of biosensors and also provides essential knowledge for students who want to enter the field

    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

    Intelligent Biosignal Processing in Wearable and Implantable Sensors

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    This reprint provides a collection of papers illustrating the state-of-the-art of smart processing of data coming from wearable, implantable or portable sensors. Each paper presents the design, databases used, methodological background, obtained results, and their interpretation for biomedical applications. Revealing examples are brain–machine interfaces for medical rehabilitation, the evaluation of sympathetic nerve activity, a novel automated diagnostic tool based on ECG data to diagnose COVID-19, machine learning-based hypertension risk assessment by means of photoplethysmography and electrocardiography signals, Parkinsonian gait assessment using machine learning tools, thorough analysis of compressive sensing of ECG signals, development of a nanotechnology application for decoding vagus-nerve activity, detection of liver dysfunction using a wearable electronic nose system, prosthetic hand control using surface electromyography, epileptic seizure detection using a CNN, and premature ventricular contraction detection using deep metric learning. Thus, this reprint presents significant clinical applications as well as valuable new research issues, providing current illustrations of this new field of research by addressing the promises, challenges, and hurdles associated with the synergy of biosignal processing and AI through 16 different pertinent studies. Covering a wide range of research and application areas, this book is an excellent resource for researchers, physicians, academics, and PhD or master students working on (bio)signal and image processing, AI, biomaterials, biomechanics, and biotechnology with applications in medicine

    Preface

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    An investigation of electronic Protected Health Information (e-PHI) privacy policy legislation in California for seniors using in-home health monitoring systems

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    This study examined privacy legislation in California to identify those electronic Protected Health Information (e-PHI) privacy policies that are suited to seniors using in-home health monitoring systems. Personal freedom and independence are essential to a person\u27s physical and mental health, and mobile technology applications provide a convenient and economical method for monitoring personal health. Many of these apps are written by third parties, however, which poses serious risks to patient privacy. Current federal regulations only cover applications and systems developed for use by covered entities and their business partners. As a result, the responsibility for protecting the privacy of the individual using health monitoring apps obtained from the open market falls squarely on the states. The goal of this study was to conduct an exploratory study of existing legislation to learn what was being done at the legislative level to protect the security and privacy of users using in-home mobile health monitoring systems. Specifically, those developed and maintained by organizations or individuals not classified as covered entities under the Health Insurance Portability and Accountability Act of 1996 (HIPAA). The researcher chose California due to its reputation for groundbreaking privacy laws and high population of seniors. The researcher conducted a content analysis of California state legislation, federal and industry best practices, and extant literature to identify current and proposed legislation regarding the protection of e-PHI data of those using in-home health monitoring systems. The results revealed that in-home health monitoring systems show promise, but they are not without risk. The use of smartphones, home networks, and downloadable apps puts patient privacy at risk, and combining systems that were not initially intended to function together carries additional concerns. Factors such as different privacy-protection profiles, opt-in/opt-out defaults, and privacy policies that are difficult to read or are not adhered to by the application also put user data at risk. While this examination showed that there is legislative support governing the development of the technology of individual components of the in-home health monitoring systems, it appears that the in-home health monitoring system as a whole is an immature technology and not in wide enough use to warrant legislative attention. In addition – unlike the challenges posed by the development and maintenance of the technology of in-home health monitoring systems – there is ample legislation to protect user privacy in mobile in-home health monitoring systems developed and maintained by those not classified as covered entities under HIPAA. Indeed, the volume of privacy law covering the individual components of the system is sufficient to ensure that the privacy of the system as a whole would not be compromised if deployed as suggested in this study. Furthermore, the legislation evaluated over the course of this study demonstrated consistent balance between technical, theoretical, and legal stakeholders. This study contributes to the body of knowledge in this area by conducting an in-depth review of current and proposed legislation in the state of California for the past five years. The results will help provide future direction for researchers and developers as they struggle to meet the current and future needs of patients using this technology as it matures. There are practical applications for this study as well. The seven themes identified during this study can serve as a valuable starting point for state legislators to evaluate existing and proposed legislation within the context of medical data to identify the need for legislation to assist in protecting user data against fraud, identity theft, and other damaging consequences that occur because of a data breach

    Behavioural modelling for ambient assisted living

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    Tese de doutoramento - MAP-i (University of Minho, Aveiro, and Porto)A mudança incomum na rotina diária ao nível da mobilidade de um idoso em sua casa, pode ser um sinal ou sintoma precoce para a possibilidade de vir a desenvolver um problema de saúde. O recurso a diferentes sensores pode ser um meio para complementar os sistemas de cuidados de saúde tradicionais, de forma a obter uma visão mais detalhada da mobilidade diária do individuo em sua casa, enquanto realiza as suas tarefas diárias. Acreditamos, que os dados recolhidos a partir de sensores de baixo custo, como sensores de presença e ocupação, podem ser utilizados para fornecer evidências sobre os hábitos diários de mobilidade dos idosos que vivem sozinhos em casa e detetar desta forma mudanças nas suas rotinas. Neste trabalho, validamos esta hipótese, desenvolvendo um sistema que aprende automaticamente as transições diárias entre divisões da habitação e hábitos de estadia em cada uma dessas divisões em cada momento do dia e consequentemente gera alarmes sempre que os desvios são detetados. Apresentamos neste trabalho um algoritmo que processa os fluxos de dados dos diferentes sensores e identifica características que descrevem a rotina diária de mobilidade de um idoso que vive sozinho em casa. Para isso foi definido um conjunto de dimensões baseadas nos dados extraídos dos sensores, como parte do nosso Behaviour Monitoring System (BMS). Fomos capazes de detetar com um atraso mínimo os comportamentos incomuns e ao mesmo tempo, durações de confirmação da deteção elevadas, de tal modo suficientes para um conjunto comum de situações anormais. Apresentamos e avaliamos o BMS com dados sintetizados, produzidos por um gerador de dados desenvolvido para este efeito e projetado para simular diferentes perfis de mobilidade de indivíduos em casa, e também com dados reais obtidos de trabalhos de investigação anteriores. Os resultados indicam que o BMS deteta várias mudanças de mobilidade que podem ser sintomas para problemas de saúde comuns. O sistema proposto é uma abordagem útil para a aprendizagem dos hábitos de mobilidade em ambientes domésticos, com potencial para detetar alterações comportamentais que ocorrem devido a problemas de saúde, e assim encorajar a monitorização dos comportamentos e dos cuidados de saúde dos idosos.Unusual changes in the regular daily mobility routine of an elderly at home can be an indicator or early symptoms for developing a health problem. Sensor technology can be utilised to complement the traditional healthcare systems to gain a more detailed view of the daily mobility of a person at home when performing everyday tasks. We hypothesise that data collected from low-cost sensors such as presence and occupancy sensors can be analysed to provide insights on the daily mobility habits of the elderly living alone at home and to detect routine changes. We validate this hypothesis by designing a system that automatically learns the daily room-to-room transitions and stays habits in each room at each time of the day and generates alarm notifications when deviations are detected. We present an algorithm to process the sensor data streams and compute features that describe the daily mobility routine of an elderly living alone at home. This was done by defining a set of sensor-driven dimensions extracted from the sensor data as part of our Behaviour Monitoring System (BMS). We are able to achieve low detection delay with confirmation time that is high enough to convey the detection of a set of common abnormal situations. We illustrate and evaluate BMS with synthetic data, generated by a developed data generator that was designed to mimic different users’ mobility profiles at home, and also with real-life dataset collected from prior research work. Results indicate BMS detects several mobility changes that can be symptoms of common health problems. The proposed system is a useful approach for learning the mobility habits at home environments, with the potential to detect behaviour changes that occur due to health problems, and therefore, motivating progress toward behaviour monitoring and elder’s care
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