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

The Industry and Policy Context for Digital Games for Empowerment and Inclusion:Market Analysis, Future Prospects and Key Challenges in Videogames, Serious Games and Gamification

The effective use of digital games for empowerment and social inclusion (DGEI) of people and communities at risk of exclusion will be shaped by, and may influence the development of a range of sectors that supply products, services, technology and research. The principal industries that would appear to be implicated are the 'videogames' industry, and an emerging 'serious games' industry. The videogames industry is an ecosystem of developers, publishers and other service providers drawn from the interactive media, software and broader ICT industry that services the mainstream leisure market in games, The 'serious games' industry is a rather fragmented and growing network of firms, users, research and policy makers from a variety of sectors. This emerging industry is are trying to develop knowledge, products, services and a market for the use of digital games, and products inspired by digital games, for a range of non-leisure applications. This report provides a summary of the state of play of these industries, their trajectories and the challenges they face. It also analyses the contribution they could make to exploiting digital games for empowerment and social inclusion. Finally, it explores existing policy towards activities in these industries and markets, and draws conclusions as to the future policy relevance of engaging with them to support innovation and uptake of effective digital game-based approaches to empowerment and social inclusion.JRC.J.3-Information Societ

Towards fog-driven IoT eHealth:Promises and challenges of IoT in medicine and healthcare

Internet of Things (IoT) offers a seamless platform to connect people and objects to one another for enriching and making our lives easier. This vision carries us from compute-based centralized schemes to a more distributed environment offering a vast amount of applications such as smart wearables, smart home, smart mobility, and smart cities. In this paper we discuss applicability of IoT in healthcare and medicine by presenting a holistic architecture of IoT eHealth ecosystem. Healthcare is becoming increasingly difficult to manage due to insufficient and less effective healthcare services to meet the increasing demands of rising aging population with chronic diseases. We propose that this requires a transition from the clinic-centric treatment to patient-centric healthcare where each agent such as hospital, patient, and services are seamlessly connected to each other. This patient-centric IoT eHealth ecosystem needs a multi-layer architecture: (1) device, (2) fog computing and (3) cloud to empower handling of complex data in terms of its variety, speed, and latency. This fog-driven IoT architecture is followed by various case examples of services and applications that are implemented on those layers. Those examples range from mobile health, assisted living, e-medicine, implants, early warning systems, to population monitoring in smart cities. We then finally address the challenges of IoT eHealth such as data management, scalability, regulations, interoperability, device–network–human interfaces, security, and privacy

JENTIL: responsive clothing that promotes an ‘holistic approach to fashion as a new vehicle to treat psychological conditions’

This paper explores an ongoing interdisciplinary research project at the cutting edge of sensory, aroma and medical work, which seeks to change the experience of fragrance to a more intimate communication of identity, by employing emerging technologies with the ancient art of perfumery. The project illustrates .holistic' clothing called the JENTIL® Collection, following on from the Author’s SmartSecondSkin' PhD research, which describes a new movement in functional, emotional clothing that incorporates scent. The project investigates the emergent interface between the arts and biomedical sciences, around new emerging technologies and science platforms, and their applications in the domain of health and well-being. The JENTIL® Collection focuses on the development of .gentle., responsive clothing that changes with emotion, since the garments are designed for psychological end benefit to reduce stress. This is achieved by studying the mind and advancing knowledge and understanding of how known well-being fragrances embedded in holistic Fashion, could impact on mental health. This paper aims to combine applied theories about human well-being, with multisensory design, in order to create experimental strategies to improve self and social confidence for individuals suffering from depressive illnesses. The range of methodologies employed extends beyond the realm of fashion and textile techniques, to areas such as neuroscience, psychiatry, human sensory systems and affective states, and the increase in popularity of complementary therapies. In this paper the known affective potential of the sense of smell is discussed, by introducing Aroma-Chology as a tool that is worn as an emotional support system to create a personal scent bubble. around the body, with the capacity to regulate mood, physiological and psychological state and improve self-confidence in social situations. The clothing formulates a healing platform around the wearer, by creating novel olfactory experiences in textiles that are not as passive as current microencapsulated capsule systems generally are

Brain Neoplasm Classification & Detection of Accuracy on MRI Images

The abnormal, uncontrolled cell growth in the brain, commonly known n as a brain tumor, can lead to immense pressure on the various nerves and blood vessels, causing irreversible harm to the body. Early detection of brain tumors is the key to avoiding such compilations. Tumour detection can be done through various advanced Machine Learning and Image Processing algorithms. Mind Brain tumors have demonstrated testing to treat, to a great extent inferable from the organic qualities of these diseases, which frequently plan to restrict progress. To begin with, by invading one of the body's most significant organs, these growths are much of the time situated past the compass of even the most gifted neurosurgeon. These cancers are likewise situated behind the blood-cerebrum boundary (BBB), a tight intersection and transport proteins that shield fragile brain tissues from openness to factors in the overall flow, subsequently obstructing openness to foundational chemotherapy [6,7]. Besides, the interesting formative, hereditary, epigenetic and micro environmental elements of the cerebrum much of the time render these tumors impervious to ordinary and novel medicines. These difficulties are accumulated by the uncommonness of cerebrum growths comparative with numerous different types of disease, restricting the degree of subsidizing and interest from the drug business and drawing in a moderately little and divided research local area

Wearable Computing for Health and Fitness: Exploring the Relationship between Data and Human Behaviour

Health and fitness wearable technology has recently advanced, making it easier for an individual to monitor their behaviours. Previously self generated data interacts with the user to motivate positive behaviour change, but issues arise when relating this to long term mention of wearable devices. Previous studies within this area are discussed. We also consider a new approach where data is used to support instead of motivate, through monitoring and logging to encourage reflection. Based on issues highlighted, we then make recommendations on the direction in which future work could be most beneficial

Self “Sensor”Ship: An Interdisciplinary Investigation of the Persuasiveness, Social Implications, and Ethical Design of Self-Sensoring Prescriptive Applications

This dissertation research investigates the social implications of computing artifacts that make use of sensor driven self-quantification to implicitly or explicitly direct user behaviors. These technologies are referred to here as self-sensoring prescriptive applications (SSPA’s). This genre of technological application has a strong presence in healthcare as a means to monitor health, modify behavior, improve health outcomes, and reduce medical costs. However, the commercial sector is quickly adopting SSPA’s as a means to monitor and/or modify consumer behaviors as well (Swan, 2013). These wearable devices typically monitor factors such as movement, heartrate, and respiration; ostensibly to guide the users to better or more informed choices about their physical fitness (Lee & Drake, 2013; Swan, 2012b). However, applications that claim to use biosensor data to assist in mood maintenance and control are entering the market (Bolluyt, 2015), and applications to aid in decision making about consumer products are on the horizon as well (Swan, 2012b). Interestingly, there is little existing research that investigates the direct impact biosensor data have on decision making, nor on the risks, benefits, or regulation of such technologies. The research presented here is inspired by a number of separate but related gaps in existing literature about the social implications of SSPA’s. First, how SSPA’s impact individual and group decision making and attitude formation within non-medicalcare domains (e.g. will a message about what product to buy be more persuasive if it claims to have based the recommendation on your biometric information?). Second, how the design and designers of SSPA’s shape social behaviors and third, how these factors are or are not being considered in future design and public policy decisions