Mobihealth: mobile health services based on body area networks

In this chapter we describe the concept of MobiHealth and the approach developed during the MobiHealth project (MobiHealth, 2002). The concept was to bring together the technologies of Body Area Networks (BANs), wireless broadband communications and wearable medical devices to provide mobile healthcare services for patients and health professionals. These technologies enable remote patient care services such as management of chronic conditions and detection of health emergencies. Because the patient is free to move anywhere whilst wearing the MobiHealth BAN, patient mobility is maximised. The vision is that patients can enjoy enhanced freedom and quality of life through avoidance or reduction of hospital stays. For the health services it means that pressure on overstretched hospital services can be alleviated

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

Personalization in cultural heritage: the road travelled and the one ahead

Over the last 20 years, cultural heritage has been a favored domain for personalization research. For years, researchers have experimented with the cutting edge technology of the day; now, with the convergence of internet and wireless technology, and the increasing adoption of the Web as a platform for the publication of information, the visitor is able to exploit cultural heritage material before, during and after the visit, having different goals and requirements in each phase. However, cultural heritage sites have a huge amount of information to present, which must be filtered and personalized in order to enable the individual user to easily access it. Personalization of cultural heritage information requires a system that is able to model the user (e.g., interest, knowledge and other personal characteristics), as well as contextual aspects, select the most appropriate content, and deliver it in the most suitable way. It should be noted that achieving this result is extremely challenging in the case of first-time users, such as tourists who visit a cultural heritage site for the first time (and maybe the only time in their life). In addition, as tourism is a social activity, adapting to the individual is not enough because groups and communities have to be modeled and supported as well, taking into account their mutual interests, previous mutual experience, and requirements. How to model and represent the user(s) and the context of the visit and how to reason with regard to the information that is available are the challenges faced by researchers in personalization of cultural heritage. Notwithstanding the effort invested so far, a definite solution is far from being reached, mainly because new technology and new aspects of personalization are constantly being introduced. This article surveys the research in this area. Starting from the earlier systems, which presented cultural heritage information in kiosks, it summarizes the evolution of personalization techniques in museum web sites, virtual collections and mobile guides, until recent extension of cultural heritage toward the semantic and social web. The paper concludes with current challenges and points out areas where future research is needed

Understanding the Cognitive Impact of Emerging Web Technologies: A Research Focus Area for Embodied, Extended and Distributed Approaches to Cognition

Alongside existing research into the social, political and economic impacts of the Web, there is also a need to explore the effects of the Web on our cognitive profile. This is particularly so as the range of interactive opportunities we have with the Web expands under the influence of a range of emerging technologies. Embodied, extended and distributed approaches to cognition are relevant to understanding the potential cognitive impact of these new technologies because of the emphasis they place on extra-neural and extra-corporeal factors in the shaping of our cognitive capabilities at both an individual and collective level. The current paper outlines a number of areas where embodied, extended and distributed approaches to cognition are useful in understanding the impact of emerging Web technologies on future forms of both human and machine intelligence

A neural probe with up to 966 electrodes and up to 384 configurable channels in 0.13 μm SOI CMOS

In vivo recording of neural action-potential and local-field-potential signals requires the use of high-resolution penetrating probes. Several international initiatives to better understand the brain are driving technology efforts towards maximizing the number of recording sites while minimizing the neural probe dimensions. We designed and fabricated (0.13-μm SOI Al CMOS) a 384-channel configurable neural probe for large-scale in vivo recording of neural signals. Up to 966 selectable active electrodes were integrated along an implantable shank (70 μm wide, 10 mm long, 20 μm thick), achieving a crosstalk of −64.4 dB. The probe base (5 × 9 mm2) implements dual-band recording and a 1

Digital transformation in healthcare: an innovative business plan for an application digitizing physical rehabilitation

The health care system adapts to innovations very slowly, as strict rules control all measures. It is even more challenging when one wants to introduce a digital solution for the healthcare market. Even minor changes to the code can mean major hurdles for approvals. This challenge was taken up in the following master thesis. The status quo of gait analysis has hardly been innovated for decades. The approach of reha buddy is to analyze how a human walks through wireless sensors. This represents an innovation that will revolutionize the market for gait analysis. Above all, trends of the last two years, which were pushed even more by the last pandemic, have shown that there is probably no better time to pursue this project. Additionally, a literature review and expert interviews were conducted to support all statements in the thesis. What is more, for a precise examination of each chapter of the business plan, a market analysis was carried out focusing on all specific characteristics of the health care market. The team of reha buddy has to overcome some major obstacles in the next few years but is well-positioned with their team of experts who set some important milestones for managing those hurdles. The result of this work is a business plan which clarifies that reha buddy's vision has an entrepreneurial foundation and that the team's idea should be pursued.O Sistema de Saúde adapta-se às inovações muito lentamente, uma vez que regras rígidas controlam todas as medidas. É um desafio ainda maior quando se deseja introduzir uma solução digital no setor da Saúde. Mesmo pequenas alterações no código podem significar grandes dificuldades para aprovações. Este desafio é abordado na presente tese de mestrado. O status quo da locomoção praticamente não foi inovado durante décadas. A abordagem do Reha Buddy passa por analisar como um humano se desloca através de sensores sem fios, o que representa uma inovação que irá revolucionar o mercado da locomoção. Acima de tudo, as tendências dos últimos dois anos, que foram impulsionadas ainda mais pela última pandemia, mostraram que provavelmente não há melhor momento para avançar com este projeto. Foi realizada uma revisão de literatura, assim como entrevistas com especialistas com o objetivo de apoiar todas as afirmações. Adicionalmente, para uma análise eficaz de cada capítulo do plano de negócios, foi realizada uma análise de mercado com foco em todas as características específicas do mercado da Saúde. A equipa do Reha Buddy terá que superar alguns obstáculos importantes nos próximos anos; está, no entanto, bem posicionada com a sua equipa de especialistas que estabeleceu alguns marcos importantes para gerir esses obstáculos. O resultado do presente projeto é um plano de negócios que esclarece que a visão do Reha Buddy tem uma base empreendedora e que a ideia apresentada pela equipa deve ser concretizada

AXMEDIS 2008

The AXMEDIS International Conference series aims to explore all subjects and topics related to cross-media and digital-media content production, processing, management, standards, representation, sharing, protection and rights management, to address the latest developments and future trends of the technologies and their applications, impacts and exploitation. The AXMEDIS events offer venues for exchanging concepts, requirements, prototypes, research ideas, and findings which could contribute to academic research and also benefit business and industrial communities. In the Internet as well as in the digital era, cross-media production and distribution represent key developments and innovations that are fostered by emergent technologies to ensure better value for money while optimising productivity and market coverage

Assessment of Hand Gestures Using Wearable Sensors and Fuzzy Logic

Hand dexterity and motor control are critical in our everyday lives because a significant portion of the daily motions we perform are with our hands and require some degree of repetition and skill. Therefore, development of technologies for hand and extremity rehabilitation is a significant area of research that will directly help patients recovering from hand debilities sustained from causes ranging from stroke and Parkinson’s disease to trauma and common injuries. Cyclic activity recognition and assessment is appropriate for hand and extremity rehabilitation because a majority of our essential motions are cyclic in their nature. For a patient on the road to regaining functional independence with daily skills, the improvement in cyclic motions constitutes an important and quantifiable rehabilitation goal. However, challenges exist with hand rehabilitation sensor technologies preventing acquisition of long-term, continuous, accurate and actionable motion data. These challenges include complicated and uncomfortable system assemblies, and a lack of integration with consumer electronics for easy readout. In our research, we have developed a glove based system where the inertial measurement unit (IMU) sensors are used synergistically with the flexible sensors to minimize the number of IMU sensors. The classification capability of our system is improved by utilizing a fuzzy logic data analysis algorithm. We tested a total of 25 different subjects using a glove-based apparatus to gather data on two-dimensional motions with one accelerometer and three-dimensional motions with one accelerometer and two flexible sensors. Our research provides an approach that has the potential to utilize both activity recognition and activity assessment using simple sensor systems to help patients recover and improve their overall quality of life