U-health expert system with statistical neural network

Ubiquitous Health(U-Health) system witch focuses on automated applications that can provide healthcare to human anywhere and anytime using wired and wireless mobile technologies is becoming increasingly important. This system consists of a network system to collect data and a sensor module which measures pulse, blood pressure, diabetes, blood sugar, body fat diet with management and measurement of stress etc, by both wired and wireless and further portable mobile connections. In this paper, we propose an expert system using back-propagation to support the diagnosis of citizens in U-Health system

An Experimental Study on Ubiquitous commerce Adoption: Impact of Personalization and Privacy Concerns

Ubiquitous commerce (u-commerce) represents anytime, anywhere commerce. U-commerce can provide a high level of personalization, which can bring significant benefits to customers. However, privacy is a major concern to customers and an obstacle to the adoption of u-commerce. This research examines how personalization and context can impact customers\u27 privacy concerns as well as intention to adopt u-commerce applications. As u-commerce is new and emerging, we used the scenario-based approach to operationalize personalization and context in an experimental study. The experimental results show that the effects of personalization on customers\u27 privacy concerns and adoption intention are situation dependent

Impact of Mobile and Wireless Technology on Healthcare Delivery services

Modern healthcare delivery services embrace the use of leading edge technologies and new scientific discoveries to enable better cures for diseases and better means to enable early detection of most life-threatening diseases. The healthcare industry is finding itself in a state of turbulence and flux. The major innovations lie with the use of information technologies and particularly, the adoption of mobile and wireless applications in healthcare delivery [1]. Wireless devices are becoming increasingly popular across the healthcare field, enabling caregivers to review patient records and test results, enter diagnosis information during patient visits and consult drug formularies, all without the need for a wired network connection [2]. A pioneering medical-grade, wireless infrastructure supports complete mobility throughout the full continuum of healthcare delivery. It facilitates the accurate collection and the immediate dissemination of patient information to physicians and other healthcare care professionals at the time of clinical decision-making, thereby ensuring timely, safe, and effective patient care. This paper investigates the wireless technologies that can be used for medical applications, and the effectiveness of such wireless solutions in a healthcare environment. It discusses challenges encountered; and concludes by providing recommendations on policies and standards for the use of such technologies within hospitals

Medical data processing and analysis for remote health and activities monitoring

Recent developments in sensor technology, wearable computing, Internet of Things (IoT), and wireless communication have given rise to research in ubiquitous healthcare and remote monitoring of human\u2019s health and activities. Health monitoring systems involve processing and analysis of data retrieved from smartphones, smart watches, smart bracelets, as well as various sensors and wearable devices. Such systems enable continuous monitoring of patients psychological and health conditions by sensing and transmitting measurements such as heart rate, electrocardiogram, body temperature, respiratory rate, chest sounds, or blood pressure. Pervasive healthcare, as a relevant application domain in this context, aims at revolutionizing the delivery of medical services through a medical assistive environment and facilitates the independent living of patients. In this chapter, we discuss (1) data collection, fusion, ownership and privacy issues; (2) models, technologies and solutions for medical data processing and analysis; (3) big medical data analytics for remote health monitoring; (4) research challenges and opportunities in medical data analytics; (5) examples of case studies and practical solutions

Smart Signs: Showing the way in Smart Surroundings

This paper presents a context-aware guidance and messaging system for large buildings and surrounding venues. Smart Signs are a new type of electronic door- and way-sign based on wireless sensor networks. Smart Signs present in-situ personalized guidance and messages, are ubiquitous, and easy to understand. They combine the easiness of use of traditional static signs with the flexibility and reactiveness of navigation systems. The Smart Signs system uses context information such as user’s mobility limitations, the weather, and possible emergency situations to improve guidance and messaging. Minimal infrastructure requirements and a simple deployment tool make it feasible to easily deploy a Smart Signs system on demand. An important design issue of the Smart Signs system is privacy: the system secures communication links, does not track users, allow almost complete anonymous use, and prevent the system to be used as a tool for spying on users

Towards personalized services in the healthcare domain

Healthcare services are designed for enabling the provision of medical care to the patient. The traditional healthcare services are based on the doctor-centric paradigm. Essentially, they enable healthcare providers to assess patients’ health status based on information derived from medical examination and information stored in patient’s electronic Medical Health Records (eMHRs) [1]. Hence, it is crucial for patient’s health data to be digitalized and organized in such a way allowing their exploitation by the healthcare provider at a later point of time [2]. The doctor-centric healthcare services enhance healthcare providers’ diagnosing skills and enable them to give patients accurate treatment directions aiming to their earlier and safer de-hospitalization