An intelligent medical care solution for elderly people with long term health condition based on wireless sensors network technology

Older Adults are facing serious difficulties, on a regular basis, to manage their own daily life activities. To live independently and have a good quality of life is quite a challenge, since the majorly of them have long term health condition diseases. Health services providers across EU, informal and formal carer plays major roles in providing the necessary services and support. Diseases on this society are one of the leading causes of death, from which thousands of people die every year. Many of the non-communicable diseases can be prevented by tackling associated risk factors. The cost of treatment of such diseases in the EU is estimated to be over 70% of the Health Service budget. Treatment includes home-care, medication, consultation and many other relevant services. However, these services are still not adequate, due to the lack of implemented technology that enable the older adults to manage their daily life activities independently, taking medications, receive the necessary health services on time, which, in many cases leads to loss of lives and waste of NHS resources. Daily life activities management and telehealth remote monitoring system is one of the potential innovative approaches, to improve the older adult’s quality of life, help live independently, improve NHS services, sustain its economic growth and improve social development. It is a rapidly developing concept where daily life activities, health condition, medical information is transferred through interactive data, and audiovisual media and shared between services provider, informal and formal carer. This paper presents the initial outcomes of the ongoing research program that is planned to develop an Integrated Assisted Living Technology (ALT) multi-functional case driven wireless ad-hoc management system of the daily life activities of older adults using smart sensors and actuators, 3d-video, audio, radio frequency identification and wireless technology, combined with secure cloud and semantic data engineering

Wireless sensor network for health monitoring

Wireless Sensor Network (WSN) is becoming a significant enabling technology for a wide variety of applications. Recent advances in WSN have facilitated the realization of pervasive health monitoring for both homecare and hospital environments. Current technological advances in sensors, power-efficient integrated circuits, and wireless communication have allowed the development of miniature, lightweight, low-cost, and smart physiological sensor nodes. These nodes are capable of sensing, processing, and communicating one or more vital signs. Furthermore, they can be used in wireless personal area networks (WPANs) or wireless body sensor networks (WBSNs) for health monitoring. Many studies were performed and/or are under way in order to develop flexible, reliable, secure, real-time, and power-efficient WBSNs suitable for healthcare applications. To efficiently control and monitor a patient’s status as well as to reduce the cost of power and maintenance, IEEE 802.15.4/ZigBee, a communication standard for low-power wireless communication, is developed as a new efficient technology in health monitoring systems. The main contribution of this dissertation is to provide a modeling, analysis, and design framework for WSN health monitoring systems. This dissertation describes the applications of wireless sensor networks in the healthcare area and discusses the related issues and challenges. The main goal of this study is to evaluate the acceptance of the current wireless standard for enabling WSNs for healthcare monitoring in real environment. Its focus is on IEEE 802.15.4/ZigBee protocols combined with hardware and software platforms. Especially, it focuses on Carrier Sense Multiple Access with Collision Avoidance mechanism (CSMA/CA) algorithms for reliable communication in multiple accessing networks. The performance analysis metrics are established through measured data and mathematical analysis. This dissertation evaluates the network performance of the IEEE 802.15.4 unslotted CSMA/CA mechanism for different parameter settings through analytical modeling and simulation. For this protocol, a Markov chain model is used to derive the analytical expression of normalized packet transmission, reliability, channel access delay, and energy consumption. This model is used to describe the stochastic behavior of random access and deterministic behavior of IEEE 802.15.4 CSMA/CA. By using it, the different aspects of health monitoring can be analyzed. The sound transmission of heart beat with other smaller data packet transmission is studied. The obtained theoretical analysis and simulation results can be used to estimate and design the high performance health monitoring systems