Body sensor network (BSN) has played a key role in the rapid advancement of e-Health applications. If it is properly designed, a BSN can act as an ambient intelligent environment by providing us not only time critical human body information but also the context and events mapped with raw sensory data.

Body sensor networks (BSN) can capture physical phenomena from a human body, contextual information from the environment and high level events of a person. Associating contextual information and events with the captured raw sensory data can serve as a crucial input for many applications such as e-health. For example, to accurately and timely monitor an elderly person with several physical disabilities while he is at home or outdoors, the context and event information along with raw sensory data needs to be reached to an e-health service provider to assist in taking time critical decision.

Nowadays, technology advances accelerate the quality and type of services 
provided for health care and especially for monitoring health conditions. Sensors have 
become more powerful to sense different physiological signs and have the ability to be worn 
on the human body using wireless communication modules. A variety of software tools have 
been developed to help in processing a variance list of vital signs by analyzing and 
visualizing data generated by multiple sensors. In this thesis, we introduced a Health ...