A Framework to bridge social network and body sensor network: An e-Health perspective

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. Such process includes receiving the sensory data, analyzing it to trigger necessary services such as sending an alert message to the family physician, hospital, emergency service, his immediate caregiver, family members, friends and so on. A BSN also allows members of one's community of interest, referred to as a social network, to query real-time sensory, contextual and event data. Combining the social network with BSN is envisioned to enhance the current state of the art in e-health applications. In this paper, we propose a framework, called SenseFace, that can dynamically pass sensory data from one's BSN to his/her social network and vice versa. Finally, we illustrate the design and implementation of the framework.