Understanding data flow and security requirements in wireless Body Area Networks for healthcare

The Body Area Network (BAN) is an emerging technology that focuses on monitoring physiological data in, on and around the human body. BAN technology permits wearable and implanted sensors to collect vital data about the human body and transmit it to other nodes via low-energy communication. In this paper, we investigate interactions in terms of data flows between parties involved in BANs under four different scenarios targeting outdoor and indoor medical environments: hospital, home, emergency and open areas. Based on these scenarios, we identify data flow requirements between BAN elements such as sensors and control units (CUs) and parties involved in BANs such as the patient, doctors, nurses and relatives. Identified requirements are used to generate BAN data flow models. Petri Nets (PNs) are used as the formal modelling language. We check the validity of the models and compare them with the existing related work. Finally, using the models, we identify communication and security requirements based on the most common active and passive attack scenarios.

Social networks and use of social supports of minority elders in East Harlem

Considerable empirical research substantiates the importance of social networks on health and well-being in later life. A study of ethnic minority elders living in two low income public housing buildings in East Harlem was undertaken to gain an understanding of the relationship between their health status and social networks. Findings demonstrate that elders with supportive housing had better psychological outcomes and used significantly more informal supports when in need. However, elders with serious health problems had poorer outcomes regardless of their level of social support. This study highlights the potential of supportive living environments to foster social integration and to optimise formal and informal networks.