Body Area Wireless Sensor Networks (BAWSNs) have numerous applications. These typically involve the sensing of physiological data in a number of sensor nodes placed at various points on the body, the communication of this data to a central node and the use of intelligence algorithms to make decisions on the basis of the data. The sensor nodes are required to be small and light, preventing the use of bulky batteries. In order to maximise the length of time for which the sensor nodes can operate without requiring recharging, their energy consumption must be minimised. There are two main causes of sensor node energy consumption, namely the processing of data and the transmission of data. Clearly, reducing the amount of data that is processed and transmitted by a node can be reduce the energy consumption. However, there is typically a trade-off between the amount of data that is processed by a node and the amount of data that it transmits. For example, distributed intelligence and compression algorithms can be used to reduce the amount of data that is transmitted by a node, at the cost of increasing the amount of data processing performed. Furthermore, the contributions of sensing, communication and intelligence are inherently linked. For example, distributed intelligence algorithms require the communication of data between the sensor nodes that are involved in making decisions. Therefore this project aims to jointly consider the sensing, communication and intelligence of BAWSNs in order to strike attractive trade-offs between the processing and communication requirements of sensor nodes.