© 2015 by Taylor & Francis Group, LLC. Monitoring human movements using wireless sensory devices promises to revolutionize the delivery of health care services. Such platforms use inertial information of their subjects for motion analysis. Potentially, each action or disease can be discovered by collaborative processing of sensor data from multiple locations on the body. This functionality is provided by a body area network (BAN), which consists of several wireless sensor nodes positioned on different parts of the body. In spite of the revolutionary potential of this platform, power requirements and wearability have limited the commercialization of these systems. This chapter presents energy-efficient communication models for BAN applications using buffers to limit communication to higher-rate short bursts, decreasing power usage and simplifying the communication. Transmission at higher rates and in short bursts will create opportunities to reduce the energy per bit for communication, hence decreasing the overall energy consumption. This energy minimization is achieved via proper buffer allocation in this chapter. The buffer allocation problem is formulated as an optimization problem that reduces transmissions among sensor nodes. Both an integer linear programming (ILP) solution and a fast greedy heuristic algorithm are discussed to solve this power optimization problem. It is shown that despite the decreased transmission efficiency, the greedy algorithm can be adopted for fast allocation of buffers in real time. Performance of both the near-optimal and greedy solutions is compared against an unbuffered system using experimental analysis. It is demonstrated that ILP and greedy solutions can reduce the amount of transmissions by an average factor of 70% and 41%, respectively.