Energy-cost-distortion optimization for delay-sensitive M-health applications

Mobile-health (m-health) systems leverage wireless and mobile communication technologies to promote new ways to acquire, process, transport, and secure the raw and processed medical data to provide the scalability needed to cope with the increasing number of elderly and chronic disease patients requiring constant monitoring. However, the design and operation of such health monitoring systems with Body Sensor Networks (BASNs) is challenging in twofold. First, limited power source of the sensor nodes. Second, Quality of Service (QoS) guarantee for the delivery of medical data. Therefore, we propose a cross-layer framework that integrates network particularities and application requirements and constraints to provide a sustainable and high-quality service for health monitoring systems. This framework focuses on energy minimization and EEG signal distortion trade-off for delay sensitive transmission of medical data over heterogeneous wireless environment. Simulation results show that the proposed scheme achieves the optimal tradeoff between energy efficiency and QoS requirements for health monitoring systems.