Growing importance in health care and monitoring systems had resulted in greater scope of research nowadays. This had resulted in a rapid surge of interest and motivation in managing patients with neurological disorders and for monitoring of patients with chronic diseases. Human movement monitoring using wireless sensory nodes across the body either at hospitals or at remote locations promises to revolutionize the delivery of healthcare services. These techniques depend on inertial information of the patients for motion analysis. Such actions can help to trigger alarms or diagnose diseases by continuous and complex processing of sensor data from various parts of the body using a Body Sensor Network (BSN). Despite the recent developments and advancements of sensing and monitoring devices, power efficiency and quality of service had left as an open challenge for improvement. This proposal suggests an adaptive energy efficient QoS optimized communication model for monitory and transmitting sensed data to the backend servers periodically. These BSN uses self-adaptive buffers to limit communication to short bursts, decreasing power usage and optimizing the QoS. This project provides a self-adaptive heuristic scheme which is formulated to reduce transmissions among sensor nodes and provide the data at right time for early diagnosis and analysis for health care professionals. Several experimental analysis and simulations are to be done to evaluate the proposed technique for fast allocation of buffers in real-time under various scenarios. The same is to be compared with existing systems as well. © Research India Publications.