Optimum data collection and fusion schemes in WBSN

In this paper first we define our strategies aiming at minimising number of communicated data while keeping data integrity in wireless body sensor networks (WBSNs). In this way, we introduce modified Fisher test, develop Spline interpolation as the behaviour function and define controlling parameters. To achieve at significant results, we propose three efficient algorithms. Furthermore, at the second step, we represent our method to calculate the priority of vital sign data packets. For this purpose, we employ Spline interpolation function and define six new controlling parameters. At the third step, for correct inference of patient's situations we introduce our method which develops adaptive neuro fuzzy inference system (ANFIS) with cross-validation. Simulation results in MATLAB R2018b demonstrate the optimum performance of our schemes for number of communicated data, network lifetime, priority based data communication and also correct inference of patient's situations.