Due to the nonlinearity and nonstationarity of the physiological data sensed by WBAN,data aggregation cannot be effectively achieved according to the time-domain trend of data.Therefore,a novel time series data aggregation algorithm with synchronous prediction was proposed.By preprocessing the original sensing data with the multi-resolution analysis,the inherent characteristics of the physiological data can be obtained to establish a light-weight synchronous prediction model at both the sensor and sink.Numerical results show that the proposed aggregation algorithm can achieve a favorable prediction precision and a low energy consumption rate by eliminating the in-network data redundancy
