Wireless body area network（ WBAN） node is usually powered by batteries

which is energy limited and not easy to change frequently. A data compression energy-saving method is proposed to reduce the energy consumption of WBAN node

adopting sparse representation classification（ SRC） algorithm to identify the normal signal

using compressed sensing（ CS） theory for signal compression sampling

and the compressed signal is sent to the base station for refactoring. The simulation and analysis have been implemented on electrocardiogram（ ECG）signal collected by WBAN nodes

the results show that the ECG signal after compression

has good recognition performance and reconstruction performance

and under the premise that ensure the data transmission precision

reduce the amount of data acquisition and transmission

effectively reduce the energy consumption of WBAN nodes.