The invention discloses an application method of a compressed sensing-based P300 brain-machine interface in a smart home. The method includes: constructing a multi-source data collection and aggregation platform, wherein the platform includes a multi-function sensor and a displayer; collecting P300 EEG signals through EEG signal collection equipment, and compressing P300 EEG signals based on datacompressed-sensing theory to obtain observation signals; transmitting the observation signals in a wireless manner to a host computer through Wifi, then determining an estimation of sparse coefficients on the basis of an orthogonal matching tracking algorithm, and then reconstructing P300 EEG signals to use the same for subsequent analysis; and designing a P300 EEG signal-based ideation control platform to realize the ideation control of a target home appliance. According to the method, highly efficient acquisition of the P300 EEG signals can be realized on the basis of the compressed-sensingtheory, data transmission efficiency can be improved, EEG signals of a user can be converted into an effective control instruction, the brain-machine interface can be enabled to be effectively appliedin the smart home, and ideation control on the home appliance can be realized.