EEG signals are vulnerable to several noise and artifacts occurred by muscle activities and body movements. Reducing these artifacts has been a challenge issue to design and develop a reliable mobile EEG system for various real-life applications including home entertainment as well as clinical monitoring, assessment and rehabilitation. In this paper, we describe a method for removing motion artifacts occurred by body movement using inertial sensors. The key contribution of this work is the automatic identification of independent components representing motion artifacts from EEG signals, incurring minimal computation in real-time. The experimental results from the application of the method show that it is able to remove, in real-time, the motion noise of body movement in an real-world environment with improving the quality of EEG signals up to 82% compared with recorded in seated condition.