This study proposes to recognize a user’s intentions in selecting from a set of machine- controlling commands by measuring his/her brainwaves. Our strategy is to convert a multiple-choice decision into yes-no decisions. For example, in a task of dialing assistance, our system prompts the user to select from each of the digits, and then analyzes his/her brainwave to determine if each digit is what he/she wants. Assume that the user’s intention is 7. Then, when the system prompts the user whether to choose digit 7, the resulting electroencephalogram (EEG) measured from the user should present a certain pattern of “Yes”; otherwise, the result should present a certain pattern of “No”. Hence, our system's goal is to determine whether the user’s intention is “Yes” or “No” based on the measured EEG. This study uses a simple, portable, and cheap instrument that extracts a single-channel EEG from the user’s frontal lobe. The underlying beta waves of EEG are then distilled and examined by a recurrent neural network to determine the user’s intention. Our experiments conducted using 2400 test EEG samples from 10 subjects show that the recognition accuracy obtained with our system is 79.2%.