In the task of epilepsy detection, the selection of EEG channel directly affects the detection performance. To solve the problem of weak detection ability in some periods of detection method using static channels, a dynamic channel selection method is proposed. The channel set is determined according to the channel position and power spectral density (PSD) of EEG. The channel with the strongest epileptic detection ability is selected as the feature extraction channel, which can enhance the overall detection ability by improving the local detection ability of epilepsy. Experimental results show that the dynamic channel selection method can detect epilepsy with 98. 99% accuracy, 98. 52% sensitivity and 99. 52% specificity. Compared with multi-channel, the detection performance is similar. However, the feature extraction channel is the least, and the time complexity was reduced to O(1). Compared with single channel, the accuracy, sensitivity and specificity are improved more than 4. 93% .