A method for extracting f wave from a single-lead electrocardiography signal is provided. The method includes: establishing a two-channel temporal convolutional neural network model, including two coding submodules, two mask estimation submodules, an information fusion module and two decoding submodules; constructing a training data set of ECG signals; training the two-channel temporal convolutional neural network model, and saving the trained model. The two-channel temporal convolution neural network encodes and decodes a QRST complex and the f wave respectively, and uses a mask of information fusion to estimate and construct regular items to restrict a distribution difference of QRST component coding features, so as to reduce the distortion of the QRST complex, select potential features of a QRST complex and f wave with high signal-to-noise ratio, and thus improve a detection accuracy of the f wave.