Fig. 4.

Two different approaches for extracting hidden information from biosignals in deep learning. (A) Convolution in a convolutional neural network fits the convolutional matrix to extract a feature map that is a type of matrix containing valuable information for discriminating between labels. (B) An autoencoder extracts hidden information useful for reconstruction of raw data from the data itself. Although the features are derived regardless of label information, principal information included in the raw signal is obtained that can be used in other machine learning algorithms to predict or detect labels.