Learning to decode human emotions with Echo State Networks

From one side this proof of concept application enhances the usability context of the reservoir computing for high dimensional static data representations by low-dimensional feature transformation as functions of the reservoir states. From other side, the proposed solution for emotion valence detection across subjects is suitable for brain studies as a complement to statistical methods. This problem is important because such decision making systems constitute “virtual sensors” of hidden emotional states, which are useful in psychology science research and clinical applications.