Human-Computer Interaction

At the course we will recognize principles and guidelines for designing User Interfaces (UI), and communication between brains and computer via movement imagery, i.e., non-invasive Brain-Computer Interface (BCI). The topics are following: human capabilities (memory and learning, perception, cognition), types of UI communications (input models, models and metaphors), UI design principles (Norman's hints, Mandel's principles, Nielsen's principles), UI design guidelines (selection and arranging graphic controllers for interaction, graphic design, feedback and interactions, selection and design of icons), electroencephalogram (EEG) and brain-computer communication, international reference database for designing BCI (EEGMMI DS - EEG Motor Movement/Imagery DataSet), designing non-invasive BCI, spectral analysis of EEG signals (power spectrum, autoregressive method, time-frequency representations, parametric modeling), feature extraction in time and frequency domain, feature selection, classification of imagined movements, BCI with machine learning, BCI applications (cursor moving, spelling, communication for handicapped). The environments used will be NetBeans and Matlab. Coursework consists of two seminars, quiz during laboratory sessions, quiz during lectures, and final exam.