User interface design for artistic expression based on bio-signals: An EEG feature extraction method based on weak periodic signal detection

This paper discusses the challenges towards achieving bio-signal based design environments. While the primary objective is to provide user-interface for disabled people for artistic expression, special emphasis is given to the design of graphical user interface where bio-signals are the predominant input sources. Among three unique solution methodologies are investigated (Electromyography (EMG), Electrooculography (EOG) and Electroencephalography (EEG)), stimulation based human-computer interaction method (EEG feature extraction method) is found to be the most promising towards achieving design environments for performing complex tasks. Stimulation signals are used to replicate the multi-level ribbon style menu options which is typical format used in today´s software interfaces. Users communicate with the computer by simply responding to appropriate stimulation signal through generating response signals. We propose an EEG feature extraction method based on Steady-State Visual Evoked Potential (SSVEP) to match the stimulating signals with the response signals. Successful pairing of stimulation signals with the brain´s response enables users of such system to perform various actions including artistic expression in 3D.