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.