A low-cost EEG system-based hybrid brain-computer interface for humanoid robot navigation and recognition.

ABSTRACT: This paper describes a hybrid brain-computer interface (BCI) technique that combines the P300 potential, the steady state visually evoked potential (SSVEP), and event related de-synchronization (ERD) to solve a complicated multi-task problem consisting of humanoid robot navigation and control along with object recognition using a low-cost BCI system. Our approach enables subjects to control the navigation and exploration of a humanoid robot and recognize a desired object among candidates. This study aims to demonstrate the possibility of a hybrid BCI based on a low-cost system for a realistic and complex task. It also shows that the use of a simple image processing technique, combined with BCI, can further aid in making these complex tasks simpler. An experimental scenario is proposed in w

SUBMITTER: Choi B 

PROVIDER: S-EPMC3762758 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature