Extending the discrete selection capabilities of the P300 speller to goal-oriented robotic arm control

A brain-computer interface (BCI), a system that translates a user's brain activity into device commands, can provide a non-muscular means for disabled individuals to interact with their environment. The P300 event-related potential, a transient brain response to a sensory stimulus, has been demonstrated to be a reliable brain signal for controlling a BCI. Traditionally, P300-based BCIs have been used for simple typing tasks using a P300 Speller application, which mimics the functionality of a computer keyboard. Here we extend the discrete selection capabilities of the P300 Speller to achieve high-level control of a 6 degree-of-freedom robotic arm. This study aims to determine if a user's performance, measured in accuracy and communication rate, is affected when a P300 Speller is used to control a robotic arm compared to simple typing. The results indicate that a user's performance is not significantly affected whether typing or controlling a robotic arm.

[1]  J. Wolpaw,et al.  A P300-based brain–computer interface for people with amyotrophic lateral sclerosis , 2008, Clinical Neurophysiology.

[2]  E. W. Sellers,et al.  Toward enhanced P300 speller performance , 2008, Journal of Neuroscience Methods.

[3]  D.J. McFarland,et al.  The wadsworth BCI research and development program: at home with BCI , 2006, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[4]  E. Donchin,et al.  A P300-based brain–computer interface: Initial tests by ALS patients , 2006, Clinical Neurophysiology.

[5]  Jonathan R. Wolpaw,et al.  Brain-computer interfaces (BCIs) for communication and control , 2007, Assets '07.

[6]  Dean J Krusienski,et al.  A comparison of classification techniques for the P300 Speller , 2006, Journal of neural engineering.

[7]  N. Birbaumer,et al.  BCI2000: a general-purpose brain-computer interface (BCI) system , 2004, IEEE Transactions on Biomedical Engineering.

[8]  Jonathan R Wolpaw,et al.  EEG-Based Communication and Control: Speed–Accuracy Relationships , 2003, Applied psychophysiology and biofeedback.

[9]  Gernot R. Müller-Putz,et al.  Control of an Electrical Prosthesis With an SSVEP-Based BCI , 2008, IEEE Transactions on Biomedical Engineering.

[10]  E. Donchin,et al.  Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials. , 1988, Electroencephalography and clinical neurophysiology.