Investigating the role of combined acoustic-visual feedback in one-dimensional synchronous brain computer interfaces, a preliminary study

Feedback plays an important role when learning to use a brain computer interface (BCI), particularly in the case of synchronous feedback that relies on the interaction subject. In this preliminary study, we investigate the role of combined auditory-visual feedback during synchronous μ rhythm-based BCI sessions to help the subject to remain focused on the selected imaginary task. This new combined feedback, now integrated within the general purpose BCI2000 software, has been tested on eight untrained and three trained subjects during a monodimensional left-right control task. In order to reduce the setup burden and maximize subject comfort, an electroencephalographic device suitable for dry electrodes that required no skin preparation was used. Quality and index of improvement was evaluated based on a personal self-assessment questionnaire from each subject and quantitative data based on subject performance. Results for this preliminary study show that the combined feedback was well tolerated by the subjects and improved performance in 75% of the naïve subjects compared with visual feedback alone.

[1]  H. Flor,et al.  A multimodal brain-based feedback and communication system , 2004, Experimental Brain Research.

[2]  José del R. Millán,et al.  Noninvasive brain-actuated control of a mobile robot by human EEG , 2004, IEEE Transactions on Biomedical Engineering.

[3]  David McAlpine,et al.  Sound localization and delay lines – do mammals fit the model? , 2003, Trends in Neurosciences.

[4]  G. Chatrian,et al.  The blocking of the rolandic wicket rhythm and some central changes related to movement. , 1959, Electroencephalography and clinical neurophysiology.

[5]  F. Lotte,et al.  Self-Paced Brain-Computer Interaction with Virtual Worlds: A Quantitative and Qualitative Study "Out of the Lab" , 2008 .

[6]  André van Schaik,et al.  A new EEG recording system for passive dry electrodes , 2010, Clinical Neurophysiology.

[7]  J. Wolpaw,et al.  Patients with ALS can use sensorimotor rhythms to operate a brain-computer interface , 2005, Neurology.

[8]  José del R. Millán,et al.  Haptic Feedback Compared with Visual Feedback for BCI , 2006 .

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

[10]  N. Birbaumer,et al.  A brain–computer interface (BCI) for the locked-in: comparison of different EEG classifications for the thought translation device , 2003, Clinical Neurophysiology.

[11]  G. Pfurtscheller,et al.  Rapid prototyping of an EEG-based brain-computer interface (BCI) , 2001, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[12]  Mikko Sams,et al.  EEG-Based Brain-Computer Interface for Tetraplegics , 2007, Comput. Intell. Neurosci..

[13]  P. Bifulco,et al.  A mobile EEG system with dry electrodes , 2008, 2008 IEEE Biomedical Circuits and Systems Conference.

[14]  José del R. Millán.  Adaptive Brain Interfaces for Communication and Control , 2003 .

[15]  Clemens Brunner,et al.  Better than random? A closer look on BCI results , 2008 .

[16]  M. Jeannerod.  Mental imagery in the motor context , 1995, Neuropsychologia.

[17]  Maria Romano,et al.  An ultra-high input impedance ECG amplifier for long-term monitoring of athletes , 2010, Medical devices.

[18]  Clemens Brunner,et al.  Mu rhythm (de)synchronization and EEG single-trial classification of different motor imagery tasks , 2006, NeuroImage.

[19]  G. Pfurtscheller,et al.  How many people are able to operate an EEG-based brain-computer interface (BCI)? , 2003, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[20]  Gert Pfurtscheller,et al.  Motor imagery and direct brain-computer communication , 2001, Proc. IEEE.

[21]  J. Wolpaw,et al.  Mu and Beta Rhythm Topographies During Motor Imagery and Actual Movements , 2004, Brain Topography.

[22]  B. Blankertz,et al.  A New Auditory Multi-Class Brain-Computer Interface Paradigm: Spatial Hearing as an Informative Cue , 2010, PloS one.