Difference between revisions of "BCI based on Motor Imagery"

Revision as of 13:05, 7 December 2009

Website(s)

BioSignal Analysis on Airlab website

Part 2: Project description

A Brain Computer Interface (BCI), also called Brain Machine Interface (BMI), is an advanced communication pathway that can allow an individual to control an external device, such as a wheelchair or a cursor on a computer, using signals measured from the brain (e.g., electroencephalography EEG). Research in this direction results of particular interest when addressed to totally paralyzed people. Using the mu and beta rhythms people has learnt to control their brain activity and thus to control external devices, such as a wheelchair, a cursor on a screen etc. We want to develop a system able to allow users to control the movement of an external device, controlling his/her mu or beta rhythms.

Part 3: Project tracking

Before 25/07/2009 some work as been done:

• literature about motor imagery in BCI field has been read
• initial sessions for signal analysis have been performed
• a feature extractor and a classifier have been trained to interpret brain's motor imagination
• some utilities to deal with large amount of data have been deployed
• everything has been ported from Matlab to BCI2000
• feedback sessions have proven the functionality of the previous work
• a BCI speller has been tested with the output of the classifier

After 25/07/2009:

• Week1:
  • Start studying material from course of Methodologies for Intelligent Systems
  • Start studying of ERP for applications in motor imagery
  • Read "Toward An Integrated P300 And ErrP-Based Brain-Computer Interface" Dal Seno B.
  • Analyzing ErrP caused by classification results in a MI task
  • Deploying a MI interface with visual synchronization signal
• Week2:
  • Interface with discrete feedback presentation ready for use
  • Interface with early classification feedback ready for testing
  • Started testing of newly created interfaces
  • Analizing P300+Errp code for merging
• Week3:
  • Brand new interface for better stimulation of potentials developed
  • Major improvement in file management for Matlab offline analysis
  • Set up of acquisition software for the new interface
  • Development of scripts to approximatively determine the end of training phase (discarded)
  • Merging and adapting code of P300+ErrP to motor imagery tasks
• Week 4:
  • Achieving a method for pipe branching in BCI2000
  • Beginning acquisition of data with ErrPs
  • Ended deployment of execution pipe, from acquisition to extraction and collection of ErrPs (future test required)

Week 5:

• • Focusing on MIS to learn methods for smart use of error probability in class selection

Part 4: References

• Control of two-dimensional movement signals by a noninvasive brain-computer interface in humans, Wolpaw J.R., McFarland J., PNAS, vol. 101, no. 51, december 2004, pages 17849-17854.
• Brain Computer interfaces for communication and control, Wolpaw J.R., Birbaumer N., McFarland D., Pfurtsheller G., Vaughan T., Clinical Neurophysiology 113, 2002, 767-791
• EEG based communication: prospects and problems, Vaughan T., Wolpaw J.R., Donchin E., IEEE transactions on rehabilitation engineering, vol. 4, no. 4, december 1996, pages 425-430.

Links

• Brain-Computer Interface page on this Wiki
• Electroencephalographs
• How to mount electrodes
• How to setup BCI software