RECENT ADVANCES IN BRAIN-COMPUTER INTERFACES

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These are the slides of my keynote at the IEEE Multimedia Signal Processing Workshop organized in Chania, Greece, on October 2007.

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  • Please mail to me this presentation in some time. I am in need of it for our seminar. Mail Id: scmurthy2@gmail.com
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  • hi..,can u please mail me the presentation to pruthvi.cit@gmail.com..,
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  • hello
    can you send me this presentation plz ?!!
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    thnx in advance xx
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  • it is really awesome...n a best piece of best skills,knowledge n ofcourse hardwork...
    m really impressed.....
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  • cud you please please give me this seminar....it is real piece of hardwork....
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  • Good afternoon members of the jury thank you for your presence here. My name is Gary Garcia I’ll present you my thesis work entitled direct brain-computer communication through scalp recorded EEG signals.
  • RECENT ADVANCES IN BRAIN-COMPUTER INTERFACES

    1. 1. <ul><li>RECENT ADVANCES IN </li></ul><ul><li>BRAIN-COMPUTER INTERFACES </li></ul><ul><li>Touradj Ebrahimi </li></ul><ul><li>IEEE MMSP 2007 </li></ul><ul><li>October 3 rd , 2007 </li></ul>
    2. 2. Human-computer interaction Interface Human output channels Computer input modalities Human input channels Computer output modalities
    3. 3. Think and make it happen without any physical effort Mental activity (MA) Commands Brain-computer interface (BCI)
    4. 4. BCI: early history 1929 Hans Berger Electrical Activity from the skull 1955 Barry Sterman animal neurofeedback Joe Kamiya Human neurofeedback (Richard Bach) 1958 1970 “ Toward Direct Brain-Computer Communication” J. Vidal, Annu. Rev. of Biophys. Bioeng 1973 1953 Eugene Aserinsky Sleep signals Jacques Vidal BCI
    5. 5. BCI development 2002 ~100 research groups 2004 1995 Gerf Pfurtscheller (Graz, Austria) 1991 Jonathan Wolpaw (Wadsworth, US) Second international meeting on BCI 38 research groups Touradj Ebrahimi (EPFL, Switzerland) 2000 1999 First international meeting on BCI 22 research groups
    6. 6. Outline <ul><li>Introduction to BCI and EEG </li></ul><ul><li>A BCI for disabled users </li></ul><ul><li>Applications and examples </li></ul><ul><li>Future Trends </li></ul>
    7. 7. Brain-computer interface architecture Brain activity monitoring Translation into commands Electrophysiological signals Commands Subject MA MA ► Action Feedback Application
    8. 8. Different types of brain activity Feedback Spontaneous activity Stimulation Evoked activity Stimulus-Driven User-Driven
    9. 9. Hemispheric specialization Left Hemisphere Right Hemisphere <ul><li>Analytical </li></ul><ul><li>processing </li></ul><ul><li>Language </li></ul><ul><li>Right Hand </li></ul><ul><li>Right Body-side </li></ul>Right visual field Left visual field <ul><li>Global, </li></ul><ul><li>holistic processing </li></ul><ul><li>Visuospatial skills </li></ul><ul><li>Left Hand </li></ul><ul><li>Left Body-side </li></ul>Corpus callosum
    10. 10. Brain activity changes following mental tasks
    11. 11. Brain activity changes following stimulation
    12. 12. Methods for measuring brain activity Invasive Noninvasive <ul><li>Microelectrode Arrays </li></ul><ul><li>Electrocorticogram </li></ul><ul><li>Magnetic Resonance Imaging </li></ul><ul><li>Magnetoencephalogram (MEG) </li></ul><ul><li>Near-Infrared Spectroscopy </li></ul><ul><li>Electroencephalogram (EEG) </li></ul>
    13. 13. Generators of the EEG
    14. 14. Scalp recorded electroencephalogram (EEG) <ul><li>Good time resolution </li></ul><ul><li>Relative simplicity </li></ul><ul><li>Low cost </li></ul>10-20 International system Fp1 Fp2 F7 F8 F3 F4 T3 T4 C3 C4 Cz T5 T6 P3 P4 O1 O2
    15. 15. EEG signals Reference electrode Fp1 Fp2 F7 F8 F3 F4 T3 T4 C3 C4 Cz T5 T6 P3 P4 O1 O2
    16. 16. EEG Signals
    17. 17. BCI operation EEG-trials EEG-trial duration (2 s) Action period (0.5 s) EEG Time Translation into commands Commands CRE
    18. 18. BCI operation EEG-trials EEG-trial duration (2 s) Action period (0.5 s) EEG Time Analysis Commands CRE MA recognition
    19. 19. Synchronous BCI operation BCI Active Time 0 1 Windows of opportunity Mental activities to recognize Set of controlling MAs
    20. 20. Asynchronous BCI operation BCI Active Time 0 1 Mental activities to recognize Neutral MA The BCI is always active
    21. 21. Outline <ul><li>Introduction to BCI and EEG </li></ul><ul><li>A BCI for disabled users </li></ul><ul><li>Applications and examples </li></ul><ul><li>Future Trends </li></ul>
    22. 22. A P300 based environment control system <ul><li>P300 </li></ul><ul><li>Images are intensified </li></ul><ul><li>Block - randomized, one at a time </li></ul><ul><li>User concentrates on one image </li></ul><ul><li>Target image evokes P300 </li></ul><ul><li>P300 allows to compute target </li></ul><ul><li>Environment Control </li></ul><ul><li>Programmable IR control “James” </li></ul><ul><li>Serial port input </li></ul><ul><li>Can control wheelchair, TV, phone, window, elevator, etc. </li></ul>
    23. 23. Classification- principle Analysis EEG acquisition EEG signals Feature vector Single Trial Classification Single Trial Aggregation Classifier
    24. 24. Analysis of EEG signals EEG signals Feature vector Analysis Feature extraction <ul><li>Lowpass Filter </li></ul><ul><li>Downsampling </li></ul>
    25. 25. Linear classification in feature vector space P300 Non-P300
    26. 26. Aggregation Scheme
    27. 27. Analysis and classification - details <ul><ul><li>Referencing </li></ul></ul><ul><ul><li>Lowpass Filtering </li></ul></ul><ul><ul><li>Downsampling </li></ul></ul><ul><ul><li>Single Trial Extraction </li></ul></ul><ul><ul><li>Outlier Removal </li></ul></ul><ul><ul><li>Normalization </li></ul></ul><ul><ul><li>Electrode Selection </li></ul></ul>Analysis Single Trial Classification <ul><ul><li>Bayesian Discriminant Analysis </li></ul></ul><ul><ul><li>Sparse Bayesian Discriminant Analysis </li></ul></ul>Aggregation <ul><ul><li>Fixed scheme </li></ul></ul><ul><ul><li>Adaptive scheme </li></ul></ul>
    28. 28. Bitrate Recognition accuracy [%] Bit rate [ bits/min ] Communication speed 25 30 40 50 60 70 80 90 100 0 20 40 60 80 100 120 140 160 180 200 220
    29. 29. Subjects S1 S3 S8 S9 Diagnosis Cerebral palsy Late-stage ALS - - Age 56 47 28 27 Age at illness onset 0 39 - - Sex M M M M Speech production Mild dysarthria Severe dysarthria - - Limb muscle control Weak Very weak - - Respiration control Normal Weak - - Voluntary eye movement Normal Normal - -
    30. 30. Some results
    31. 31. Outline <ul><li>Introduction to BCI and EEG </li></ul><ul><li>A BCI for disabled users </li></ul><ul><li>Applications and examples </li></ul><ul><li>Future Trends </li></ul>
    32. 32. Gaming
    33. 33. Spelling device
    34. 34. 2D cursor control Wolpaw et al , “ Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans ”, Proceedings of the National Academy of Sciences, 2004
    35. 35. Outline <ul><li>Introduction to BCI and EEG </li></ul><ul><li>A BCI for disabled users </li></ul><ul><li>Applications and examples </li></ul><ul><li>Future Trends </li></ul>
    36. 36. BCI Research Areas Instrumentation Neuroscience Algorithms Applications Evaluation
    37. 37. Instrumentation / Algorithms <ul><li>The ideal sensor </li></ul><ul><ul><li>Cheap, robust, simple </li></ul></ul><ul><ul><li>High spatial and temporal resolution </li></ul></ul><ul><ul><li>Long-term use possible, non-invasive, non-obtrusive </li></ul></ul><ul><ul><li>Candidate: Dry EEG electrodes, multimodal methods </li></ul></ul><ul><li>Algorithms </li></ul><ul><ul><li>Which type of signal needs adaptation </li></ul></ul><ul><ul><li>Adaptation with and without class labels </li></ul></ul><ul><ul><li>Speed of adaptation </li></ul></ul><ul><ul><li>Stability </li></ul></ul><ul><ul><li>Reaction of the user to adaptation </li></ul></ul>
    38. 38. Neuroscience / Applications <ul><li>Neuroscience </li></ul><ul><ul><li>Feedback through electrical stimulation </li></ul></ul><ul><ul><ul><li>What region should be stimulated </li></ul></ul></ul><ul><ul><ul><li>How should feedback be encoded </li></ul></ul></ul><ul><ul><li>Characterization of signals from disabled users </li></ul></ul><ul><li>Applications </li></ul><ul><ul><li>Better applications for the disabled </li></ul></ul><ul><ul><li>Intelligent devices </li></ul></ul><ul><ul><li>Multimedia </li></ul></ul>
    39. 39. Acknowledgements <ul><li>This work is based on contributions from: </li></ul><ul><li>Med. Sc. Damien Debatisse </li></ul><ul><li>Dr. Gary Garcia </li></ul><ul><li>Ulrich Hoffmann* </li></ul><ul><li>Dr. Jean-Marc Vesin* </li></ul><ul><li>* Coauthors of accompanying paper </li></ul>
    40. 40. Further information <ul><li>Thank you for your attention </li></ul><ul><li>For more information please visit </li></ul><ul><li>http://bci.epfl.ch </li></ul>
    41. 41. <ul><li>«  We must develop as quickly as possible technologies that make possible a direct connection between brain and computer, so that artificial brains contribute to human intelligence rather than opposing it » </li></ul><ul><li>Stephen Hawking </li></ul>

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