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

2. Human-computer interaction Interface Human output channels Computer input modalities Human input channels Computer output modalities

3. Think and make it happen without any physical effort Mental activity (MA) Commands Brain-computer interface (BCI)

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. 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

7. Brain-computer interface architecture Brain activity monitoring Translation into commands Electrophysiological signals Commands Subject MA MA ► Action Feedback Application

8. Different types of brain activity Feedback Spontaneous activity Stimulation Evoked activity Stimulus-Driven User-Driven

10. Brain activity changes following mental tasks

11. Brain activity changes following stimulation

13. Generators of the EEG

15. EEG signals Reference electrode Fp1 Fp2 F7 F8 F3 F4 T3 T4 C3 C4 Cz T5 T6 P3 P4 O1 O2

16. EEG Signals

17. BCI operation EEG-trials EEG-trial duration (2 s) Action period (0.5 s) EEG Time Translation into commands Commands CRE

18. BCI operation EEG-trials EEG-trial duration (2 s) Action period (0.5 s) EEG Time Analysis Commands CRE MA recognition

19. Synchronous BCI operation BCI Active Time 0 1 Windows of opportunity Mental activities to recognize Set of controlling MAs

20. Asynchronous BCI operation BCI Active Time 0 1 Mental activities to recognize Neutral MA The BCI is always active

23. Classification- principle Analysis EEG acquisition EEG signals Feature vector Single Trial Classification Single Trial Aggregation Classifier

25. Linear classification in feature vector space P300 Non-P300

26. Aggregation Scheme

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. 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. Some results

32. Gaming

33. Spelling device

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

36. BCI Research Areas Instrumentation Neuroscience Algorithms Applications Evaluation