Hacking Brain Computer Interfaces
1 like2,760 views
The document discusses brain-computer interfaces (BCIs), detailing their definition, types, and data analysis methods. It presents OpenBCI as an open-source platform that supports community engagement and offers affordable BCI solutions, along with examples of practical applications, including games that utilize EEG data for user interaction. The conclusion highlights the potential for further development and innovation within the BCI field.
Hacking Brain Computer Interfaces
- 1. Hacking Brain-Computer Interfaces SMSI talk by Mike Schäkermann Berlin - March 17, 2015
- 2. Overview 1. About BCIs 2. OpenBCI 3. Live Demo
- 3. Overview 1. About BCIs 2. OpenBCI 3. Live Demo
- 5. A brain-computer interface is a direct communication pathway between the brain and an external device.
- 6. Brain Imaging Techniques EEG fMRI NIRS Invasive techniques
- 7. Brain Imaging Techniques EEG fMRI NIRS Invasive techniques
- 11. Pros and Cons of EEG High temporal resolution Level of insight Sensitivity Low spatial resolution Discomfort Sensitivity
- 12. EEG Data: (1/3) Presentation Time domain plot Frequency domain plot Spectrogram Head plot / topography
- 13. EEG Data: (1/3) Presentation TIME DOMAIN PLOT FREQUENCY DOMAIN PLOT HEAD PLOT
- 14. EEG Data: (1/3) Presentation SPECTROGRAM
- 15. EEG Data: (2/3) Preprocessing Removal of noise / artifacts, caused by: blinks lateral eye movements muscle activity head/body movement electrical currents (powerline interference)
- 16. EEG Data: (3/3) Analysis Frequency analysis (Alpha, Beta, Gamma, Delta, Theta, Mu) Event-related potentials (P300, ERN, and many more) Steady-state topography (SSVEP, ASSR) Others (Hemispheric asymmetry, Coherence)
- 17. EEG Data: (3/3) Analysis Frequency analysis (Alpha, Beta, Gamma, Delta, Theta, Mu) Event-related potentials (P300, ERN, and many more) Steady-state topography (SSVEP, ASSR) Others (Hemispheric asymmetry, Coherence)
- 18. EEG Data: (3/3) Analysis GAMMA (> 31 Hz) DETECTED OVER THE SOMATOSENSORY CORTEX DURING CROSS-MODAL SENSORY PROCESSING FREQUENCY ANALYSIS
- 19. EEG Data: (3/3) Analysis BETA (15 - 31 Hz) DETECTED SYMMETRICALLY IN FRONTAL REGIONS DURING PHASES OF FOCUS AND CONCENTRATION FREQUENCY ANALYSIS
- 20. EEG Data: (3/3) Analysis ALPHA (8 - 15 Hz) DETECTED IN POSTERIOR REGIONS DURING RELAXED STATES AND WHILE EYES ARE CLOSED FREQUENCY ANALYSIS
- 21. EEG Data: (3/3) Analysis MU (8 - 12 Hz) DETECTED OVER MOTOR CORTEX DURING IMAGINED OR ACTUAL MOVEMENT FREQUENCY ANALYSIS
- 22. EEG Data: (3/3) Analysis THETA (4 - 7 Hz) DETECTED DURING IDLING, RELAXED, MEDITATIVE AND CREATIVE STATES FREQUENCY ANALYSIS
- 23. EEG Data: (3/3) Analysis DELTA (< 4 Hz) DETECTED IN FRONTAL REGIONS DURING SLOW- WAVE SLEEP + CONTINUOUS ATTENTION TASKS FREQUENCY ANALYSIS
- 24. EEG Data: (3/3) Analysis Frequency analysis (Alpha, Beta, Gamma, Delta, Theta, Mu) Event-related potentials (P300, ERN, and many more) Steady-state topography (SSVEP, ASSR) Others (Hemispheric asymmetry, Coherence)
- 25. EEG Data: (3/3) Analysis EVENT-RELATED POTENTIALS (EX: P300)
- 26. EEG Data: (3/3) Analysis EVENT-RELATED POTENTIALS (EX: P300)
- 27. EEG Data: (3/3) Analysis EVENT-RELATED POTENTIALS (EX: P300)
- 28. EEG Data: (3/3) Analysis Frequency analysis (Alpha, Beta, Gamma, Delta, Theta, Mu) Event-related potentials (P300, ERN, and many more) Steady-state topography (SSVEP, ASSR) Others (Hemispheric asymmetry, Coherence)
- 29. EEG Data: (3/3) Analysis Frequency analysis (Alpha, Beta, Gamma, Delta, Theta, Mu) Event-related potentials (P300, ERN, and many more) Steady-state topography (SSVEP, ASSR) Others (Hemispheric asymmetry, Coherence)
- 31. BrainBall: Relax to Win (1999) Based on alpha and theta activation
- 32. BrainBall: Relax to Win (1999) Based on alpha and theta activation
- 33. SharkAttack: mind-controlled shark (2015) Based on multiple people’s alpha activation
- 34. SharkAttack: mind-controlled shark (2015)
- 35. HexBug: mind-controlled robot (2015) Based on alpha activation and visual entrainment
- 36. HexBug: mind-controlled robot (2015)
- 37. HexBug: mind-controlled robot (2015)
- 38. HexBug: mind-controlled robot (2015)
- 39. Unity3D SDKs for Emotiv and Neurosky
- 40. Necomimi: emotional cat ears
- 41. Overview 1. About BCIs 2. OpenBCI 3. Live Demo
- 43. Overview 1. About BCIs 2. OpenBCI 3. Live Demo
- 44. Crowdfunded open source consumer BCI
- 52. Building a BCI community ...
- 53. Emotiv NeuroSky Muse OpenEEG Systems for research or clinical use, cost thousands of dollars Prices range from $50 to $300, for a comparison, see here Bridging a gap ...
- 54. Open-source: Software Hardware Headware Access to raw data High sample rate: 256 Hz SDKs / connectors available for: Processing Python OpenVIBE BrainBay OpenFrameworks (coming soon) Node.js (coming soon) Comes pre-assembled Affordable price: $450 for 8-channel kit $800 for 16-channel kit Bridging a gap ...
- 55. Overview 1. About BCIs 2. OpenBCI 3. Live Demo
- 56. Live Demo
- 57. Alpha wave trigger for meditation music
- 58. Alpha wave trigger for meditation music EYES OPEN PLAY ENERGETIC MUSIC
- 59. Alpha wave trigger for meditation music EYES OPEN PLAY ENERGETIC MUSIC EYES CLOSED PLAY CALMING MUSIC
- 60. Alpha wave trigger for meditation music
- 61. Alpha wave trigger for meditation music
- 62. Alpha wave trigger for meditation music FUTURE WORK: GUARD BANDS
- 63. Alpha wave trigger for meditation music FUTURE WORK: GUARD BANDS
- 64. Alpha wave trigger for meditation music FUTURE WORK: GUARD BANDS
- 65. Thanks for your attention! Questions, please!
- 66. References & Further Reading OpenBCI (http://openbci.com/): Docs: Tutorials: http://docs.openbci.com/tutorials/01-GettingStarted Software: http://docs.openbci.com/software/01-OpenBCI_SDK Hardware: http://docs.openbci.com/hardware/01-OpenBCI_Hardware Blogs (http://openbci.com/community/): Omphaloskeptic: http://www.autodidacts.io/ Chip Audette: http://eeghacker.blogspot.com/ Conor Russomanno: http://conorrussomanno.com/ Jeremy Frey: http://blog.jfrey.info/ GitHub: https://github.com/OpenBCI
- 67. References & Further Reading Ambinder, Mike. 2011. Biofeedback in Gameplay: How Valve Measures Physiology to Enhance Gaming Experience. Presentation at Game Developers Conference (GDC) 2011. http://www.gdcvault.com/play/1014734/Biofeedback-in- Gameplay-How-Valve. Cacioppo, John T., Louis G. Tassinary, and Gary Berntson. 2007. Handbook of Psychophysiology. Cambridge University Press. isbn: 9780521844710. Hakvoort, Gido, Hayrettin Gü rkö k, Danny Plass-Oude Bos, Michel Obbink, and Mannes Poel. 2011. Measuring immersion and affect in a brain-computer interface game. In Proceedings of the 13th ifip tc 13 international conference on human-computer interaction - volume part i, 115–128. INTERACT’11. Berlin, Heidelberg: Springer-Verlag. isbn: 978- 3-642-23773-7, http://dl.acm.org/citation.cfm?id=2042053.2042069. Kivikangas, J. Matias, Inger Ekman, Guillaume Chanel, Simo Järvelä, Ben Cowley, Pentti Henttonen, and Niklas Ravaja. 2010. Review on psychophysiological methods in game research. In Proc. of 1st nordic digra, digra. Luck, Stephen J. 2005. An introduction to the event-related potential technique. Cognitive neuroscience. MIT Press. isbn: 9780262621960.
- 68. References & Further Reading Mandryk, Regan. 2008. Physiological Measures for Game Evaluation. In Game usability: advice from the experts for advancing the player experience. Nacke, Lennart E. 2011. Directions in Physiological Game Evaluation and Interaction. In chi 2011 bbi workshop proceedings. ———. 2013. An Introduction to Physiological Player Metrics for Evaluating Games. Chap. 26 in Game analytics: maximizing the value of player data, 585–620. London: Springer-Verlag. isbn: 978-1-4471-4768-8, doi:10.1007/978-1- 4471-4769-5. Nacke, Lennart E., Mark N. Grimshaw, and Craig A. Lindley. 2010. More Than a Feeling: Measurement of Sonic User Experience and Psychophysiology in a First-person Shooter Game. Interact. Comput. (New York, NY, USA) 22, no. 5 (Sept.): 336–343. issn: 0953-5438, doi:10.1016/j.intcom.2010.04.005, http://dx.doi.org/10. 1016/j.intcom.2010.04.005. Wehbe, Rina R., Dennis L. Kappen, David. Rojas, Matthias. Klauser, Bill. Kapralos, and Lennart E. Nacke. 2013. EEG- based Assessment of Video and In-game Learning. In Chi ’13 extended abstracts on human factors in computing systems, 667–672. CHI EA ’13. New York, NY, USA: ACM. isbn: 978-1-4503-1952-2, doi:10.1145/2468356.2468474, http://doi.acm.org/10.1145/2468356.2468474.