Brain Computer Interfaces(BCI)

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1. Introduction
2. What is BCI
3. History
4. Structure and signals
5. Architecture/Logical structure
6. Brain waves
7. Functionality
8. Future Work
9. Conclusion
10. References

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Brain Computer Interfaces(BCI)

  1. 1. Presented By Sri Uday Saikia
  2. 2.           Introduction What is BCI History Structure and signals Architecture/Logical structure Brain waves Functionality Future Work Conclusion References
  3. 3.     It is the study of brain functions. A collaboration in which a brain accepts and controls a mechanical device. Direct communication pathway between a brain and an external device. Thus BCI extracts electro-physical signals from suitable components of the brain and process them to generate control signals for computers, robotic machines or communication devices.
  4. 4. “ A Brain-Computer Interface is a communication system that do not depend on peripheral nerves and muscles “ [J. R. Wolpaw et al. “Brain-computer interface technology: A review of the first international meeting,” IEEE Trans. Rehab. Eng., vol. 8, no. 2, pp. 164–173, 2000]
  5. 5.  Brain-Computer Interfaces (BCI) ◦ Interaction between the human neural system and machines ◦ Goal  Enabling people (especially disabled) to communicate and control devices by mere thinking. ◦ BCI is a control system
  6. 6.    1924: Hans Berger discovers the EEG Analyses the interrelation of EEG and brain diseases. 1970: First developments to use brain waves as input ARPA has vision of enhanced human First step in the right direction
  7. 7.     1990: First successful experiments with monkeys Implanting electrode arrays into monkey brains Recording of monkeys„ brain waves 2000: Monkeys control robots by thoughts
  8. 8.    More non-invasive than invasive approaches Brain reading by eg. EEG, MEG or fMRI 2004: First human benefits from research
  9. 9. BASIC COMPONENTS: • Implant device • Signal recording and processing • External device used for control • Feedback section to the subject
  10. 10. • Brain is made out of neurons • Brain detects and translates the signal of brain to tangible action • Same principle different clearness • More accurate signal detection from invasive BCI
  11. 11. What is logical scheme of BCI? appropriate feature extraction Signal Features Brain Psychological Effort (Intention) Computer Classification Of Intent appropriate feedback strategy computer training user training Modification of EEG Brain Signals Environment
  12. 12. What is the motivation for BCI Research ? Only in USA, more than 200,000 patients live with the motor consequences of serious injury. Motivation for Patients: is to give disable people to communicate, to operate prostheses, and even to operate wheelchairs using brain signals Nicolelis, 2001 Only the INVASIVE SURGEON TECHNIQUE allows putting electrode into a very local area of a brain uniting a few neurons. These neurons could be belong to the cortex center, for example, for finger control.
  13. 13. BCI Types Invasive BCI: implant electrodes directly onto a patient’s brain. Non-Invasive: implant medical scanning devices to read brain signals.
  14. 14. What is invasive technology for BCI ? Philip Kennedy and Roy Bakay (Emory University in Atlanta) were first to install a brain implant in a human that produced signals of high enough quality to simulate movement. Implant was installed in 1998 and the patient lived long enough to start working with the implant, eventually learning to control a computer cursor. Kennedy, P.R., Bakay R.A. (1998) Restoration of neural output from a paralysed patient by a direct brain connection. Neuroreport. ;9(8):1707-11 10 array of electrodes, each separated by 400 μm John P. Donoghue, et al. Assistive technology and robotic control using motor cortex ensemble-based neural interface systems in humans with tetraplegia. J Physiol 579.3 (2007) pp 603–611
  15. 15. Disability Level and Application: BCI for common people Communication  Most Disable people  Neuroprosthetics  Health people  Environmental control Robotics / Manipulators/ Mobility devices
  16. 16. Honda Asimo Controll
  17. 17. And an artificial eye can see a lot…
  18. 18.   Feature Extraction The Translation Algorithm
  19. 19.  Any controllable machines ◦ ◦ ◦ ◦  For answering yes/no questions For word processing Wheelchair Virtual Reality Usually, Computer screen and the output is the selection of targets or cursor movement
  20. 20.  Successful Story, Wearable BCI  BCI2000 ◦ A successful transition of the whole BCI system to the portable device ◦ No machine learning ◦ Limited computational power (limited signal processing) ◦ A general-purpose system for (BCI) research  Source Module (new device new driver)  Signal Processing Module (reusable, No Machine Learning)  User Application Module (UDP/IP support to be running in any machine) ◦ Platform  Microsoft Windows™ 2000/XP  C++ language
  21. 21.  Mobility ◦ Communication technologies  Bluetooth  802.11(wire less –WLAN)  GSM/GPRS ◦ PDA instead of stationary computer   Dry Electrode instead of wet (reducing montage time) Making the BCI transparent ◦ No need to change electrodes for a reasonable long time
  22. 22. Theta waves [4, 7.5] associated with reverie, daydreaming, meditation, creative ideas Delta waves [0,4] Hz associated with deep sleep and in the awake state were thought to indicates physical defects in the brain.
  23. 23. Alpha wave(8-13hz)-its indicates both a relaxed and attention mode of the brain. Beta wave(13-30 hz)-it is the brain wave usually associated with activity thinking, active attention.
  24. 24. CHARACTERISTICS OF BRAIN WAVES Gamma waves-within 35Hz-it reflect the mechanism of consciousness. Mu wave(8-12)hz –associated with Motor activity,
  25. 25.  Steps for the function of BCI. 1.user wired to a multi-electrode EEG skin cap, which is connected to a pc running BCI2000. 2.user of the signal asked to generate a series of signals. 3.EEG potential record and analyze the signal 4.the software attempt to match these signal to previous recorded signals. 5.at last identified words are wrapped on output devices like-screen or speech synthesizer.
  26. 26.  Undergone through hurdle brain surgery.  New surgery for each up gradation  Risky and complicated eyes surgery.  Use wearable computing devices.  External device is good option.  Glasses and Lasik operation is best options.
  27. 27. BCI DRAWBACKS THE DRAWBACKS OF BCI : - THE BRAIN IS INCREDIBLY COMPLEX, - THE SIGNAL IS WEAK & PRONE TO INTERFENCE, - THE EQUIPMENTS IS LESS THAN PORTABLE,
  28. 28.  Berlin Brain-Computer-Interface ◦ Joint Venture of several German research organisations ◦ Supported by the Ministry of Education and Research  Graz Brain-Computer-Interface ◦ Wide range of research topics ◦ Impressive combination of BCI and FES (Functional Electrical Stimulation)
  29. 29.    Virtual Reality Bluesense,Sniff mode Bluesense, Security
  30. 30. • A potential therapeutic tool. • BCI is an advancing technology promising paradigm shift in areas like Machine Control, Human Enhancement, Virtual reality and etc. So, it’s potentially high impact technology. • Several potential applications of BCI hold promise for rehabilitation and improving performance, such as treating emotional disorders (for example, depression or anxiety), easing chronic pain, and overcoming movement disabilities due to stroke. • Will enable us to achieve singularity very soon. • Intense R&D in future to attain intuitive efficiency.
  31. 31. Star wars Humans dive into a virtual world by connecting their brains directly to a computer. Harder concentration to the fan to blow for simulating the ball to float
  32. 32.   [1] IEEE Xplorer Digital Library website(Through SJCE Server) http://ieeexplore.ieee.org/Xplore [2] Wikipedia - internet encyclopedia http://en.wikipedia.org/wiki/Braincomputer_interface
  33. 33. • Sixto Ortiz Jr., "Brain-Computer Interfaces: Where Human and Machine Meet," Computer, vol. 40, no. 1, pp. 17-21, Jan., 2007 • F. Babiloni, A. Cichocki, and S. Gao, eds., special issue, “BrainComputer Interfaces: Towards Practical Implementations and Potential Applications,” ComputationalIntelligence and Neuroscience, 2007 • P. Sajda, K-R. Mueller, and K.V. Shenoy, eds., special issue, “Brain Computer Interfaces,” IEEE Signal Processing Magazine,Jan. 2008 • The MIT Press – “Toward Brain-Computer Interfacing” • Wikipedia, HowStuffWorks and various other website sources…

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