Brain Computer Interface ppt


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Brain Computer Interface ppt

  1. 1. Brain Computer Interface By, Ajay George S8 - IT03/13/13 IT Department, JECC
  2. 2. What is BCI• Direct communication pathway between the brain and an external device• Reads electrical signals from brain• Signals translated into a digital form03/13/13 IT Department, JECC
  3. 3. History• Research started from 1970• BCI Project by Jacques Vidal• Implanting simple BCI sensors within rats, mice, monkeys, and humans.03/13/13 IT Department, JECC
  4. 4. History• 1990 - implanting an electrode in the motor cortex of a paralyzed patient.• Makes the patient communicate by moving a cursor.• 1999 – Trained rats to use their brain signals to move a robotic water-dispensing arm.03/13/13 IT Department, JECC
  5. 5. How BCI work03/13/13 IT Department, JECC
  6. 6. How BCI work03/13/13 IT Department, JECC
  7. 7. How BCI work • Uses optical nerves for image input • Camera input directed to brain03/13/13 IT Department, JECC
  8. 8. Types of BCI• Invasive• Partially Invasive• Non-Invasive03/13/13 IT Department, JECC
  9. 9. Invasive BCI• Targeted for people with paralysis• Implanted directly into the grey matter• Produce the highest quality signals Jens Naumann, a man with acquired blindness, being• scar-tissue build-up interviewed about his vision03/13/13 IT Department, JECC
  10. 10. Partially Invasive BCI• BCI devices are implanted inside the skull• produce better resolution signals Cathy Hutchinson, who was one• lower risk of of the first persons to have a forming scar-tissue direct connection between her brain and a computer implanted03/13/13 IT Department, JECC
  11. 11. Non-Invasive BCI• Easy to wear• produce poor signal• dispersing the electromagnetic waves created by the neurons03/13/13 IT Department, JECC
  12. 12. Recording Domains03/13/13 IT Department, JECC
  13. 13. Electrocorticography(ECoG )• Pioneered in the early 1950s• Measures the electrical activity of the brain• Taken from beneath the skull• Embeds electrodes in a plastic bag placed above cortex• A surgical incision is required03/13/13 IT Department, JECC
  14. 14. MRI technology• Uses brain signals to control• Detects the subject’s brain signals and sends the MRI signals over Ethernet cables, via TCP/IP, to a computer.03/13/13 IT Department, JECC
  15. 15. MRI technology03/13/13 IT Department, JECC
  16. 16. Magnetoencephalography (MEG)• Magnetic Field of 10-15 T to 10-13 T• S.Q.U.I.D Sensors are required• Shielded room is needed03/13/13 IT Department, JECC
  17. 17. Electroencephalography (EEG)• Recording of electrical activity along the scalp• Measures voltage fluctuations resulting from ionic current.• Fine temporal resolution• Ease of use, portable and low set-up cost03/13/13 IT Department, JECC
  18. 18. Electroencephalography (EEG)Emotiv Cap, 14 Electordes,Wireless connection. Commercial BCI from NeuroSky03/13/13 IT Department, JECC
  19. 19. Electroencephalography (EEG) P30003/13/13 IT Department, JECC
  20. 20. Electroencephalography (EEG)• Described in frequency ranges• Delta (δ) < 4 Hz. Most apparent in deep sleep states.• Theta (θ) waves 4-8 Hz, appear in a relaxed state and during light sleep and meditation.03/13/13 IT Department, JECC
  21. 21. Electroencephalography (EEG)• Alpha (α) waves 8-12 Hz, associated with meditation and relaxation.• Beta (β) 13-30 Hz waves, connected to alertness and focus.• Gamma (γ) waves > 30 Hz, related to subjective awareness03/13/13 IT Department, JECC
  22. 22. Electroencephalography (EEG) System Block Diagram03/13/13 IT Department, JECC
  23. 23. Processes• Bandpass Filter - to filter out frequencies that do not fall within the α and β ranges.• Related to senseorimotor activities• Common Spatial Patterns (CSP) – enhances the discriminability between classes.03/13/13 IT Department, JECC
  24. 24. ProcessesFeature Extraction methods used to collect useful vectors• Log Variance• Power Density Estimation (PSD)• Wavelet Packet Decomposition (WPD)03/13/13 IT Department, JECC
  25. 25. Processes• Principle Component Analysis (PCA) -reduce the dimensionality of the feature vector• Classification Method - to build classifier which discriminate between labels. Linear Discriminant Analysis (LDA) is used03/13/13 IT Department, JECC
  26. 26. Electroencephalography (EEG)03/13/13 IT Department, JECC
  27. 27. Applications• Medicinal• Military• Bioengineering• Brain operated wheelchair• Multimedia and Virtual Reality03/13/13 IT Department, JECC
  28. 28. Conclusion• Enables people to communicate and control appliances with use of brain signals• Open gates for disabled people.• Development of new brain imagining techniques• Numerous future applications03/13/13 IT Department, JECC
  29. 29. Bibliography• Toward Inexpensive and Practical Brain Computer Interface by Hamzah S. AlZu’bi Nayel S. Al-Zubi Waleed Al-Nuaimy• Robot Navigation using Brain-Computer Interfaces by Athanasios Vourvopoulos and Fotis Liarokapis03/13/13 IT Department, JECC
  30. 30. Bibliography• A general framework of Brain-Computer Interface with Visualization and Virtual Reality Feedback by Gufei Sun, Kuangda Li, Xiaoqiang Li, Bofeng Zhang, Shizhong Yuan, Gengfeng Wu03/13/13 IT Department, JECC
  31. 31. Thank You03/13/13 IT Department, JECC