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Brain Computer Interface

                   By,
               Ajay George
                  S8 - IT

03/13/13       IT Department, JECC
What is BCI
• Direct communication pathway between the
  brain and an external device

• Reads electrical signals from brain

• Signals translated into a digital form

03/13/13          IT Department, JECC
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
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
How BCI work




03/13/13     IT Department, JECC
How BCI work




03/13/13     IT Department, JECC
How BCI work

                        • Uses optical nerves
                          for image input
                        • Camera input
                          directed to brain



03/13/13     IT Department, JECC
Types of BCI
• Invasive
• Partially Invasive
• Non-Invasive




03/13/13          IT Department, JECC
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 vision

03/13/13         IT Department, JECC
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 implanted
03/13/13         IT Department, JECC
Non-Invasive BCI
• Easy to wear
• produce poor signal
• dispersing the
  electromagnetic
  waves created by
  the neurons

03/13/13         IT Department, JECC
Recording Domains




03/13/13       IT Department, JECC
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 required

03/13/13          IT Department, JECC
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
MRI technology




03/13/13      IT Department, JECC
Magnetoencephalography (MEG)
• Magnetic Field of 10-15 T
  to 10-13 T
• S.Q.U.I.D Sensors are
  required
• Shielded room is needed



03/13/13          IT Department, JECC
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 cost

03/13/13          IT Department, JECC
Electroencephalography (EEG)




Emotiv Cap, 14 Electordes,
Wireless connection.             Commercial BCI from NeuroSky
03/13/13               IT Department, JECC
Electroencephalography (EEG)




           P300

03/13/13          IT Department, JECC
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
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 awareness

03/13/13         IT Department, JECC
Electroencephalography (EEG)




           System Block Diagram



03/13/13           IT Department, JECC
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
Processes
Feature Extraction methods used to collect
  useful vectors
• Log Variance
• Power Density Estimation (PSD)
• Wavelet Packet Decomposition (WPD)


03/13/13         IT Department, JECC
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 used
03/13/13          IT Department, JECC
Electroencephalography (EEG)




03/13/13      IT Department, JECC
Applications
•   Medicinal
•   Military
•   Bioengineering
•   Brain operated wheelchair
•   Multimedia and Virtual Reality


03/13/13          IT Department, JECC
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 applications

03/13/13        IT Department, JECC
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 Liarokapis


03/13/13        IT Department, JECC
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 Wu



03/13/13        IT Department, JECC
Thank You




03/13/13   IT Department, JECC

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Brain Computer Interface ppt

  • 1. Brain Computer Interface By, Ajay George S8 - IT 03/13/13 IT Department, JECC
  • 2. What is BCI • Direct communication pathway between the brain and an external device • Reads electrical signals from brain • Signals translated into a digital form 03/13/13 IT Department, JECC
  • 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. 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. How BCI work 03/13/13 IT Department, JECC
  • 6. How BCI work 03/13/13 IT Department, JECC
  • 7. How BCI work • Uses optical nerves for image input • Camera input directed to brain 03/13/13 IT Department, JECC
  • 8. Types of BCI • Invasive • Partially Invasive • Non-Invasive 03/13/13 IT Department, JECC
  • 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 vision 03/13/13 IT Department, JECC
  • 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 implanted 03/13/13 IT Department, JECC
  • 11. Non-Invasive BCI • Easy to wear • produce poor signal • dispersing the electromagnetic waves created by the neurons 03/13/13 IT Department, JECC
  • 12. Recording Domains 03/13/13 IT Department, JECC
  • 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 required 03/13/13 IT Department, JECC
  • 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. MRI technology 03/13/13 IT Department, JECC
  • 16. Magnetoencephalography (MEG) • Magnetic Field of 10-15 T to 10-13 T • S.Q.U.I.D Sensors are required • Shielded room is needed 03/13/13 IT Department, JECC
  • 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 cost 03/13/13 IT Department, JECC
  • 18. Electroencephalography (EEG) Emotiv Cap, 14 Electordes, Wireless connection. Commercial BCI from NeuroSky 03/13/13 IT Department, JECC
  • 19. Electroencephalography (EEG) P300 03/13/13 IT Department, JECC
  • 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. 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 awareness 03/13/13 IT Department, JECC
  • 22. Electroencephalography (EEG) System Block Diagram 03/13/13 IT Department, JECC
  • 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. Processes Feature Extraction methods used to collect useful vectors • Log Variance • Power Density Estimation (PSD) • Wavelet Packet Decomposition (WPD) 03/13/13 IT Department, JECC
  • 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 used 03/13/13 IT Department, JECC
  • 27. Applications • Medicinal • Military • Bioengineering • Brain operated wheelchair • Multimedia and Virtual Reality 03/13/13 IT Department, JECC
  • 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 applications 03/13/13 IT Department, JECC
  • 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 Liarokapis 03/13/13 IT Department, JECC
  • 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 Wu 03/13/13 IT Department, JECC
  • 31. Thank You 03/13/13 IT Department, JECC