Brain Computer Interface allows direct communication between the brain and external devices. It reads electrical signals from the brain and translates them into a digital format. Research on BCIs started in the 1970s with basic sensors implanted in rats, mice, monkeys and humans. Today, BCIs can be invasive, partially invasive or non-invasive. Invasive BCIs are implanted directly into the brain to provide high quality signals, while non-invasive BCIs like EEGs record electrical activity from the scalp. BCIs have applications in medicine, military technology, and assisting people with disabilities.

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.
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5. How BCI work
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6. How BCI work
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7. How BCI work
• Uses optical nerves
for image input
• Camera input
directed to brain
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8. Types of BCI
• Invasive
• Partially Invasive
• Non-Invasive
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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
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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
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11. Non-Invasive BCI
• Easy to wear
• produce poor signal
• dispersing the
electromagnetic
waves created by
the neurons
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12. Recording Domains
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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
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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.
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15. MRI technology
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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
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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
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18. Electroencephalography (EEG)
Emotiv Cap, 14 Electordes,
Wireless connection. Commercial BCI from NeuroSky
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19. Electroencephalography (EEG)
P300
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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.
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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
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22. Electroencephalography (EEG)
System Block Diagram
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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.
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24. Processes
Feature Extraction methods used to collect
useful vectors
• Log Variance
• Power Density Estimation (PSD)
• Wavelet Packet Decomposition (WPD)
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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
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26. Electroencephalography (EEG)
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27. Applications
• Medicinal
• Military
• Bioengineering
• Brain operated wheelchair
• Multimedia and Virtual Reality
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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
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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
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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
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31. Thank You
03/13/13 IT Department, JECC