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BCI Brain Computer Interface. by Omar Nada & Sina Firouzi. Introduction. What is it A communication channel between brain and electronic device Computer to brain/Brain to computer Why we need it Medical purposes Repairing eyesight, hearing, movement of body parts

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bci brain computer interface

BCIBrain Computer Interface

by Omar Nada & Sina Firouzi

introduction
Introduction
  • What is it
    • A communication channel between brain and electronic device
    • Computer to brain/Brain to computer
  • Why we need it
    • Medical purposes
      • Repairing eyesight, hearing, movement of body parts
    • Entertainment and multimedia communications
      • Toys, video games, activity in virtual reality environments, controlling devices with thought, synthetic telepathy
    • Military
      • Mood control , commanding and telepresence
  • How does it work
    • Algorithms are used to translate brain activity into control signals
    • Brain can handle signals generated by electronic devices
overview
Overview

Source: wingsforlife.com

how does it work
How does it work
  • Brain’s electrical activity produced by firing of electrically charged neurons is observed by sensors
  • Invasive sensors
    • Electrodes are implanted directly into gray matter
      • High quality of signals, risk of scar-tissue
  • Partially invasive
    • Electrodes are implanted inside skull but not into gray matter
      • Lower quality, less risk of scar-tissue
  • Non-invasive
    • Signals are observed from outside the skull
      • Low quality as skull dampens signal, no surgery, no scar-tissue, safest method
    • Electroencephalography (EEG) by observing the wave of ions released by neurons
    • Magnetoencephalography (MEG) by observing magnetic fields produced in brain
    • Functional magnetic resonance imaging (FMRI)
  • This information is translated using algorithms and used by electronic devices and vice versa
bci projects
BCI Projects
  • Assist Arm Robot
    • Carleton University
    • BCI + Assist
  • Berlin Brain-Computer Interface
  • Health Care
1 assist arm robot
1) Assist ARM Robot
  • Early phase One degree of freedom Assist Arm
  • Uses nerves and force sensor as input
  • Assist in a desired motion ( for recovery)

MEG(using electrodes)

Biceps & triceps

Projected Motion

impedance control schema

Motion(force sensor)

Up & Down directions

assisted movement
Assisted Movement

force

sensor

electrodes

Initial movement

Assisted movement

challenges
Challenges
  • Same group muscles can control different joints
  • Body fat, muscle mass, muscle fatigue affect measurements
  • Different people give different values ( like PWM)
  • Lack of volunteers!!!! (especially for invasive methods)
  • Guessing the user Intensions!
work arounds solutions
Work Arounds / Solutions
  • Session Calibration
    • Using min and max values of voltages
  • Muscle Group Calibration
    • Run the above technique for all the group muscles used for readings
  • THEN: Work relatively
    • Use the session and group muscle boundaries to predict user intention
2 berlin bci
2) Berlin BCI
  • The Berlin Brain-Computer Interface: EEG-based communication without subject training

Benjamin Blankertz, Guido Dornhege, Matthias Krauledat, Klaus-Robert Müller, Volker Kunzmann, FlorianLosch, Gabriel Curio

  • Non-invasive
  • Key features
    • Use of well-established motor competences as control paradigms
    • High-dimensional features from 128-channel EEG
    • Advanced machine learning techniques
2 berlin bci1
2) Berlin BCI
  • Establishing a BCI system based on motor imagery that works without subject training
    • ‘Let the machine learn’
      • System automatically adapts to the specific brain signals of each user by using advanced techniques of machine learning and signal processing
  • It is possible to transfer the results obtained with regard to movement intentions in healthy subjects to phantom movements in patients with traumatic amputations.
  • High information transfer rates can be obtained from single-trial classification of fast-paced motor commands
3 health care
3) Health Care
  • Health care example
    • Repairing damaged hearing
      • Sounds are received by an external device and signals are sent to brain
    • Repairing damaged eyesight
      • A camera sends signals to brain
    • Helping people with spine injuriesand paralyzed limbs by electrically stimulating muscles
    • Moving paralyzed body parts with help of robotic parts
3 health care1
3) Health Care
  • Replacing damaged or lost body parts
    • Mechanical hands, fingers.
  • Helping people with severe paralysis to communicate with outside world using a computer.
  • Restore speech
    • Patient concentrates on a letter and computer receives and pronounces it
feasible future
Feasible Future
  • What is in research
    • Are people able to willingly fire specific neurons in real-time?
    • Images seen by human eyes have been recorded in black and white. Recording color images is in research
    • Recording dreams and thoughts
  • What is coming out soon
    • Affordable non invasive sensors
    • Calibration using heart rates ( more accurate results)
omar s view of the future
Omar’s view of the future
  • BCI
      • Better control algorithm to decode the brain activities (cheap non invasive) coming to reality
      • Check out TED video emotivby Tan Le
  • Application
          • ‘HandsFree’ Driving
          • Thinking Pattern Authentication
sina s view of the future
Sina’s view of the future
  • Virtual reality
    • Being able to interact with others in a virtual 3D environment without using muscles or mouse
  • Using electronic devices without touch or any muscle movement
  • Well functioning moving body parts
  • Mood control
    • Sending signals to your brain can improve your mood
conclusion
Conclusion
  • BCI = Brain + Computer + Communication Channel
  • BCI Applications
    • Carleton Assist ARM
    • Berlin BCI
    • Health applications
  • How we view the future from the BCI lens