BRAIN MACHINE INTERFACE

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BRAIN MACHINE INTERFACE

  1. 1. SEMINAR BRAIN MACHINE INTERFACEPRESENTED BY GUIDED BYSRUTHI.S.KUMAR MAHESWARI R ROLL NO:53 GUEST LUCTURER
  2. 2. INTRODUCTION Brain Machine interface is a new communication link between a functioning human brain and the outside world. Electronic interfaces with the brain that can send and receive signals from the brain. Signals from the brain are taken to brain via implants and transforms the mental decision to control signals
  3. 3. THE HUMAN BRAIN relevant part - cerebral cortex. Cerebral cortex is responsible for many higher order functions like problem solving, language comprehension and processing of complex visual information.
  4. 4. MAIN PRINCIPLEBioelectrical activity ofnerves and muscles .When the neuron fires, thereis a voltage change across thecell which is monitored andanalyzed.A neuron depolarizes togenerate an impulse; thisaction causes changes in theelectric field around theneuron.1 for impulse generated and 0for no impulse
  5. 5. BMI APPROACHES1. Pattern recognition approach based on mental tasks.2. Operant conditioning approach based on the self-regulation of the EEG response.
  6. 6. 1.INVASIVE directly implanted into the grey matter. produce the highest quality signals prone to building up of scar- tissue
  7. 7. 2.PARTIALLY INVASIVE Implanted inside the skull but rest outside. produce better resolution signals than non-invasive BCIs Electrocorticography (ECoG) uses the same technology, the electrodes are embedded in a thin plastic pad that is placed above the cortex.
  8. 8. 3.NON INVASIVE Electroencephalography-recording is obtained by placing electrodes on the scalp with a conductive gel or paste. FMRI(Functional Magnetic Resonance Imaging) exploits the changes in the magnetic properties of hemoglobin as it carries oxygen. Activation of a part of the brain increases oxygen levels there increasing the ratio of oxyhemoglobin to deoxyhemoglobin.
  9. 9. BLOCK DIAGRAM
  10. 10. MAIN PARTSIMPLANT DEVICESSIGNAL PROCESSING SECTIONEXTERNAL DEVICEFEEDBACK SECTION
  11. 11. 1.IMPLANT DEVICESImplanted array ofmicroelectrodes intothe frontal and parietallobes.provide the electricalcontact between theskin which transformsthe ionic current onthe skin to theelectrical current inthe wires.
  12. 12. 2.SIGNAL PROCESSING MULTICHANNEL ACQUISITION SYSTEMS At this section amplification, initial filtering of EEG signal and possible artifact removal takes place. SPIKE DETECTION Spike detection will allow the BMI to transmit only the action potential waveforms. SIGNAL ANALYSIS In this stage, certain features are extracted from the preprocessed and digitized EEG signal which are input to the classifier. Classifier recognize different mental tasks.
  13. 13. 3.EXTERNAL DEVICES The classifier’s output is the input for the device control. The device control simply transforms the classification to a particular action. Examples are robotic arm, thought controlled wheel chair etc
  14. 14. 4.FEEDBACK Feedback is needed for learning and for control. In the BMIs based on the operant conditioning approach, feedback training is essential for the user to acquire the control of his or her EEG response. The BMIs based on the pattern recognition approach and using mental tasks do not definitely require feedback training.
  15. 15. PROS AND CONS Can help people  The signals are with inabilities to weak and are prone control wheel chairs to interference . or other devices  Surgery to brain with brain activity. might be risky and To develop better cause brain death. sensing system.  There are chemical BCIs are linguistic reactions involved in independent and can brain which BCI be used any where devices cannot pick across the world. up.
  16. 16. APPLICATION1. Auditory and visual prosthesis 2.Functional-neuromuscular stimulation (FNS) 3.Prosthetic limb control
  17. 17. PROJECTS Honda Asimo Control
  18. 18. 2.Gamingcontrol 3.Brain gate 4.Bionic eye
  19. 19. CONCLUSION A potential therapeutic tool. Brain-Computer Interface (BCI) is a method of communication based on voluntary neural activity generated by the brain. have the ability to give people back their lost capabilities.
  20. 20. REFERENCES P. Sajda, K-R. Mueller, and K.V. Shenoy, eds., special issue, “Brain Computer Interfaces,” IEEE Signal Processing Magazine,Jan. 2008 Wolpaw, J.R. et al. (2002) Brain–computer interfaces for communication and control. Clin. Neurophysiol. 113, 767–791 Birbaumer, N. (2006) Brain–computer-interface research: coming of age. Clin. Neurophysiol. 117, 479–483 www.betterhumans.com www.howstuffworks.com

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