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BRAIN MACHINE INTERFACE

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  • 1. SEMINAR BRAIN MACHINE INTERFACEPRESENTED BY GUIDED BYSRUTHI.S.KUMAR MAHESWARI R ROLL NO:53 GUEST LUCTURER
  • 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. 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. 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. BMI APPROACHES1. Pattern recognition approach based on mental tasks.2. Operant conditioning approach based on the self-regulation of the EEG response.
  • 6. 1.INVASIVE directly implanted into the grey matter. produce the highest quality signals prone to building up of scar- tissue
  • 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. 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. BLOCK DIAGRAM
  • 10. MAIN PARTSIMPLANT DEVICESSIGNAL PROCESSING SECTIONEXTERNAL DEVICEFEEDBACK SECTION
  • 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. 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. 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. 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. 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. APPLICATION1. Auditory and visual prosthesis 2.Functional-neuromuscular stimulation (FNS) 3.Prosthetic limb control
  • 17. PROJECTS Honda Asimo Control
  • 18. 2.Gamingcontrol 3.Brain gate 4.Bionic eye
  • 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. 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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