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Brain Wave Group 1

Brain Wave Group 1. Final Presentation James Lin Son Phan Michael Oduselu. Purpose. Research Thought Controlled Applications Observe how mind control can be used Open new means of communication Enhance quality of life and mental well-being. Potential Applications. EEG Biofeedback

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Brain Wave Group 1

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  1. Brain Wave Group 1 Final Presentation James Lin Son Phan Michael Oduselu

  2. Purpose • Research Thought Controlled Applications • Observe how mind control can be used • Open new means of communication • Enhance quality of life and mental well-being

  3. Potential Applications • EEG Biofeedback • Control brain rhythms • Computer Control & Communication • Thought controlled systems • Entertainment & Virtual Reality • Brain influcenced music and graphics • Adaptive Virtual Worlds

  4. Applications Cont. • Education and Research • Brainwave experiments and labs • Military and Commercial Applications • Monitor health and concisousness (NASA) • Controlling planes (Air Force) • Monitor consumer reactions to Ads and Products

  5. Research Background • John Chapin • Trained 6 rats to push a lever • Computer established pattern for pushing lever • Mice pushed lever with thought • Gloria Calhoun • Used brainwaves to pilot a flight simulator

  6. EEG • Stands for Electroencephalogram • Records bioelectric activity of brain • Monitors Frequencies from 0.5 to 20 Hz • Dependent on brain activity • Age, arousal level, sleeping state, cerebral dysfunctions

  7. EEG Machines Available • Brainmaster • 2-channel general purpose brainwave monitor • Performs data storage, retrieval, real-time signal processing, display, and feedback • WaveRider Jr • Has Audiovisual feedback • More integrated and configured for easy use but less sophisticated

  8. EEG Machines Cont. • POD • EEG feedback machine • Used to improve self in areas ranging from studying to golf • ProComp • 8 channel machine capable of EEG, EMG, EKG, skin conductance, temperature, heart rate, etc. • Expensive

  9. Goals • Tackle first task of reading brainwaves • Research and design EEG circuit • Assemble EEG circuit • Read brainwave on oscilloscope

  10. Design Objective • Build EEG Circuit • Get parts • Use BrainMaster schematicsd • Test/Optimize EEG • Test for heartbeat • Test for brainwave • Solder final circuit

  11. Previous Design • Amplifier didn’t work

  12. Revised Design • First step: EEG Monitor

  13. Amplifier Schematic

  14. Analysis Objectives • Understanding Circuit • Brain-Master Schematic • Part Functions • Implement Circuit in P-spice • Ideal Op-Amps • AD620 • OP90 • Simulate and Examine Result • Input and Output • Total Gain

  15. Implement Circuit in P-spice

  16. Simulate and Examine Result

  17. Continued…

  18. Specifications • Type: differential • Gain: 20,000 • Bandwidth: 1.7 – 34 Hz • Input Range 200uV • Output Range 4 V • CMRR >100dB

  19. Other components • Midpoint Voltage circuit

  20. Other components • Clean power source

  21. Navigation: Waves vs Emotion

  22. Heartbeat Test Results • Breadboard circuit measurement of heart beat • Second figure shows a close up. • Compare with EKG

  23. Assemble working circuit • Solder circuit together for better performance • Cleaner signal with better electrodes and pads • Flat signal = good sign

  24. Signal from head • Tested signal to amp by biting down. • First capture shows one bite. • Second capture shows 3 bites.

  25. Measure Brainwaves • Results from head show fluctuating signal between 3 and 30 Hz. • Wave compared to Brainmaster screenshot.

  26. Brain results cont. • Waves look similar • Need to use filtering to isolate frequency energy of wave in a specific time.

  27. FFT Response • FFT shows that range of frequncies is 0 – 30 Hz • Closer insepection shows a consistant frequency spike around 10 Hz. • Frequency corresponds to Alpha waves at front of head.

  28. Muscle induced response • First capture shows response of raising eyebrows once. • Second capture shows two eyebrow raises.

  29. Results continued • Capture shows signal created by a hard blink

  30. Conclusions • EEG amplifier worked well in collecting signals from the head. • Muscles signals were far easier to see and create. No training involved. • Application such as a vehicle requires instantaneous responses which muscle signals may be better suited for.

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