Brain computer interface
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- 2. Simulate a Microcontroller With the help of Brain Wave Patterns To Trigger a Specific Course of Action is done by BCI process. A brain-computer interface (BCI), sometimes Called a Direct neural interface or a brain- machine interface, is a direct communication pathway between a human and an external device For these purpose , A Electroencephalograph is chosen for measuring the impedance of the brain waves there by generating a EEG graph. By Analyzing these EEG graph And Trigger a specific course of action on a microcontroller circuit. 2
- 3. By conducting experiments, we found out that simple activities like blinking of eye, movement of legs, and movement of arms produced a specific wave in the brain. The peaks in the waveform denote the action, there by triggering the course of action. In the long run, the triggering could be used in highly complicated circuits like an advanced security system. 3
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- 17. Delta Wave Theta wave Alpha wave Mu wave Beta wave Gamma waves 17
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- 21. An Example of Playing an Game 21
- 22. Controlling a wheel chair 22
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- 26. Jens Naumann, a man with acquired blindness, being interviewed about his vision BCI on CBS's The Early Show 26
- 27. User has a EEG cap on. By thinking about left and right hand movement the user controls the virtual keyboard with her brain activity. Virtual Keyboards 27
- 28. Advantages of processing EEG signal using µC • Reduce power consumption • Reduce system implementation cost • Reduce space • Reduce maintenance 28
- 29. Brain to Microcontroller Interfacing EEG acquisition Filtering Amplification ADC & Sampling Processing 29
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- 32. Interface • Begins at surface electrode location • Each electrode is attached to skin • Electrode material will not interact chemically with skin • Reference electrode voltage is subtracted from signal electrode 32
- 33. Filter • Situated Between interface and Amplifier • Notch filter and LPF • Passive filters • Notch filter remove 60Hz supply noise • LPF remove signals above 50Hz 33
- 34. Amplification • Zero trim remove dc offset • Applied to signal amplifier • Gain can be adjusted • o/p will not exceed ADC I/P range • Removing dc offset 34
- 35. Signal Processing • Signal is applied to ADC channel’s of µC • small conversion time • Conversion : CH1,CH2…..CH8 • Data send to µC2 • µC2 store it to flash drive and compare with look up table. • Control the output pins 35
- 36. Sampling • Done by µC • Nyquest sampling Fs ≥ 2Fm Fm= 50 Hz • Fs must be ≥ 100 Hz • Usually 1 KHz and above is used 36
- 37. Requirements of Op-Amp • High input impedance (> 10 MΩ) • Gain > 100 • High CMMR (> 100 dB) • Low offset voltage (mV) • Very small bias current (nA) • Operating voltage ±5 37
- 38. Requirements of µC • Speed - 25MHz • Memory – 2kB RAM & 32kB ROM • 8-channel ADC with 8 or 10 bit resolution • Serial communication ports (SPI,USART,I2C) 38
- 39. File format for 8 bit ADC sample d1 d2 d3 d4 d5 d6 d7 d8 t1 d1-d8 represent the sampled byte from each channel t1 represents the triggering and control bits 39
- 40. With The Help of Brain Wave Patterns We Could Trigger A Specific Course of Action And Hence Successfully Simulate A Microcontroller 40 CONCLUSION
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