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LookOmotive First Seminar

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LookOmotive First Seminar

  1. 1. LookOmotive<br />Think About … Move Around<br />
  2. 2. Team<br /><ul><li>Supervisors
  3. 3. Prof. Dr. Mostafa Gad
  4. 4. Dr. Howaida Abd El Fatah
  5. 5. Dr. Safwat Hamad
  6. 6. T.A Ramy Medhat
  7. 7. Members
  8. 8. Mina Osama Fayek - Computer Science department
  9. 9. Mona Mohamed - Scientific Computing department
  10. 10. Mostafa Saeed - Scientific Computing department
  11. 11. Nour Galal - Information Systems department
  12. 12. Ossama Moussa - Scientific Computing department</li></li></ul><li>Agenda<br /><ul><li>Problem statement
  13. 13. Objective
  14. 14. Motivation
  15. 15. Description
  16. 16. LookOmotive overview
  17. 17. Previous approaches
  18. 18. EEG signal processing
  19. 19. Basic system architecture
  20. 20. Time Plan
  21. 21. Tools, technologies and SWE methodology
  22. 22. References</li></li></ul><li>Problem Statement<br /><ul><li>For the time being handicaps need human assistance to perform their everyday activities.</li></li></ul><li>Objectives<br /><ul><li>Help Handicaps to live independently without others assistance.
  23. 23. Learn about EEG signal processing to detect cognitive states.
  24. 24. Develop a generic SDK that can support different applications (Ubiquitous environment).
  25. 25. Dealing with unfamiliar technologies and tools.
  26. 26. To be a good representative of Egyptian developers (Imagine Cup: Poland 2010)</li></ul>-for more info…<br />List location or contact for specification (or other related documents)<br />
  27. 27. Motivation<br /><ul><li>After considering the way handicaps lead their lives, we have decided to integrate our technical background with science to provide them with means of making their lives better.</li></li></ul><li>Description<br /><ul><li>LookOmotive overview
  28. 28. Previous approaches
  29. 29. EEG signals
  30. 30. Basic system architecture</li></li></ul><li>LookOmotive Overview<br />
  31. 31. LookOmotive overview<br /><ul><li>LookOmotive is an assisting technology that helps handicaps to control their wheelchair based on their cognitive state of mind .
  32. 32. LookOmotive user should think about an action (Forward, Backward, Right, Left or Stop).
  33. 33. Brian signals should be read, and then processed by LookOmotive.
  34. 34. LookOmotive should control the wheelchair according to the detected state.</li></li></ul><li>Previous approaches <br /><ul><li>Cap2Monitor [2009]: Computer desktop control application based on detecting EEG status of specific muscular actions (Eye blinking & Focus).</li></li></ul><li>EEG Signals<br />
  35. 35. EEG Signals<br /><ul><li>Introduction
  36. 36. Stands for electroencephalogram.
  37. 37. The electroencephalogram (EEG) is a recording of the electrical activity of the brain from the scalp.
  38. 38. The brain nerve cells in the brain produce signals that are called action potentials.
  39. 39. Measured in microvolts (µV) .</li></li></ul><li>EEG Signals<br /><ul><li>Signal detection
  40. 40. Electrodes: Small metal discs placed on the scalp in special positions.
  41. 41. These positions are set according to the International 10/20 System</li></li></ul><li>EEG Signals<br /><ul><li>Montages
  42. 42. The manner in which pairs of electrodes are connected to each amplifier of the EEG machine.
  43. 43. Differential amplifiers measure the voltage difference between the two signals at each of its inputs.
  44. 44. The resulting signal is amplified and then displayed as a channel of EEG activity.</li></li></ul><li>Basic System Architecture<br />
  45. 45. Basic System Architecture <br />Emotiv<br />EPOC SDK<br />EPOC headset <br />by Emotiv Systems<br />Wheelchair<br />
  46. 46. Basic System Architecture <br />Why Not?<br /><ul><li>Emotive SDKs</li></li></ul><li>Basic System Architecture (Modified) <br />Emotiv<br />EPOC SDK<br />EPOC headset <br />by Emotiv Systems<br />Wheelchair<br />
  47. 47. Basic System Architecture (Modified) <br />Emulator<br />LookOmotive<br />SDK<br />Service<br />Config<br />Wheelchair<br />UI<br />
  48. 48. Initial Time Plan<br />
  49. 49. Initial Time Plan<br />Emulator design( 2 weeks)<br />Emulator implementation<br /> (1 month)<br />Research (EEG signal detection and processing )<br />SDK design (2 weeks)<br />SDK implementation <br />(4 ½ months )<br />Assembly (3 weeks)<br />Algorithms design (3 ½ months)<br />Documentation (3 weeks)<br />Testing<br />
  50. 50. Tools<br />
  51. 51. Tools and methodologies<br /><ul><li>Tools & Technologies:
  52. 52. Microsoft .NET Framework (Visual Studio 2008)
  53. 53. Microsoft Office Live Workspace
  54. 54. Operating Systems:
  55. 55. Windows XP Embedded (XPe)
  56. 56. Hardware
  57. 57. x86 based development board
  58. 58. Software development methodology:
  59. 59. Agile(Scrum)</li></li></ul><li>Web Blog<br /><ul><li>http://lookomotive.wordpress.com/</li></ul> News, updates and code samples ..<br />
  60. 60. References<br /><ul><li>Books
  61. 61. EEG signal processing - by Sanei, Saeid / Chambers, J. A.#v=onepage
  62. 62. EEG signal classification for brain computer interface application by </li></ul>Y. P. A. Yong, N. J. Hurley, and G. C. M. Silvestre Computer Science, University College Dublin<br /><ul><li>Electroencephalogram: Basic principles, clinical applications and related fields
  63. 63. Determining user state and mental task demand from electroencephalographic data
  64. 64. Papers
  65. 65. Introduction to EEG - by Smith, E.J
  66. 66. ESTIMATING COGNITIVE STATE USING EEG SIGNALS - Tian Lan, Andre Adami, Deniz Erdogmus, Misha Pavel
  67. 67. EEG Signal Classification with Different Signal Representations</li></li></ul><li>Thank You!<br />

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