1. Electrical and Computer Engineering Team14: BMW Brainwave Manipulated Wagon Midway Design Review

2. 2 Electrical and Computer Engineering Team 14 Members Zijian Chen CSE Tiffany Jao CSE Man Qin EE Xueling Zhao EE Faculty Advisor: Qiangfei Xia

3. 3 Electrical and Computer Engineering Outline  Review  System Requirement  Block Diagram  Individual Responsibility  MDR Demo  CDR Schedule

4. 4 Electrical and Computer Engineering Review: Problem Statement  People with physical disability is relatively dependent on others Limited strength to control wheelchair Solution: BMW  Demonstrates brainwave (EEG) control using robotic car

5. 5 Electrical and Computer Engineering Outline  Review  System Requirement  Block Diagram  Individual Responsibility  MDR Demo  CDR Schedule

6. 6 Electrical and Computer Engineering What is BMW? A brainwave controlled robotic car!

7. 7 Electrical and Computer Engineering System Requirement  Computer application GUI Database  Compatible with different user training system  Remote Car Controls: move forward, speed up, stop, and etc.

8. 8 Electrical and Computer Engineering Outline  Review  System Requirement  Block Diagram  Individual Responsibility  MDR Demo  CDR Schedule

9. 9 Electrical and Computer Engineering Block Diagram Computer Arduino/ C# Application USB serial Write MySQL Database XBEE:TX Signal Processing Command Algorithm User Interface XBEE: RX ArduinoMotor Power Supply Neurosky headset Bluetooth v3.0 ThinkGear Packet Robotic Car TX Arduino Module Man Qin Zijian Chen Xueling Zhao Tiffany Jao

10. 10 Electrical and Computer Engineering Block Diagram Computer Arduino/ C# Application USB serial Write MySQL Database XBEE:TX Data Analyze Command Algorithm User Interface XBEE: RX ArduinoMotor Power Supply Bluetooth v3.0 ThinkGear Packet Robotic Car TX Arduino Module Man Qin Zijian Chen Xueling Zhao Tiffany Jao Neurosky headset

11. 11 Electrical and Computer Engineering Outline  Review  System Requirement  Block Diagram  Individual Responsibility  MDR Demo  CDR Schedule

12. 12 Electrical and Computer Engineering Data Retrieval: Neurosky Headset Neurosky HeadsetLaptop Bluetooth v3.0 Thinkgear.dill Poor Signal Concentration/ Meditation Alpha/Beta/Theta Power Raw Data  Retrieve attention level and corresponding raw EEG data  Save.txt file for further analysis

13. 13 Electrical and Computer Engineering Graphical User Interface  Development language: C# Warning message Stimuli

14. 14 Electrical and Computer Engineering Graphical User Interface: State Diagram

15. 15 Electrical and Computer Engineering Command Algorithm High Attention List Sorting Calculate Classify Point Attention Level Low Attention Concentrated Not Concentrated Two consecutive low attention level Input point > 90 % * classify point

16. 16 Electrical and Computer Engineering Data Collection and Analysis  Why? Multiple Commands Achieve more reasonable algorithm

17. 17 Electrical and Computer Engineering Data Collection and Analysis: Assumption  Different kinds of concentration: Increased memory – High Theta (3.5 – 6.7 Hz) Increased focus and awareness – High Alpha (11-14Hz) Increased conscious thinking – High Beta (14-30 Hz) "Brain Wave States & How To Access Them.” Brainwaves Frequencies Change States of Consciousness. 1 Jan. 2005. Web. 22 Nov. 2014.

18. 18 Electrical and Computer Engineering Data Analysis: Graph *data is provided by the headset

19. 19 Electrical and Computer Engineering Data Analysis: Challenges  No standard experiment is defined during data acquisition  Power spectrum is less stable than attention level  No way to know the time delay(FFT)  Power Spectrum are provided once per second (FFT)

20. 20 Electrical and Computer Engineering FFT  Replace the attention level with other parameters  Corresponding alpha wave and attention level comparison  Matlab – perform FFT C# will replace Matlab for FFT  Provide a platform for further experiment

21. 21 Electrical and Computer Engineering FFT Result: Alpha Spectrum vs Attention Level

22. 22 Electrical and Computer Engineering Outline  Review  System Requirement  Block Diagram  Individual Responsibility Software Training System Research  MDR Demo  CDR Schedule

23. 23 Electrical and Computer Engineering Proposed MDR Deliverables  Demonstration of functioning algorithm Controlling LED on/off Stable result  Demonstration of graphical user interface User determine control time Display attention level

24. 24 Electrical and Computer Engineering Outline  Review  System Requirement  Block Diagram  Individual Responsibility Software Training System Research  MDR Demo  CDR Schedule

25. 25 Electrical and Computer Engineering Proposed CDR Deliverables  Remotely control robotic car  Improved Command Algorithm  Utilize FFT result and classifier Try to replace attention level  More user-friendly training interface Graph Database for training interface

26. 26 Electrical and Computer Engineering Schedule: Ghatt Chart 11/24/201411/30/201412/7/201412/14/201412/21/201412/28/20141/4/20151/11/20151/18/20151/25/20152/1/20152/8/20152/15/20152/22/2015 MDR draft report (All) MDR final report (All) XBEE TX/RX Robotic Car integration of robotic car and TX/RX integration of RX and GUI (Tiffany+Man) define experiment method (All) FFT in c# (Beysian) Classifier Integration of FFT & Beysian with Training interface (Xueling+Tiffany+Zijian) Peforming Experiment with alrogithm (Xueling+Tiffany+Zijian) Database GUI improvement

27. 27 Electrical and Computer Engineering Thank you Any Question?

28. 28 Electrical and Computer Engineering PDR Feedback Why not use an embedded solution?  We decided to build C# application instead of embedded solution Need to experiment to find a usable stimuli Easy to set up an experiment interface with C# application

29. 29 Electrical and Computer Engineering Previous Ver.

30. 30 Electrical and Computer Engineering Naïve Bayes Classifier  Probabilistic classifier based on applying Bayes’ theorem. Bayes Theorem:  Advantage : Better performances when the amount of input is large Easy to implement and requires O(n) run time. A way to determine alpha and beta relationship with attention level

31. 31 Electrical and Computer Engineering How To Use Naïve Bayes Classifier P (High Attention) = 40 /60 P (Low Attention) = 20 / 60 Now, we have a new input X P (X | High Attention)=1/ 40 P (X | Low Attention) 3 /30