Discount Megamind's Lowcost Electro Encephalogram(EEG)

The goal of the project is, to build a mobile and low-cost electroencephalography(EEG) device to measure brain electrical signals for educational purposes.

=Problem Definition=

Background
People know that the heart pumps blood, that the muscles contract, and that the brain thinks. But how does it think and how does it communicate? Currently, if you pulled a random person off the street, and asked how the brain transmitted a signal to the rest of their body, they would probably be unable to answer accurately. The main reason causing this knowledge gap is the inadequate funding and few realistic and engaging ways to illustrate how the brain functions in a traditional school system. Students having minimal knowledge regarding the most critical organ in their body is a substantial problem. This project aims at providing an inexpensive, consistent and easy-to-use solution to this problem. By creating an affordable electroencephalogram system for high school students to build and operate, teachers will be enabled to effectively demonstrate how the brain operates within its physical space.

Deliverables
 Improved EEG circuit board  Using Differential Amplifier Arduino-compatible PCB design   Improved EEG headset  A more aesthetically pleasing design​   Reduce cost  Recycled and low-cost materials</li> 3-D printing technology</li> </ul> </li> Document step-by-step video instructions  On how to build the device</li> To present work to Moscow High School</li> </ul> </li> Add a Graphical-User-Interface  To allow better data visualization and allow for machine learning analysis of brain waves for data interpretation</li> </ul> </li> </ul>

Specifications


=Design Considerations=

Software Considerations
In order to use machine learning to make guesses about a user's directional thinking or emotional state, sufficient test data needs to be generated so that the machine learning model can be trained. Because there is no identical EEG device to ours out there currently, there is no existing data that our machine learning model can train with. Therefore, creating a data set of brainwave information along with a labeling each sample with the appropriate directional thought or emotional state is necessary to have our machine learning model work correctly. We plan on generating this data set by scanning our team members' brains and applying the appropriate label to each sample.

=Project Learning= Headset Project Learning

Our main design goals for the headset is include adjustability mechanisms to allow for the headset to fit a wide range of head sizes.

We initially tried to achieve this goal by changing the diameter of the headset through a pin mechanism located in the back of the headset. This design proved to be hard to adjust, as the error tolerances of the 3D printing fabrication made it difficult to create a perfectly circular shape. This lead to complications in inserting the pin through the holes. It required two people to properly adjust the headset. To overcome this issue, we designed a compliant ratchet mechanism. This allowed for the user to adjust the diameter size of the headset without the help of another person.

Another design we created to provide the headset with more adjustability was to have a ball socket connection between the frame and electrode arms. This design initially worked well, as the ball socket allowed for two degrees of freedom. However, the joint quickly wore out and became loose. This is due to the plastic printing material having a low surface hardness, leading to the joint scrape off parts of the plastic during normal operation. The design we came up with to solve this problem was to create a cylindrical slot in the frame and insert the electrode arm vertically into this slot. While this removed the degrees of freedom for the electrode arms, it provides a stable base. It is also easily moved to the different connection points on the frame.

=Final Design=

=Validation=

=Team Members=

=Additional Documentation=

Project Schedule

Budget