Project Week 6

All Project Weekly Report

Goals

Finishing Wiring and testing. Issues with the parts we ordered. Parts connect and work well but the circuit is not reading correctly (Jacob)
Start Printing the fusion model. Will be taking multiple attempts because there may be many errors with how the print comes out (Diego)
Pre processing and real time processing (Jeremy)
Weekly Report. Continue learning Machine learning until the next phase (Vihan)

Design Process

Construct and test

Both are example of the flexible filament we tested.

Diego Pena

Coordinator and Fusion Specialist

Tested different thickness levels using TPU to see how the print would turn out. This helped build a better understanding of how the material will print for the Fusion helmet. Also continued working on the Fusion helmet design.

This was the amplifier that we tested which worked perfectly.

Jacob Rubin

Electronics Specialist and Lead Designer

This week, we tested the amplifier and confirmed that it started working perfectly and was able to successfully amplify a signal. However, it eventually stopped functioning after some time. Next week, we will continue troubleshooting the issue while focusing on designing a more reliable and stable solution.

Vihan Patel

Researcher and Historian

Reading the influence on Machine earning on the EEG. We want to use Machine learning to analyze the brain waves. It has worked to analyzes potential seziures and was 96% correct. So I believe that using machine learning should enhance our project. I will continue my research next week. Also created an updated project report on Wensday and Thursday. I was working on the Desinging the solution.

This table compares different studies that used EEG signals to classify mental states with eyes open and eyes closed, showing the participants, methods, and accuracy of each approach.

Jeremy Dinh

Lead Coder and Technical Documentation Lead

Look up examples and tested different examples of code found online and researched more of what is needed. The plan for the progression of the code was made as well.

Gather the data through the use of MatLab and a raspberry pi
Use a filter bandpass to get rid of interference
Plot the data in real-time
Apply machine learning by finding an example that separates the different signals between a hand movement or leg movement.
Put it to an outputted signal

Plans for next two weeks:

Finish a rough draft of the code that can read the brainwave from a raspberry pi.
finish the bandpass filter system
find a way to read the data in realtime

The image shows MATLAB code applying a bandpass filter and displaying the spectrogram and filter response of the signal.

Page updated

Report abuse