Project Week 7

All Project Weekly Report

Goals (for the next two weeks)

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

Working on the backstrap for the model in fusion.

Diego Pena

Coordinator and Fusion Specialist

This week, I successfully located the filament and shifted my focus to developing the posterior structure of the head. My efforts were dedicated to carefully constructing and refining this section, paying close attention to both form and functionality. I experimented with different approaches to ensure structural integrity while maintaining the intended aesthetic, iteratively improving the design through testing and adjustment. This phase allowed me to better understand how the back portion integrates with the overall head structure, setting a solid foundation for the next stages of development.

These are examples of us working on the electrodes placement. On the second photo you can see the wiring for the electrodes.

Jacob Rubin

Electronics Specialist and Lead Designer

This week, I located the filament and focused on developing the posterior structure of the head. In parallel, I worked on the brain signal interface, troubleshooting the wiring connected to the electrodes to ensure accurate signal transmission. To improve signal quality, I added a low-pass filter and began redesigning the schematics for greater efficiency and reliability. These efforts involved iterative testing, careful adjustment, and integration with the overall design. This phase not only refined the structural elements but also strengthened the electronic functionality, laying a solid foundation for the next stages of development.

Vihan Patel

Researcher and Historian

This week, I researched how machine learning can be used to better interpret EEG brain wave signals, especially for identifying patterns that are difficult to detect with traditional methods. This supports the idea that it could improve our project’s accuracy. I will continue this research next week.

I also helped update the project report, worked on designing the solution, and contributed a bit to the Fusion portion of the project.

In MATLAB, frequencies in a signal can be separated using the Fast Fourier Transform (FFT) and filters. First, the FFT converts the signal from the time domain into the frequency domain so the different frequency components can be identified. Then, filters such as bandpass, low-pass, or high-pass filters can isolate specific frequency ranges and remove unwanted noise.

Jeremy Dinh

Lead Coder and Technical Documentation Lead

This week, I worked on refining the code related to data plotting and encountered performance issues, as the plotting process was running slowly. In addition, I explored additional MATLAB commands for use with the Raspberry Pi, including basic functions for reading pin values and controlling outputs.

This is a GIF which shows the example (to the right) running and updating the x-axis of the graph. However, at some point, the updating begins to slow down.

The above picture is an example I made on a potential way that the graph reading the brainwaves' frequency can update as the data is continuously being read.

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