Week 13 (2/01/2021)

This week the Team continued to work on the Capstone project. The low pass and high pass filters were designed using Multisim to verify its results prior to building it onto the breadboard. The electrodes, originally plugged into the breadboard, were removed and soldered into a perforated PCB board to reduce the amount of movement it had while plugged into the breadboard. The team thinks that the signal that is currently being collected at the end of the filters is either too noisy or has too much of a low amplitude to be detected by the oscilloscope.

The machine learning algorithm was progressed by plotting the different brainwaves from students watching educational videos (https://www.kaggle.com/wanghaohan/confused-eeg).

The image below illustrates the alpha brainwave of different students that were plotted using Matlab. Based on the video that the students were watching, it appears that one of the student's dents alpha brainwave rose increasingly at 121.846, which directly correlates to the 2:01-2:02 timestamp of the video. At the 2:01-2:02 timestamp of the video, a student corrects the professor on a mistake that the professor made on the board.

THIS WEEK

Tyler

• Built the low pass filter and high pass filter on the breadboard and tested both on Multisim and in real life

• Soldered the electrodes onto the perforated PCB board

Mark

• Plotted the different brainwaves of an EEG dataset and compared the dataset.

• Soldered the electrodes onto the perforated PCB board
  

NEXT WEEK

Tyler

• Build the next amplifier stage with another filter to collect a cleaner signal

Mark

• Continuing working with the EEG data to create a K-mean clustering machine learning algorithm using the aforementioned Kaggle dataset

Memo: The team is behind. The team spoke with Dr. Hossein Asghari to discuss issues that we were facing with the helmet. There is too much noise being collected. Mark is to review EEGLAB's code.