Week 18 (3/14/2021)

Following the presentation to Loyola Marymount University's (LMU) Electrical Engineering faculty, the team focused on collecting signals from the brain. The team also reviewed PLX-DAQ, a software that acquires data from a microcontroller and positions the collected data into columns in an excel datasheet, to make it easier for the MATLAB machine learning algorithm to process the data collected from the EEG helmet. Figure 1 illustrates the tool PLX-DAQ.

Figure 1: PLX-DAQ Main Interface

The team has also been researching methods for quickly developing the EEG helmet. Figure 2 illustrates the Ultracortex Mark III helmet design that the team has found (https://github.com/OpenBCI/Ultracortex/tree/master/Mark_III_Nova). The team has been in communication with the Engineering Design Center at LMU to determine the possibility of them being able to print out the helmet for rapid EEG helmet development.

Figure 2: Ultracortex Mark IIl 3D Printed EEG Helmet

THIS WEEK

Tyler

• Presented current progress to Loyola Marymount University's Electrical Engineering faculty

• Performed data collection from the EEG circuit

• Testing out the functionality of PLX-DAQ

Mark

• Presented current progress to Loyola Marymount University's Electrical Engineering faculty

• Analyzed and reviewed the data being collected from the EEG circuit
  

NEXT WEEK

Tyler

• Continue to collect data from the EEG circuit and perform any necessary circuit debugging

• Further test the functionality PLX-DAQ

Mark

• Continue to edit MATLAB code for improvements

• Assist Tyler on data collection

Meeting with Dr. Asghari: Dr. Asghari mentioned that if we would like to remove some of the data is being collect from movements that we could apply a high pass filter. The team will look into developing the high pass filter digitally.