MVP/Proof-of-Concept Journal Updates, March 13th 2020 —

Milecia recorded our EEG data using her OpenBCI device, which has four electrodes. She recorded (100) 1-second bursts of EEG data, which Ryan used to train a predictive model with 97% accuracy! We built a back-end Python API — which, when called upon, will return a number 0, 1, 2, 3, 4, or 5. Those numbers correspond to one of six commands that the user may be thinking: no, yes, up, down, left, or right.

Ellen & Roenz built both the front-end React JS user-interface and the back-end connectivity to our database for securely storing user's data. The back-end Python API is called upon when the user on the front-end clicks the record EEG button, which is pictured at the bottom of this page with the pink brain and rotating blue/white circles. When that button is clicked, the following code is executed:

• ⚙️ Connect to the local EEG device
• ⚙️ Collect EEG data for one second
• ⚙️ Compile the data into a pandas dataframe
• ⚙️ Run predictions on those instances of EEG “screenshots”
• ⚙️ Of those predictions, return the command that was most frequently predicted

Then with that returned command, the front-end is hard-coded to react in a certain way, depending on which command was being “thought of” by the user wearing the EEG device for that one second in time — sort of like recording your voice to make a voice command to Siri or Google Assistant, but you're recording your brain's neuroelectrical transmissions.

We'd eventually like to be able to just continuously record and make predictions in real-time, while filtering out all other thoughts that the user is thinking, unless they're thinking of a specific command: no, yes, up, down, left, right. And we'd also like to eventually, obviously add more commands to our list of available actions.

However, these six commands are enough for a proof-of-concept. Currently, our front-end is equipped with the following functionalities, using just these six commands.