Our project aims to help students, especially those in high school and college, adjust to a new medium of learning with the necessary tools. By looking at brain waves associated with focus levels, we can improve concentration, which in turn enhances the online learning experience.
Since the beginning of the pandemic, millions of students have moved to online learning. This sudden shift has led students to have to face new challenges, such as:
- The loss of concentration during class
- Missing important information and due dates
- Incomplete school work due to internal and external distractions
- Internal: anxiety and emotional distress, peer pressure
- External: family time, the aroma of food
- Mental fatigue
- Lack of motivation to study and keep up with classes
- Brain fog
Approaching the concentration problem...
- During study or work time, when signals of lack of focus are detected, the users would get notified to focus
- Low gamma waves + high alpha waves = low focus
- Knows when to get back to task without having to worry
Youtube: https://youtu.be/oZV_FBJ0N7I
- Web Application: React
- Data Cleaning and Analysis: Python
- Hardware: 8-channel OpenBCI Cyton Board
- We wanted to test our implementation with professionally-taken data(i.e. multiple participants, multiple trials, 64-channel EEG) to see if our results improved, diminished, or remained consistent.
- Below is a randomly-selected sample that begins with a student in a “non-focused” state, then transitions to a “focused state”
- Noisy user data
- Most likely because we used tape instead of electrode glue
- Algorithmic Improvements
- An fine-tuned algorithm that clearly defines the difference between the state of “focus” and the state of “distraction”
- User Friendly
- “Game-ify” the not-focused notification
- Possible range of choices that users can choose to set as reminders
- ex. animal gifs, encouraging texts, fun bgm, tips to focus, etc.
Chris Toukmaji, Cally Lin, Michelle Sheu, Ari Iramanesh, Jessica Yoon.