Mindtrics - Mind metrics. Made simple

17% of global workers actively manage their work time. Mindtrics, an unobtrusive brain-computer interface, offers a more exhaustive portal into personal productivity insights and stress reduction.

Comment

Inspiration

The inspiration behind "Mindtrics - Mind metrics. Made simple." stems from the growing importance of mental well-being and cognitive performance in our fast-paced digital world. We wanted to create a tool that effortlessly integrates into daily life, leveraging cutting-edge EEG technology and Logitech's superior audio hardware to provide users with actionable insights into their focus levels and mental state.

How we built it

Our project, Mindtrics, in order to create a seamless way to maintain the state of flow when carrying out any productive tasks, uses the following:

  • Logitech webcam
  • Logitech headphones (with the proposed application of EEG electrodes onto the headphone frame)
  • Logitech keyboards
  • Logitech mice

Instead of utilizing a timer-based system which can lead to breaking of the flow state, we focus on ensuring that users can extend these flow ranges beyond just a set timer. Our project incorporates real-time EEG data acquisition which is used to identify the level of focus that a person has had throughout time. In case the person goes below a specific threshold of focus, we can indicate this using our interactive website or through peripherals that allow RGB lighting. This provides a subtle way of indicating if the user is still in a state of flow or if they are unable to focus, ensuring that they do not experience any interruption.

Additionally, we provide many insights that a lot of users find actionable and intriguing. We make a step to a future of integrated non-intrusive BCI-s.

What it does

  • EEG Measurement (Through electrodes mounted on headphones): We used OpenBCI's 8-channel EEG headset whose electrodes we plan on incorporating through the Logitech headphones. We used a Band Pass filter and notch filter to carry out the initial filtering of the signals obtained from the EEG electrodes and then convert them into Alpha, Beta, Gamma, Theta, and Delta frequency wave categories. We use the ratio between Alpha and Beta waves to determine the level of focus the user has at different standpoints and a threshold to determine if they are focused or not. The logic is similar to most of the focus determining BCI tools available on the market and is possible to carry out with even 4 electrodes.
  • Activity Recognition: We use mmaction2 to recognize activities performed over a 40-frame sliding window. These sequences of activities are used also as a metric to see the type of activities that were performed during the productive work (e.g. watching, talking to, sitting, standing etc.)
  • Gaze Estimation: Our tool also uses a gaze detection neural network in order to identify eye movement patterns while performing tasks in front of the computer to check for changes in the direction of gaze.
  • Mouse Tracking: We track the movements of the mouse as well to identify if there was a wide spread of movements or more specific clicks which we use to find variability of mouse movements.
  • Dashboard: The dashboard consists of a start button which, when pressed, starts obtaining live EEG signals as well as recording activity, gaze, and mouse movement data. The EEG signal strength is visible by the color tone of the particles on this page. When "stop" is pressed, all the data is saved and displayed on the dashboard. This data consists of changes to focus strength, frequency of activities performed, spread for mouse movement, and change in gaze direction.

Challenges we ran into

  • Integration of multi-processing to run multiple neural networks, and algorithms over laptops
  • Distributing computing workload across different laptops
  • Integrating the UI for the live data streaming and results visualization.
  • Making of calibrated out-of-the-box gaze-to-screen estimation module.
  • Aggregation of collected telemetry to a score-based system.

Accomplishments that we're proud of

  • Integration of all the different metrics into the dashboard and focus-based scoring system.
  • Incorporating activity measurement and several other metrics for accurately identifying focus and "state-of-flow"

What we learned

Throughout this project, we deepened our understanding of EEG technology, signal processing, BCI algorithms, gaze algorithms. The experience taught us valuable lessons in hardware-software integration and integrating complex workflows together to create visualizations.

What's next for Mindtrics - Mind metrics. Made simple

Looking ahead, we envision the use of gamification of this tool to create leaderboards where user and their friends could have healthy competition to achieve the best focus metrics. We also envision the use of this project for the measurement of focus or state-of-flow during gaming sessions and measurement of gaze and mouse movements to identify how well they were co-related over time for an aiming game session.

Built With

Share this project:

Updates