Working on a project? Cramming for an exam? This brain-sensing, environment-augmenting lamp uses EEG technology to tell how focused your are and block out distractions.
We’ve all been there: It’s late at night, you’re cramming for an exam when suddenly you’re interrupted by the simplest thing. How cool would it be to have a desktop accessory that could give you a kick in the right direction and increase your intensity as you try to finish your studying? Thanks to a group of Makers from the School of Visual Arts, that will soon be a reality.
The brainchild of developers Mejía Cobo, Belen Tenorio, and Josh Sucher, Clara is a brain-sensing lamp that employs EEG technology to tell how focus you are at a task at hand. Embedded with speaker and LEDs, the scene-augmenting device is capable of responding to changes in brainwaves, then reacting to your level of concentration by increasing the ambient music and shifting the light levels.
To bring this idea to fruition, the team used the combination of an Arduino Uno (ATmega328), an MP3 shield, several Adafruit NeoPixels, a SparkFun Bluetooth modem and a Neurosky MindWave Mobile EEG headset to wirelessly measure your “attention” and map the lamp’s color temperature, thereby subtly altering your environment.
As you begin homing in on a specific idea, the light will become crisper and cooler as the volume of the ambient noise emitted from the speaker slowly rises. This helps to enhance your ninja-like focus and block out other distractions.
“The basic structure of the Arduino code is straightforward. The NeoPixel strip is instantiated, then the Music Maker shield is instantiated, then we take advantage of interrupts to listen for, receive and act on Bluetooth serial data while the music is playing,” its creators reveal. “When the MindWave detects ‘activity’ (a number from 0-100 generated via some proprietary algorithm on the Neurosky chip), we initiate the ‘fade’ of the music and the light.”
Looking ahead, don’t be too surprised if you see Clara on Kickstarter in the coming months. Plus, the team hints that they may even migrate to an Arduino Mega (ATmega2560) for its next iteration. Until then, check out rather unique project on its page here.