We were inspired by the amazing features that the muse headband had with its ability to track brainwaves as well as the versatile wireless communication of the spark core. We wanted to build a powerful demonstration of how these technologies can be combined to create something with potential. We were able to control a small LED on a spark core using a muse headband and develop a system to enter a password using specific thought patterns. Spark cores can control many household objects such as televisions and toasters, which now have the potential to be controlled by one's mind through the use of the muse headband.
The video demonstrates how the muse headband can decipher between two mind states: "calm" (focused) and "agitated" (unfocused/excited thought). Brainwaves are from the muse are sent via bluetooth and processed by a python program. The python program determines whether the signals are controlled (calm) or erratic (agitated). If the signals are calm, the program sends an HTTP request via a curl to a spark core (which has its own code to interpret HTTP requests, written in processing) and a light will turn on. If the signals are agitated, the light is turned off. Potentially anything (so long as its connected to a spark core) such as a sound system, TV, etc. can be turned on and off in this manner.
The password that is being demonstrated in the video is the binary thought sequence: CALM CALM AGITATED AGITATED (CCAA). When this sequence of brain wave signals is received, it can be recognized as a valid password. Passwords can be more complicated of course. This method allows for a very discreet and secure way to unlock a system.
Some main challenges we ran into were connection problems with the muse's bluetooth and the computer as well as the lack of a comprehensive muse developer api for obtaining and processing brainwave data. Despite this, we were able to develop a system by which we can identify distinct thought patterns.
We ran further tests to determine how the brain responds to different colors/foods. These more complex thought patterns could potentially be classified using machine learning algorithms.
We have essentially demonstrated a fast and feasible way to control a spark core chip using the muse headband and the human brain, combining two very powerful pieces of hardware.
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