CognoSynth

Inspiration

Physical disability limits millions of individual from reaching their true potentials yet with the emerging technologies in the field of brain computer interface, physical disability can be a thing of the past.

What it does

The developed app utilizes a commercial electroencephalography (EEG) headset to measure the cognitive load of the brain and produce a musical tone to assist in maintaining the cognitive load.

How we built it

We used the Emotive Epoc+ headset to measure the EEG of the user and produce tones based on the different brain waves. The accompanying app was developed for Android using android studio. A machine learning algorithm was developed using Weka (a research based Java library) to classify the cognitive load. The music was generated by playing multiple harmonics of a base sine wave that was scaled using the power of the measured EEG.

Challenges we ran into

Maintain constant connection with the Epoc+ headset Identify the EEG waves that best represent the cognitive loads Develop the music box to constantly play a base sound that is scaled using the EEG power Importing the developed machine learning algorithm into Android Studio

Accomplishments that we're proud of

It works!!! The app measures the cognitive load accurately and classifies it as high or low. It then produces a musical tone that matches the load. The musical tone was completely designed and built by us.

What we learned

App development Multithreading and thread management Training and testing of the machine learning algorithms Integration of Java libraries into Android studio Music generation

What's next for CognoSynth

Since we can now measure and classify the cognitive load the next step is to expand beyond music generation to control of external devices such as personal computers and ultimately controlling assistive devices to increase mobility.

Built With

• adobe-experience-design
• android-studio
• dsp
• eclipse
• java
• photoshop
• weka