Meet The Team

Brain Betrayal: EEG Lie Detector

We wanted to test if a P300 wave could be detected when a subject sees a face that they recognize, as compared to when they see unfamiliar faces. The P300 wave is a positive deflection in the human event-related potential. If successful, our project could be used as a lie detector test by showing subjects visual scenes, faces, or objects and knowing if the subject is lying about having been in that situation, seen that person or used that object. Members

Soulaimane Bentaleb, Raul Davila, Jasmine Zhang, Lena Johnson, 

Colby Lamond, Samika Karthik, Naomi Moskowitz

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BrainBrush

Some individuals find it difficult to effectively express their emotions and interpret the emotions of others. That is why we decided to develop project BrainBrush, a machine learning-based algorithm to translate EEG data into an easily understandable visual output. Our model classifies emotions on 3 axes: valence (pleasantness), arousal (intensity), and dominance (control). These values are then sent to TouchDesigner, where they determine the characteristics (color, speed, shape, etc. ) of the dynamic, visual output. Members

Andrew Bennecke, Alexandra Kwon, Emma Friedenberg, Jonathan Salman, Nicole Lee Yang, Hanniel Uwadia, Manya Bali

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EggHead

Our project, Egghead, aims to bring video games to those with motor deficits who may not be able to indulge in game entertainment in a traditional sense. Built as a puzzle game, you must help your character (the egg) avoid obstacles by pulling levers to help it escape its confines. As opposed to physically having to use a finger to push a button to pull the lever, Egghead evades the middle man by reading in SSVEP signals of the occipital lobe in live time— essentially, using brain waves to pull the lever directly. To accomplish this, each differently colored lever corresponds to a different frequency emitted from the brain which can be properly registered by a computer program. Members

Erica Li, Suraj Doshi, Bhrugu Bharathi, Martin Bourdev, Orrin Zhong, 

David Chung, Roja Ponnapan, Archi Bhattacharyaa

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Project Beats

By creating a pipeline that connects theta-stimulating binaural beats with a theta-tracking EEG headset, we plan to improve the working memory not only of students but potentially of patients suffering from dementia and other types of memory impairments as well. We also plan to
potentially create an app with a built-in feedback system that uses binaural beats to improve memory retention, thereby increasing the accessibility of our product. Members

David Bakalov, Aryak Rekhi, Daniel Hong, Will Stonehouse, Ashley Lamba, 

Elliot Berdy, Ronan MacRunnels, Tiffany Chen

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Optimal Alarm Clock

We aim to find a more accurate, precise method of measuring sleep quality. Fortunately, we believe this can be done through the collection and analysis of EEG data. We are planning on tracking brain activity throughout the sleep cycles. There will be a large variety of brainwave activity that we are planning on tracking since the waves change throughout a sleep cycle. 

Members

Rahil Modi, Jonathan Beltran, Angela Kan, Ahmed Ali, 

Becky Belisle, Katie Villasenor, Charles Hood