RemBRAINdt: Generating Art from Live Brain Data

Champion Name

Shane Eaton

University of Alberta

Challenge Description

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Development of RemBRAINdt, an EEG-based application for entertainment, as well as development of a business strategy to commercialize the application. Currently it is designed for use at public events such as conferences, fundraisers and outreach events. We believe a good starting place would be such events related to brain and mental health. The application would use live EEG data to generate a dynamic art screen with features customized by the user. The art would capture the user’s changing emotional state, thus providing a type of biofeedback that influences and engages the user. User data (name, contact information) would be collected to create a profile linked to their personalized art generation baseline and settings. At any time, a snapshot of the dynamic art could be taken which could be made into a high quality print for purchase by the user. We will also explore including a sculpture mode, where 3D-printed artwork could also be made available. The business plan for the application would include market research, identifying appropriate pricing, outreach to local events for beta-testing, and exploration of a SaaS (software as a service) model.
The application would be built with Python, utilizing machine learning algorithms and cloud computing. Affordable EEG headsets are readily available, and a framework for the application has already been established. In combining emotion and art, this technology would generate personalized art, provide entertainment and have the potential to popularize consumer neurotechnology. Generating public interest in neurotechnologies is essential for attracting funding to the field, and this project is poised to do just that. The ideal team would have collective expertise in neuroscience, design, python, machine learning, and business.