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2023 NeuroTechx Student Club Competition Finalists

From the NTX organizers:

NeuroTechX has experienced phenomenal growth recently with the onboarding of new student groups both across North America as well as the entire globe. Continuing to incorporate live streaming into this year’s competition not only enhances participants’ experiences but also aligns directly with the NTX mission: To facilitate the advancement of neurotechnology through three pillars: education, professional development and, particularly in the case of this year’s competition, enriching our engaged and enthusiastic Student Clubs community who are ready to learn, support one another and grow. This is an exciting challenge for NTX as organizers as much as it is for student club participators and industry partners.

Each year, NeuroTechX organizes its renowned NTX Student Club Competition. During this annual event, numerous NTX Student Clubs from around the world submit their projects to a curated jury of industry leaders and experts for a chance to win monetary prizes, hardware and internships. Over the past several competitive seasons there has been an impressive uptick in the quality of projects submitted.

Congratulations to the winners of the 7th Annual Student Club Competition:tada:

 Teams should be so proud of the amazing work they’ve done – the judges were impressed with what was presented in such a short time frame. Kudos to all participating teams! If you were busy and couldn’t join us at the event, keep an eye on the NTX YouTube Channel for the event recording as well as a review of all the finalist projects!

Each year, NeuroTechX’s student club competition receives creative and technically accomplished brain-computer interface project submissions. Judging was based on innovation, complexity, GitHub repo clarity, and project demo.

Winner: NeurotechSC from the University of California Santa Cruz. Their project sought to detect (subvocal) phonemes from OpenBCI hardware-obtained facial electromyography (fEMG) data using a Deep Neural Network model implemented in Python.

2nd Place: Triton NeuroTech from the University of California San Diego. Their project was a low-cost, 4-channel neural interface EMG input device (Cyton-EMG armband), a proof-of-concept intended to overcome mobility limitations and to make brain-computer interfaces more accessible.

3rd Place: Neurotech@Davis from the University of California Davis. Their project was a classifier which incorporates an OpenBCI Cyton board and an Arduino system, designed to send an audio signal to alert the user when their focus is waning. They demonstrated this concept through the operation of a single motor as a functional representation.

View all competition submissions here. Each includes a GitHub with a video and detailed walkthroughs of the data acquisition/analysis pipeline. The projects serve as a valuable resource to those getting started with EXG-based brain-computer interfaces.

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