Together, we are developing a brain-computer-interface (BCI) to non-invasively decode electrical signals into precise control signals using Deep Learning architectures.
Our interdisciplinary and diverse team comprises chemical, electrical, mechanical and neural engineering students as well as computer science and robotics students from 12 nationalities.
TUM is where remarkable things happen! From world records for electric vehicles to pioneering startups and empowering girls in coding, student initiatives are making a splash! At the recent Student Initiatives Night, we shared ideas and tackled common challenges together. We at NeuroTUM are working on Brain-Computer Interface technology, expanding into neuromorphic computing and electronics, and we want you to join us! Don’t miss the application window from October 25th to November 1st.
Signal processing is a vital step in Brain-Computer Interfaces (BCIs), enabling the transformation of raw EEG data into meaningful information. This article explores the essential tasks performed by neuroTUM's signal processing team to extract valuable insights from brain activity. From noise filtering to artifact removal and spectral analysis, signal processing plays a pivotal role in advancing BCIs, unlocking new frontiers in neuroscience and human-computer interaction.
Have you ever wondered how to design experiments in the domain of neurotechnology? In this article we’ll take you through the experimental teams’ workflow for designing electroencephalography (EEG) experiments for brain-computer interface (BCI) applications.
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