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Seminars

Deep Learning for EEG-Based Brain-Computer Interface

  • 2023-09-25 (Mon.), 10:30 AM
  • Auditorium, B1F, Institute of Statistical Science;The tea reception will be held at 10:10.
  • Online live streaming through Cisco Webex will be available.
  • Prof. Chun-Shu Wei
  • Department of Computer Science, National Yang Ming Chiao Tung University

Abstract

The field of brain-computer interface (BCI) has witnessed significant advancements in recent years, driven in large part by the integration of deep learning techniques. This talk explores the cutting-edge applications of deep learning techniques in the context of BCIs based on electroencephalogram (EEG) signals, a non-invasive, portable, and cost-effective neuromonitoring modality, bridging the human brain and external devices. Based on the foundational principles of EEG signal acquisition, preprocessing, and recognition, we delve into the evolving landscape of deep learning models and architectures tailored for EEG data analysis. Our focus extends to the real-world implications of these advancements, shedding light on how deep learning-powered EEG-BCIs are revolutionizing assistive technology, healthcare, and neuroscientific research, with insights into the emerging trends and pivotal challenges.

Please click here for participating the talk online.

Download

1120925 Prof. Chun-Shu Wei.pdf
Update:2023-09-22 13:42
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