AI Applications in EEG
Explore how EEG signals are collected, processed, and analyzed using AI for breakthrough applications in brain-computer interfaces.
Apply NowEEG Basics
Signal collection and preprocessing fundamentals
ML & DL
Machine learning models for EEG decoding
Real Apps
Clinical diagnosis and BCIs
Hands-On
Practical experience with MNE-Python
Workshop Schedule
Three days of lectures, live demos, and hands-on lab sessions.
Day 1: Foundations & EEG Basics
Inaugural Talk: Prof. Srinivasa Chakravarthy
Overview of EEG, BCIs and AI applications in neuroscience.
Introduction to EEG & System Setup (9:00–10:00)
EEG principles, 10–20 montage, cap fitting demo, impedance check demonstration.
EEG Pre-processing Lab (10:00–13:00)
Filtering, artifact removal, ICA techniques, and preparing EEG signals for machine learning.
ML & DL for EEG (14:00–17:15)
Feature extraction (PSD, PLI), machine learning models (SVM, Random Forest), and deep learning models (CNN, LSTM) for EEG classification.
Day 2 – Imagery & Clinical Studies (Feb 21)
Motor Imagery Theory & Lab (9:00–11:00)
Guided lab session using left/right hand imagination tasks and classification of Motor Imagery EEG signals.
Epilepsy & Seizure Detection (14:00–15:30)
Introduction to BONN EEG dataset, spike detection, seizure event annotation and clinical relevance.
Lab: Seizure Classification (15:30–17:15)
Comparative modeling using Random Forest and CNN architectures for automated seizure detection.
Day 3 – Neurodegenerative Detection (Feb 22)
Neurodegenerative Disorder Detection (9:00–11:00)
Parkinson’s vs Healthy classification using EEG biomarkers and machine learning models.
Alzheimer's Detection Lab (11:00–13:00)
EEG marker extraction and classification of Alzheimer's vs healthy brain activity patterns.
Visual Imagery Lab (14:00–15:30)
Studying EEG signatures of imagined objects and scenes and decoding visual imagination patterns.
Faculty Talks & Closing Ceremony (15:30–17:30)
Talks by neurotechnology experts followed by closing ceremony and certificate distribution.
Important Dates
Fee Structure
UG
₹3,000
PG/PhD
₹3,500
Professional
₹4,000
Participant Feedback
Anonymous feedback from previous participants
The workshop featured expert lectures, live demonstrations, and guided lab sessions, providing a strong practical foundation in computational neuroscience and neurotechnology. I am sincerely grateful to Prof. Srinivasa Chakravarthy and the organizing team for their mentorship and for creating such a rigorous and enriching learning environment.
The sessions delivered by faculty members and neurotechnology experts provided valuable insights into EEG acquisition, preprocessing, feature extraction, AI-based neural decoding especially of motor imagery, visual imagery, epilepsy & seizure detection, neurodegenerative disorders.
The program was exceptionally well designed, with extensive hands-on sessions focused on EEG signal preprocessing and practical applications. The workshop offered deep insights into how the human brain functions and the interdisciplinary intersection of neuro-engineering, psychology, and biology.
The focus on building up the workshop from the fundamentals made it very engaging.
Advanced pre-processing is something I wanted to learn for a very long time and I got foundational knowledge on it.
The deep learning and machine learning part along with codes as my background is from bioinformatics. I also found biology part of the workshop helpful in recalling neuroscience fundamentals.
Sessions on Motor and Visual Imagery were extremely insightful. Before the workshop I could not quite understand how one could decode imagination — now I have a much clearer picture on what is possible.
Ready to Decode the Brain?
Questions? Reach out to workshops@neurogati.com