EEG based action classification By Pratyush Sinha (Y9227434) - PowerPoint PPT Presentation

Sep 28, 2023 •412 likes •562 views

EEG based action classification By Pratyush Sinha (Y9227434) Mentor: Prof. Amitabha Mukherjee EEG The electroencephalogram, or EEG, consists of the electrical activity of relatively large neuronal populations that can be recorded from the

EEG based action classification By Pratyush Sinha (Y9227434) Mentor: Prof. Amitabha Mukherjee
EEG • The electroencephalogram, or EEG, consists of the electrical activity of relatively large neuronal populations that can be recorded from the scalp. • Hans Berger (1873 – 1941) recorded the first human EEG in 1924 . He also invented the electroencephalogram, an invention described as “ as one of the most surprising, remarkable, and momentous developments in the history of clinical neurology ” • Today Event Related Potential (ERP) measured using EEG is one of the most widely used method in cognitive neuroscience.
The Experiment Trying to distinguish between kinesthetic imagination and actual motor movement.
Dataset • 64-channel EEG recorded using the BCI2000 system. Available at Physionet. • Tasks included: – opening and closing of right or left fist – Imagination of opening and closing of right or left fist – Opening and closing of both fists or both feet – Imagination of opening and closing of both fists or both feet.
Assumptions/Simplifications • It is generally believed that the motor activity takes place in the sensorimotor cortical areas of brain. • For simplification, considered only the channels C3,C4 and Cz(reference electerode). • Considered only the tasks related to movement of fists and the imagination of their movement.
• Previous studies have shown that the mu rhythm (8-13 Hz) is blocked prior and during hand movement. • Power Spectral density study shows there is a significant gap between the actual and imagery motor tasks in the mu rhythm range.
Additions/Modifications • A classifier to be made from data from a large number of subjects using machine learning. • Feet movement, contrary to hand movement shows a positive spike in mu rhythm. This can be used to distinguish it.
Thank You! Questions?
References • http://www.sciencedirect.com/science/article/pii/S0304394097008896 • http://wexler.free.fr/library/files/beisteiner%20(1995)%20mental%20repr esentations%20of%20movements.%20brain%20potentials%20associated %20with%20imagination%20of%20hand%20movements.pdf • http://www.sciencedirect.com/science/article/pii/S0304394097008896 • http://www.sciencedirect.com/science/article/pii/S1388245799001418 • http://www.ai.rug.nl/~lambert/projects/BCI/literature/serious/non- invasive/BCI-eeg-mu-and-beta-rhythm-topographies-with-movement- imagery-and-actual-movement.pdf • http://edu.technion.ac.il/haptech/publications/Publications_files/Imagery _motor_actions_2005.pdf • mathworks.in

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