Electroencephalography (EEG)

Slides:

Advertisements

Similar presentations

Introduction to Web Design Lecture number:. Todays Aim: Introduction to Web-designing and how its done. Modelling websites in HTML.

Advertisements

Slope of a Line Slope basically describes the steepness of a line Free powerpoints at

Working With Cartograms. Cartograms give graphic representations of data in ways that help us visually compare areas.

Rock Out with Excel Basics Summer 2007 Janie Hardt

HTML III. Learning Objectives HTML Links Structuring Pages with Frames Introduction to Cascading Style Sheets (CSS)

HOW TO SET UP A WIKI SITE With Wikispaces Written by Jacqui Sharp.

A PRIMER FOR ANIMALS & HEARING Sound & Waves. Sound is Vibration.

Thought Translation Device

Copyright Compumedics Limited

What do we measure with EEG and MEG?

Start of Part 3 Eric W. Harris, PhD.. Basic Functional Subdivision of Neurons But, of course, there are exceptions – e.g., action potentials can originate.

BCIs using EEG for multidimensional control! Compared to invasive BCIs – Pros/cons – Real-world clinical application – Performance optimization.

Authors: Hochberg, Leigh R. Bacher, Daniel Jarosiewicz, Beata Masse, Nicolas Y. Simeral, John D. Vogel, Joern Haddadin, Sami Liu, Jie Cash, Sydney S. van.

Fig. 4-1, p Fig. 4-2, p. 109 Fig. 4-3, p. 110.

Human Body Skeletal, Muscular, and Nervous Systems Unit G in our textbook.

Primate Comparisons Measurements. Brain Case Size Use the calipers to measure the brain case Each end should be placed on the temples of the skull If.

Key Concepts What factors affect the gravitational force between two objects? Why do objects accelerate during freefall?

Non-Invasive BCI.

Brain-computer interfaces: classifying imaginary movements and effects of tDCS Iulia Comşa MRes Computational Neuroscience and Cognitive Robotics Supervisors:

For Neurology Residents

P.464. Table 13-1, p.465 Fig. 13-1, p.466 Fig. 13-2, p.467.

Fig. 11-1, p p. 360 Fig. 11-2, p. 361 Fig. 11-3, p. 361.

By Annemari de Silva Supervised by Prof. Peter Robinson.

1 Affective Learning with an EEG Approach Xiaowei Li School of Information Science and Engineering, Lanzhou University, Lanzhou, China

Table 6-1, p Fig. 6-1, p. 162 p. 163 Fig. 6-2, p. 164.

Functional Brain mapping using ECoG (electrocorticography)

BCI Systems Brendan Allison, Ph.D. Institute for Automation University of Bremen 6 November, 2008.

COMSATS Institute of Information Technology,Sahiwal.

Studying Earthquakes. Seismology: the study of earthquakes and seismic waves.

Closed and Open Electrical Fields

Brain Computer Interfaces

NeuroPhone : Brain-Mobile Phone Interface using a wireless EEG Headset Ilho nam.

Brain-Computer Interfaces for Communication in Paralysis: A Clinical Experimental Approach By Adil Mehmood Khan.

Functional Brain Signal Processing: Current Trends and Future Directions Kaushik Majumdar Indian Statistical Institute Bangalore Center

Review, Hollan & Gorodnitsky Adrienne Moore, by

84 year old woman with spells of right upper limb weakness and numbness Teaching NeuroImages Neurology Resident and Fellow Section © 2014 American Academy.

Introduction of Electroencephalographic Signals in Dementia- Part (I) Richard Chih-Ho Chou, MD Biomedical Imaging and Electronics Laboratory.

Graz-Brain-Computer Interface: State of Research By Hyun Sang Suh.

Artifacts Across the Modalities: Panel Discussion EEG Coretta Shields, R, EEG T. Rush University Medical Center.

Human Brain and Behavior Laboratory Center for Complex Systems and Brain Sciences EEG Coordination.

EEG-Based Communication and Control: Short-Term Role Feedback Present by: Yu Yuan-Chu Dennis J. Mcfarland, Lynn M. McCane, and J. R. Wolpaw.

Using Feed Forward NN for EEG Signal Classification Amin Fazel April 2006 Department of Computer Science and Electrical Engineering University of Missouri.

Measuring brain activity Blood flow fMRI, PET, NIRS Electrical activity EEG.

Dr. Ali Saad modified from Dr. Carlos Davila Southe. metho univ 1 EEG Brain signal measurement and analysis 414BMT Dr Ali Saad, College of Applied medical.

1 Psychology 304: Brain and Behaviour Lecture 4. 2 Research Methods and The Structure of the Nervous System 2. What are the primary divisions of the nervous.

Brain-Computer Interfaces

12. General Clinical Issues Relevant to Brain-Computer Interfaces YOON, HEENAM.

Electroencephalogram. Terms EEG- Elecrtoencephalogram Electroencephalograph ECoG- Electrocorticogram.

PHYSIOLOGY LAB EEG I. The cerebral cortex is composed of nerve cells, many of which are functionally connected to each other, and connected to other parts.

Vlodek Siemionow, Yin Fang, Leonard Calabrese, Vinod Sahgal, Guang H

Animation Basic Concepts.

Brain operated wheelchair

1. EEG source cortical pyramidal cells

[Ran Manor and Amir B.Geva] Yehu Sapir Outlines Review

Brain Electrophysiological Signal Processing: Postprocessing

Electroencephalogram (EEG)

Representative polysomnographic recordings from adults in the awake state and various stages of sleep. Recordings are made at conventional sleep laboratory.

Saving your Animations

Ultradian Rhythm STAGES OF SLEEP: Link to Spec 4.2.2

Perceptual Echoes at 10 Hz in the Human Brain

Sound shadow effect Depends on the size of the obstructing object and the wavelength of the sound. If comparable: Then sound shadow occurs. I:\users\mnshriv\3032.

Cycle 10: Brain-state dependence

IEEE Trans. Biomedical Eng. ( ) Presenter : Younghak Shin

Machine Learning for Visual Scene Classification with EEG Data

Brain-Computer Interfaces in Medicine

(c) V/2-Com (Verhaart) Multimedia Elements & standards 4/15/2019 (c) V/2-Com (Verhaart)

A–C, Surgical planning, case 9 (Table 1): 18-year-old boy with life-long medically intractable seizure disorder due to a perinatal hemorrhage (A). A–C,

Source-based CP BCI robotic arm control.

Axial T2-weighted image (A) demonstrates focal cortical dysplasia (arrow) centered in the left anterior temporal lobe in a right-handed patient. Axial.

Presentation transcript:

Electroencephalography (EEG)

Hz (awake, but relaxed, attenuated w/ activity) mu  alpha having to do w/ motion Hz (Low amplitude w/ multiple/varying freq when thinking) up to 3 Hz (sleep and babies) 4-7 Hz (kids and meditation) Hz raw EEG

Wolpaw, PNAS 101(51), 2004, Fig. 1

C3=L C4=R nose (24 Hz) (12 Hz)

Wolpaw, PNAS 101(51), 2004, Fig. 1 beta mu (alpha) C3=L C4=R nose 3&4 2&5 1&6 7&8 1&2 3&8 4&7 5&6 C3 C4

Wolpaw, PNAS 101(51), 2004, Table 1

/07/ DC1/03504Movie1.movhttp:// /07/ DC1/03504Movie1.mov Movie 1. Two-dimensional cursor control with scalp-recorded sensorimotor rhythms. In this QUICKTIME movie, a person with spinal cord injury (i.e., user A) uses scalp-recorded sensorimotor rhythms to control cursor movement in two dimensions. In each trial, a target appears at one of eight possible locations on the periphery of the screen, and 1 sec later, the cursor appears in the center and moves. Its vertical movement is controlled by the sum of the weighted amplitudes of a 24-Hz beta rhythm recorded from the scalp over left and right sensorimotor cortices, and its horizontal movement is controlled by the difference between the weighted amplitudes of a 12-Hz mu rhythm recorded over left and right sensorimotor cortices, as described in Methods.

Wolpaw, PNAS 101(51), 2004, Fig. 2

Wolpaw, PNAS 101(51), 2004, Fig. 3

Wolpaw, PNAS 101(51), 2004, Fig. 4

Looking into the future….

They use more channels and more frequencies….and tailor it for different users

Hochberg, et al. Neuronal ensemble control of prosthetic devices by a human with tetraplegia, Nature, 44(13), 2006 p Fig. 1

Hochberg, et al. Neuronal ensemble control of prosthetic devices by a human with tetraplegia, Nature, 44(13), 2006 p Fig. 2

Hochberg, et al. Neuronal ensemble control of prosthetic devices by a human with tetraplegia, Nature, 44(13), 2006 p Fig. 2

Hochberg, et al. Neuronal ensemble control of prosthetic devices by a human with tetraplegia, Nature, 44(13), 2006 p Fig. 3

Hochberg, et al. Neuronal ensemble control of prosthetic devices by a human with tetraplegia, Nature, 44(13), 2006 p Fig. 3

Hochberg, et al. Neuronal ensemble control of prosthetic devices by a human with tetraplegia, Nature, 44(13), 2006 p Fig. 4

Not the original video… but close JjEhTshttp:// JjEhTs

Hochberg, et al. Neuronal ensemble control of prosthetic devices by a human with tetraplegia, Nature, 44(13), 2006 p Fig. 5

Hochberg, et al. Neuronal ensemble control of prosthetic devices by a human with tetraplegia, Nature, 44(13), 2006 p Fig. 6