Transcript Slide 1

Brain-Computer Interfaces for
Communication in Paralysis: A Clinical
Experimental Approach
By
Adil Mehmood Khan
Contents
● Introduction
● BCI for communication in paralysis
● BCI software
● Self-regulation of SCPs and training
● Spelling through brain-cmputer communication
Brain-Computer-Interface (BCI) ?
control signal
EEG
Subject/
Patient
Brain Computer
Interface
Device
“A system for controlling a device e.g. computer, wheelchair or a
neuroprothesis by human intention which does not depend on the
brain’s normal output pathways of peripheral nerves and muscles”
[Wolpaw et al., 2002].
HCI – Human Computer Interface
DBI – Direct Brain Interface (University of Michigan)
TTD – Thought Translation Device (University of Tübingen)
Some examples of BCI applications
BCI_
BCI
Leeb et al., Computational Intelligence and
Neuroscience, 2007 (doi:10.1155/2007/79642)
Brain Computer Interfaces
● Allow patients to control a computer by
concious changes of brain activity
● Provide a means of communication to completeley paralysed patients:
amyotrophic lateral sclerosis (ALS), cerebral palsy, locked in syndrome
● Can be used to control a cursor, select symbols, control external
devices like orthesis / prothesis (depending on type of BCI)
● Have a very low data rate, typical a few bit per second or less
● First results in the 1970ies (Vidal, visual evoked potentials, VEP-BCI)
Brain Computer Interfaces
Principles of operation:
Brain Computer Interfaces – Electrophysilogical
Activities used
● SCP Slow Cortical Potentials
● Mu Movement Imagination
● P300, SSVEP ERP-Analysis
● cortical neurons,
direct brain interfaces
The control information
is extracted from the
real time EEG-recording
http://www.wired.com/news/images/full/thoughtlock1_f.jpg
Brain Computer Interfaces – SSVEP
● Steady State Visual Evoked Potentials
derived from the visual (occipital) cortex
● focussing attention to visual stimuli of different frequency
shows up in the EEG freqeuncy bands
● relibable and high transfer rate, but some prerequisites (eyes)
http://www.iua.upf.es/activitats/
semirec/semi-Reilly/
Brain Computer Interfaces – SCP BCIs
● detection of slow cortical potentials (SCPs)
● needs DC EEG Amplifiers
● first successful device end 1990‘s:
Niels Birbaumers Thought translation device
intensive training was necessary to gain
control over the SCP waves
SCPs:
DC-shifts, slow negativation
of cortical areas
Preparation of movement
and cognitive tasks,
Several hundert milliseconds
before the task
Patinet using TTD to write a letter
http://www.heise.de/ct/06/18/088/bild1.jpg
Brain Computer Interfaces - μ-rhythm BCIs
● μ–rhythm is the idle-rhythm of the motor cortex
● frequencies around 10 and 18 Hz.
● ERD / ERS – event related desynchronisation / synchronisation
movements or imagination of movements inhibit the μ–rhythm
Berlin-BCI, http://www.fraunhofer.de/
Brain Computer Interfaces - P300 BCIs
● P300 wave – posivite component in
the event related potential, 300ms
after a stimulus
● natural response to events considered
as important
● selection of a symbol: count the flashes,
algorithm averages trails and finds a P300
P300 runtime user interface
Brain Computer Interfaces - μ / P300 comparison
μ - BCIs
Require training
2d-control possible
movement imagination
affected by movement
P300 BCIs
do not require training
1D control only
concentration / decision
affected by distraction
BCI for Communication in Paralysis
• An overview of different approaches to BCIs
developed at Institute of Medical Psychology and
Behavioral Neurobiology.
• Thought-Translation Device (TTD).
• Brain-Controlled Web Browser.
• Visual and Auditory feedback modes.
• Oscillatory Features based Classification.
SCPs: A Brief History
• An initial application: Epileptic Seizures
– Down regulation of brain potentials towards
a positive amplitude.
• BCI for “locked-in syndrome”
– Communication through self-regulation of SCPs
– Also known as TTD
BCI Software
• Thought Translation Device: Components
– EEG Amplifier
• EEG8 system
• G.tec amplifiers
• BrainAmp system
– Two Monitors
• One for operator (supervise the training)
• One for patient (feedback)
•
•
•
•
•
Sampling frequency: 256Hz
Digitized with 16 bits/sample
Amplitude range: +(-) 1mV
Low frequency cutoff: 0.01 Hz
High frequency cutoff:: 40-70 Hz
TTD Feedback and Communication System
•
The current version of TTD software is derived
from BCI2000 standard
TTD Feedback and Communication System
TTD Software
Data acquisition
and storage
Online signal
processing
Classification
Feedback and
application interface
Brain Computer Interfaces - BCI2000
● Research Platform for BCI Systems
● Written by Gerwin Schalk, Wadsworth Center, Albany (NY)
● Modular structure: Signal Aquisition, Signal Processing
and User Application communicatie via TCP/IP
● Operator module used for configuration of the other modules
● various user tasks availbale: 1D/2D cursor, Speller, P300, SCP
● free for academic use
● driver for OpenEEG available
http://www.bci2000.org/
BCI2000: Components
• Filters
– Spatial, temporal, and spectral
• Online artifact detection and correction
• Classification
– Linear Discriminant Analysis (LDA)
– Simple Threshold Classification
– Support Vector Machine (SVM)
• MATLAB interfaces.
Self-Regulation of SCPs
● Slow event-related direct-current shifts of the EEG.
● They last from 0.3 seconds up to several seconds.
● Occur as a result of external or internal events.
● Negative shift is related to excitability of neurons.
● Positive shifts are measured during the execution
of cognitive tasks
● Healthy subjects as well as patients can learn to
produce positive or negative SCPs
● Training requires feedback
•Visual
•Auditory
Self-Regulation of SCPs
● Recording site for feedback signal is usually Cz.
● EEG is usually recorded from 3-7 Ag/AgCI-electrodes
placed at Cz, C3, C4, Fz, and Pz.
● vEOG is recorded using a bipolar channel for online
and offline artifact correction.
● A fixed percentage of vEOG signal is subtracted from
the SCP signal at Cz for EOG correction.
● SCPs are calculated by applying a 500ms moving
average to EEG signal.
Self-Regulation of SCPs
● With the visual feedback modality:
•Subjects viewed the course of their SCPs as the vertical
movement of feedback cursor.
•Vertical cursor movement corresponded to the SCP
amplitude.
•Task was to move the cursor towards the modality
indicated by a red rectangle.
Self-Regulation of SCPs: Training Process
Target
Presentation
interval
Selection
interval
Response
interval
Self-Regulation of SCPs: Training Process
Target
Presentation
interval
Selection
interval
● First 2-4 sec of the trial.
● Target is illuminated in red.
● Allows the subject to prepare for the corresponding
SCP regulation.
Response
interval
Self-Regulation of SCPs: Training Process
Target
Presentation
interval
Selection
interval
Response
interval
● Feedback is provided by the vertical position of the
steady horizontally moving cursor.
● Cortical negativity moved the cursor up.
● Positivity moved the cursor down.
● Center of the screen corresponded to the baseline.
● Task is to move the cursor to the red area.
Self-Regulation of SCPs: Training Process
Target
Presentation
interval
Selection
interval
Response
interval
● A response is classified as correct if:
•Average potential carried the correct polarity.
•Or is inside the target boundaries of the required goal.
● Classification methods, such as LDA or SVM can be
used for improvement of the correct response rate.
Self-Regulation of SCPs: Performance
1st Trial: Target presentation ,
Selection, Response
2nd Trial: Target presentation ,
Selection, Response
NthTrial: Target presentation ,
Selection, Response
● Performance
•Percentage of correct responses in valid trials.
•After a rate of 75% correct responses, subjects were
trained to select letters and write messages
● Subjects typically reach this level after 1 to 5 months
of training, with 1 to 2 training days per week.
● A training day comprises 7 to 12 runs, and a run
comprises 70 to 100 trials.
Applications
Spelling by Brain-Computer Communication:
•A program driven by “yes” or “no” responses, which serve as
“select” or “reject” commands.
•Requires three intervals in one trial.
•Allows user to select letters from a language alphabet and to
combine letters into words and sentences.
Presentation
Selection
Response
Applications
Spelling by Brain-Computer Communication:
•A program driven by “yes” or “no” responses, which serve as
“select” or “reject” commands.
•Requires three intervals in one trial.
•Allows user to select letters from a language alphabet and to
combine letters into words and sentences.
Presentation
Selection
•Presentation of the letter set.
•Displayed in target rectangles on the screen.
Response
Applications
Spelling by Brain-Computer Communication:
•A program driven by “yes” or “no” responses, which serve as
“select” or “reject” commands.
•Requires three intervals in one trial.
•Allows user to select letters from a language alphabet and to
combine letters into words and sentences.
Presentation
Selection
Response
•Feedback is provided.
•Self regulation of SCP amplitudes is used
to select or reject the letter set.
Applications
Spelling by Brain-Computer Communication:
•A program driven by “yes” or “no” responses, which serve as
“select” or “reject” commands.
•Requires three intervals in one trial.
•Allows user to select letters from a language alphabet and to
combine letters into words and sentences.
Presentation
Selection
Response
•Response interval indicating to user the
result of the selection.
•Error correction is done using a “go-back”
option.
Spelling by Brain-Computer Communication
Spelling by Brain-Computer Communication
Performance:
•Writing the most conveniently situated letter , “E,” takes 5 trials.
•Writing the most remote sign requires 9 trials, i.e. 36 – 45 sec.
Improvement
•A simple personal dictionary to make free spelling less time consuming.
•Contains words that are frequently used by patients.
•A complete word is suggested after at least two letters have been written.
•This word can then be chosen with a single selection response.