SlideShare a Scribd company logo
1 of 30
EEG recordings in man
Examples of records and results of
analysis made by Braintune (St.
Petersbuurg) hardware/software.
Nyquist Theorem
• The highest frequency which can be
accurately represented is one-half of
the sampling rate.
• The sampling rate here is below the
Nyquist frequency, so the result of
sampling is nothing like the
input:aliasing.
• For practical purposes the sampling
rate should be 10 higher than the
highest frequency in the signal.
•
EEG is a difference in potential
between two electrodes
• If two electrodes are “active”, it is called “bipolar”
recording.
• If one electrode is “silent”, it is called “monopolar”
recording. The reference sites: ear lobe, mastoid,
nose.
Bipolar vs. monopolar recordings
• Monopolar recording is used in research,
because it enables the researcher to localize
the event of interest.
• Bipolar recording is used in BF, because it
reduces shared artifacts. Electrodes should
be placed on the sites with the strongest
gradients of the potentials under training.
EMG and eye blink artifacts in
EEG
• These types of
artifacts can be
detected by visual
inspection.
• Eye blinks can be
excluded from
data analysis.
• EMG should be
taken into
account during
spectral analysis.
EEG recorded at Cz
• EEG is a mixture of waves at different
frequencies and amplitudes.
EEG recorded at T5
• At each time interval several sine-waves at
different frequencies may be present in the
signal.
Quality control of EEG recording
• 1) EEG amplifies must be calibrated with
daily checks
• 2) acquisition parameters must be checked
daily and keep the same
• 3) the same procedures must be employed
in all individuals
• 4) all artifacts must be eliminated or taken
into account prior to spectral analysis.
EMG Artifact
• EMG artifact starts as low as 12 Hz and ranges to
300 Hz. Most of the spectrum lies between 30-150
Hz.
• Sites F3, F4, T3, T4, P3, P4 can pick up EMG the
massester and temporalis muscles.
• Posterior electrodes can pick up EMG from
occipitalis, trapezius and supraspinal muscles.
• To avoid this type of artifact one can relax or
position the head properly or change slightly the
position of electrode.
• Fz, Cz, Pz can give a relatively pure EEG signal.
EKG artifact
• ECG artifacts occur from the electrodes that
pick up activity from underlying pulsating
blood vessels in the scalp.
• EKG artifact gets more prevalent with
aging.
Ocular, blinks and electroretinal
activity
• Eye movement and blinks artifacts occur in
the delta range 0-4 Hz and occur over the
anterior part of the scalp.
The noise from the standard AC
electrical line current
• This noise can be diminished by the proper
grounding of the equipment (both computer and
amplifies).
• It could be also eliminated by a so called notch filter
which selectively removes 50 (60 for the US) Hz
activity from the signal.
• This noise could be attenuated by obtaining good
contact of electrodes with the scalp. The electrode
impedance less than 10 kOhms is desirable.
EEG recording in man
• Eyes opened condition.
• Examples of different waves.
Reviewing EEG
• EEG is characterized by:
• 1) voltage
• 2) frequency (is used for BF)
• 3) spatial location (is used for BF)
• 4) inter-hemispheric symmetries
• 5) reactivity (reaction to state change)
• 6) character of waveform occurrence
(random, serial, continuous)
• 6) morphology of transient events
Reviewing EEG: voltage
• Amplitude is the voltage in microvolts
measured from the peak of the wave to the
trough of the wave. Varies from 10 mcV to
100 mcV with average around 20-50 mcV.
•
Reviewing EEG: frequency
• Spectrums reflect the amount of energy in a
certain frequency range of EEG.
• Term monorhythmic means that a particular
portion of EEG shows a rhythmic
component in a singular frequency.
• Term polyrhythmic means that several
rhythmic frequencies are present in EEG.
• The presence of large-amplitude delta-
activity may indicate infarct or other lesion.
Reviewing EEG: frequency
• Slow (0-4 Hz) and high (more 20 Hz)
frequency bands of EEG may pick up artifacts,
such as eye movements and muscle activity,
and therefore should be evaluated with caution.
• Despite the use of artifact rejection algorithms,
the failure to accurately distinguish true
physiological rhythmicity from the artifacts is a
serious shortcoming of current software
systems and requires the expert assessment.
Reviewing EEG: transient events
• A transient is an isolated form or feature that
stands out from the background activity.
• It is called a spike if it has the duration less
than 70 msec.
• It is called a sharp wave if it has the duration
between 70 and 200 msec.
• The presence of large amplitude spikes and
waves may indicate the presence of epilepsy.
Maps of EEG spectrums in
standards bands
• Eyes opened
condition.
EEG recording in man
• Eyes closed condition.
• Enhancement of alpha waves.
Maps of EEG spectrums
• Eyes closed condition
EEG
spectrums
• Three conditions (EC, R, M)
are compared to Eyes Opened
condition.
• Two peaks (in theta and alpha
band) with different scalp
distribution are observed.
• Reading and math produce big
(but different) changes in alpha
band and small changes in theta
and beta bands.
• Note that alpha activities are
different for all four conditions
both in distribution and
frequency.
EEG spectrums in individual
bands
• Regular theta -
idling rhythm
• Irregular theta -
working activity
• Reading and
math produce
alpha rhythms
that are different
in frequency and
location.
EEG as a sequence of micro-
states
• EEG consists of series of
short-lasting quasi-
stationary epochs
corresponding to what
Lehmann et al. (1987) have
called brain functional
micro-states.
• EEG reflects the changes in
the state of neuronal
networks rather than
specific aspects of
information processing.
Normal distribution
• When many independent
random factors act in an
additive manner to create
variability, data will follow a
bell-shaped distribution called
the Gaussian distribution. This
distribution is also called a
Normal distribution.
• Although no data follows that
mathematical ideal, many
kinds of data follow a
distribution that is
approximately Gaussian
Dysfunction as a deviation from
normal distribution
• If we measure some
parameter in the
population with some
brain dysfunction,
then this parameter
must has a different,
not Gaussian
distribution.
• There are statistical
tests that measure this
difference.
Bimodal distribution in ADHD?
• Clinicians who diagnose this disorder have been criticized
for merely taking a percentage of the normal population
who have the most evidence of inattention and continuous
activity and labeling them as having a disease. In fact, it is
unclear whether the signs of ADHD represent a bimodal
distribution in the population or one end of a continuum of
characteristics. This is not unique to ADHD as other
medical diagnoses, such as essential hypertension and
hyperlipidemia, are continuous in the general population,
yet the utility of diagnosis and treatment have been proven.
Nevertheless, related problems of diagnosis include
differentiating this entity from other behavioral problems
and determining the appropriate boundary between the
normal population and those with ADHD.
Life span normative EEG
database (LNDB)
• There are at least four eyes-closed LNDB:
• 1) E. Roy John et al. (1977)
• 2) Frank Duffy et al. (1994)
• 3) Robert Thatcher et al. (1987)
• 4) Barry Sterman et al. (199?)
Three goals of LNDB
• 1) to assess the neurological basis for the
patient’s complains (the issue of organicity)
• 2) to identify the weakness of
electrophysiological organization of the
brain (the issue of neurotherapy design)
• 3) to evaluate the efficacy of treatment ( the
issue of treatment evaluation)
• Thatcher, 1999
Active and “passive” conditions
for NDB
• 1) Eyes opened and eyes closed conditions
are often used in NDB, because of
simplicity and relative uniformity of
recording conditions.
• 2) Active tasks depend of many
uncontrolled factors, such as intensity of
stimuli, the subject’s involvement, the
distance from stimuli, etc. There are no
standards for active conditions.

More Related Content

What's hot

Benign variants in eeg
Benign variants in eegBenign variants in eeg
Benign variants in eegNeurologyKota
 
Artifacts & Normal variants in EEG
Artifacts & Normal variants in EEGArtifacts & Normal variants in EEG
Artifacts & Normal variants in EEGshahanaz ahamed
 
EEG Maturation - Serial evolution of changes from Birth to Old Age
EEG Maturation - Serial evolution of changes from Birth to Old AgeEEG Maturation - Serial evolution of changes from Birth to Old Age
EEG Maturation - Serial evolution of changes from Birth to Old AgeRahul Kumar
 
1 basics of eeg and fundamentals of its measurement
1 basics of eeg and fundamentals of its measurement1 basics of eeg and fundamentals of its measurement
1 basics of eeg and fundamentals of its measurementSwathy Ravi
 
EEG Variants with patterns by Murtaza Syed
EEG Variants with patterns by Murtaza SyedEEG Variants with patterns by Murtaza Syed
EEG Variants with patterns by Murtaza SyedMurtaza Syed
 
Normal EEG patterns, frequencies, as well as patterns that may simulate disease
Normal EEG patterns, frequencies, as well as patterns that may simulate diseaseNormal EEG patterns, frequencies, as well as patterns that may simulate disease
Normal EEG patterns, frequencies, as well as patterns that may simulate diseaseRahul Kumar
 
Benign variants of eeg
Benign variants of eegBenign variants of eeg
Benign variants of eegNeurologyKota
 
Electroenchephalography
ElectroenchephalographyElectroenchephalography
Electroenchephalographyimabongaigaon
 

What's hot (20)

Abnormal eeg
Abnormal eegAbnormal eeg
Abnormal eeg
 
Textbook of electroencephalography
Textbook of electroencephalographyTextbook of electroencephalography
Textbook of electroencephalography
 
normal eeg
 normal eeg  normal eeg
normal eeg
 
Benign variants in eeg
Benign variants in eegBenign variants in eeg
Benign variants in eeg
 
Artifacts in eeg final
Artifacts in eeg finalArtifacts in eeg final
Artifacts in eeg final
 
Basics of eeg signal
Basics of eeg signalBasics of eeg signal
Basics of eeg signal
 
Artifacts & Normal variants in EEG
Artifacts & Normal variants in EEGArtifacts & Normal variants in EEG
Artifacts & Normal variants in EEG
 
EEG Maturation - Serial evolution of changes from Birth to Old Age
EEG Maturation - Serial evolution of changes from Birth to Old AgeEEG Maturation - Serial evolution of changes from Birth to Old Age
EEG Maturation - Serial evolution of changes from Birth to Old Age
 
1 basics of eeg and fundamentals of its measurement
1 basics of eeg and fundamentals of its measurement1 basics of eeg and fundamentals of its measurement
1 basics of eeg and fundamentals of its measurement
 
Sleep activity in eeg
Sleep activity in eegSleep activity in eeg
Sleep activity in eeg
 
EEG Variants with patterns by Murtaza Syed
EEG Variants with patterns by Murtaza SyedEEG Variants with patterns by Murtaza Syed
EEG Variants with patterns by Murtaza Syed
 
Normal EEG patterns, frequencies, as well as patterns that may simulate disease
Normal EEG patterns, frequencies, as well as patterns that may simulate diseaseNormal EEG patterns, frequencies, as well as patterns that may simulate disease
Normal EEG patterns, frequencies, as well as patterns that may simulate disease
 
EEG
EEGEEG
EEG
 
Benign variants of eeg
Benign variants of eegBenign variants of eeg
Benign variants of eeg
 
Eeg presentation
Eeg presentationEeg presentation
Eeg presentation
 
EEG Generators
EEG GeneratorsEEG Generators
EEG Generators
 
Electroenchephalography
ElectroenchephalographyElectroenchephalography
Electroenchephalography
 
EEG INTERPRETATION
EEG INTERPRETATIONEEG INTERPRETATION
EEG INTERPRETATION
 
Triphasic waves in EEG
Triphasic waves in EEGTriphasic waves in EEG
Triphasic waves in EEG
 
EEG artefacts
EEG artefactsEEG artefacts
EEG artefacts
 

Similar to Eeg examples (20)

EEG_circut.ppt
EEG_circut.pptEEG_circut.ppt
EEG_circut.ppt
 
EEG_circuit.ppt
EEG_circuit.pptEEG_circuit.ppt
EEG_circuit.ppt
 
SUMSEM-2021-22_ECE6007_ETH_VL2021220701295_Reference_Material_I_04-07-2022_EE...
SUMSEM-2021-22_ECE6007_ETH_VL2021220701295_Reference_Material_I_04-07-2022_EE...SUMSEM-2021-22_ECE6007_ETH_VL2021220701295_Reference_Material_I_04-07-2022_EE...
SUMSEM-2021-22_ECE6007_ETH_VL2021220701295_Reference_Material_I_04-07-2022_EE...
 
Basics of EEG
Basics of EEGBasics of EEG
Basics of EEG
 
EEG in neurology and psychiatry
EEG in neurology and psychiatryEEG in neurology and psychiatry
EEG in neurology and psychiatry
 
EEG guest lecture_iub_eee541
EEG guest lecture_iub_eee541EEG guest lecture_iub_eee541
EEG guest lecture_iub_eee541
 
Eeg
EegEeg
Eeg
 
Clinical teaching on electroencephelography
Clinical teaching on electroencephelographyClinical teaching on electroencephelography
Clinical teaching on electroencephelography
 
Magnetoencephalography
MagnetoencephalographyMagnetoencephalography
Magnetoencephalography
 
Eeg by prc
Eeg by prcEeg by prc
Eeg by prc
 
Eeg by prc
Eeg by prcEeg by prc
Eeg by prc
 
EEG of Children and Sleep
EEG of Children and Sleep EEG of Children and Sleep
EEG of Children and Sleep
 
Eeg basics.drjma
Eeg basics.drjmaEeg basics.drjma
Eeg basics.drjma
 
EEG & Evoked potentials
EEG & Evoked potentialsEEG & Evoked potentials
EEG & Evoked potentials
 
Electrocardiogram pptx
Electrocardiogram pptxElectrocardiogram pptx
Electrocardiogram pptx
 
Eeg
EegEeg
Eeg
 
Chapter (1) Introduction to EEG
Chapter (1) Introduction to EEGChapter (1) Introduction to EEG
Chapter (1) Introduction to EEG
 
Eeg seminar
Eeg seminarEeg seminar
Eeg seminar
 
EEG
EEGEEG
EEG
 
eeg-17112611154112428491152828379272737.pdf
eeg-17112611154112428491152828379272737.pdfeeg-17112611154112428491152828379272737.pdf
eeg-17112611154112428491152828379272737.pdf
 

Recently uploaded

Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityPrincipled Technologies
 
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?Antenna Manufacturer Coco
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptxHampshireHUG
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024The Digital Insurer
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountPuma Security, LLC
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationRadu Cotescu
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Miguel Araújo
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Servicegiselly40
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationSafe Software
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsMaria Levchenko
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Scriptwesley chun
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Drew Madelung
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfEnterprise Knowledge
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Igalia
 
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Enterprise Knowledge
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024The Digital Insurer
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationMichael W. Hawkins
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking MenDelhi Call girls
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsEnterprise Knowledge
 

Recently uploaded (20)

Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivity
 
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
 
Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024Axa Assurance Maroc - Insurer Innovation Award 2024
Axa Assurance Maroc - Insurer Innovation Award 2024
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organization
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Service
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
 
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day Presentation
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI Solutions
 

Eeg examples

  • 1. EEG recordings in man Examples of records and results of analysis made by Braintune (St. Petersbuurg) hardware/software.
  • 2. Nyquist Theorem • The highest frequency which can be accurately represented is one-half of the sampling rate. • The sampling rate here is below the Nyquist frequency, so the result of sampling is nothing like the input:aliasing. • For practical purposes the sampling rate should be 10 higher than the highest frequency in the signal. •
  • 3. EEG is a difference in potential between two electrodes • If two electrodes are “active”, it is called “bipolar” recording. • If one electrode is “silent”, it is called “monopolar” recording. The reference sites: ear lobe, mastoid, nose.
  • 4. Bipolar vs. monopolar recordings • Monopolar recording is used in research, because it enables the researcher to localize the event of interest. • Bipolar recording is used in BF, because it reduces shared artifacts. Electrodes should be placed on the sites with the strongest gradients of the potentials under training.
  • 5. EMG and eye blink artifacts in EEG • These types of artifacts can be detected by visual inspection. • Eye blinks can be excluded from data analysis. • EMG should be taken into account during spectral analysis.
  • 6. EEG recorded at Cz • EEG is a mixture of waves at different frequencies and amplitudes.
  • 7. EEG recorded at T5 • At each time interval several sine-waves at different frequencies may be present in the signal.
  • 8. Quality control of EEG recording • 1) EEG amplifies must be calibrated with daily checks • 2) acquisition parameters must be checked daily and keep the same • 3) the same procedures must be employed in all individuals • 4) all artifacts must be eliminated or taken into account prior to spectral analysis.
  • 9. EMG Artifact • EMG artifact starts as low as 12 Hz and ranges to 300 Hz. Most of the spectrum lies between 30-150 Hz. • Sites F3, F4, T3, T4, P3, P4 can pick up EMG the massester and temporalis muscles. • Posterior electrodes can pick up EMG from occipitalis, trapezius and supraspinal muscles. • To avoid this type of artifact one can relax or position the head properly or change slightly the position of electrode. • Fz, Cz, Pz can give a relatively pure EEG signal.
  • 10. EKG artifact • ECG artifacts occur from the electrodes that pick up activity from underlying pulsating blood vessels in the scalp. • EKG artifact gets more prevalent with aging.
  • 11. Ocular, blinks and electroretinal activity • Eye movement and blinks artifacts occur in the delta range 0-4 Hz and occur over the anterior part of the scalp.
  • 12. The noise from the standard AC electrical line current • This noise can be diminished by the proper grounding of the equipment (both computer and amplifies). • It could be also eliminated by a so called notch filter which selectively removes 50 (60 for the US) Hz activity from the signal. • This noise could be attenuated by obtaining good contact of electrodes with the scalp. The electrode impedance less than 10 kOhms is desirable.
  • 13. EEG recording in man • Eyes opened condition. • Examples of different waves.
  • 14. Reviewing EEG • EEG is characterized by: • 1) voltage • 2) frequency (is used for BF) • 3) spatial location (is used for BF) • 4) inter-hemispheric symmetries • 5) reactivity (reaction to state change) • 6) character of waveform occurrence (random, serial, continuous) • 6) morphology of transient events
  • 15. Reviewing EEG: voltage • Amplitude is the voltage in microvolts measured from the peak of the wave to the trough of the wave. Varies from 10 mcV to 100 mcV with average around 20-50 mcV. •
  • 16. Reviewing EEG: frequency • Spectrums reflect the amount of energy in a certain frequency range of EEG. • Term monorhythmic means that a particular portion of EEG shows a rhythmic component in a singular frequency. • Term polyrhythmic means that several rhythmic frequencies are present in EEG. • The presence of large-amplitude delta- activity may indicate infarct or other lesion.
  • 17. Reviewing EEG: frequency • Slow (0-4 Hz) and high (more 20 Hz) frequency bands of EEG may pick up artifacts, such as eye movements and muscle activity, and therefore should be evaluated with caution. • Despite the use of artifact rejection algorithms, the failure to accurately distinguish true physiological rhythmicity from the artifacts is a serious shortcoming of current software systems and requires the expert assessment.
  • 18. Reviewing EEG: transient events • A transient is an isolated form or feature that stands out from the background activity. • It is called a spike if it has the duration less than 70 msec. • It is called a sharp wave if it has the duration between 70 and 200 msec. • The presence of large amplitude spikes and waves may indicate the presence of epilepsy.
  • 19. Maps of EEG spectrums in standards bands • Eyes opened condition.
  • 20. EEG recording in man • Eyes closed condition. • Enhancement of alpha waves.
  • 21. Maps of EEG spectrums • Eyes closed condition
  • 22. EEG spectrums • Three conditions (EC, R, M) are compared to Eyes Opened condition. • Two peaks (in theta and alpha band) with different scalp distribution are observed. • Reading and math produce big (but different) changes in alpha band and small changes in theta and beta bands. • Note that alpha activities are different for all four conditions both in distribution and frequency.
  • 23. EEG spectrums in individual bands • Regular theta - idling rhythm • Irregular theta - working activity • Reading and math produce alpha rhythms that are different in frequency and location.
  • 24. EEG as a sequence of micro- states • EEG consists of series of short-lasting quasi- stationary epochs corresponding to what Lehmann et al. (1987) have called brain functional micro-states. • EEG reflects the changes in the state of neuronal networks rather than specific aspects of information processing.
  • 25. Normal distribution • When many independent random factors act in an additive manner to create variability, data will follow a bell-shaped distribution called the Gaussian distribution. This distribution is also called a Normal distribution. • Although no data follows that mathematical ideal, many kinds of data follow a distribution that is approximately Gaussian
  • 26. Dysfunction as a deviation from normal distribution • If we measure some parameter in the population with some brain dysfunction, then this parameter must has a different, not Gaussian distribution. • There are statistical tests that measure this difference.
  • 27. Bimodal distribution in ADHD? • Clinicians who diagnose this disorder have been criticized for merely taking a percentage of the normal population who have the most evidence of inattention and continuous activity and labeling them as having a disease. In fact, it is unclear whether the signs of ADHD represent a bimodal distribution in the population or one end of a continuum of characteristics. This is not unique to ADHD as other medical diagnoses, such as essential hypertension and hyperlipidemia, are continuous in the general population, yet the utility of diagnosis and treatment have been proven. Nevertheless, related problems of diagnosis include differentiating this entity from other behavioral problems and determining the appropriate boundary between the normal population and those with ADHD.
  • 28. Life span normative EEG database (LNDB) • There are at least four eyes-closed LNDB: • 1) E. Roy John et al. (1977) • 2) Frank Duffy et al. (1994) • 3) Robert Thatcher et al. (1987) • 4) Barry Sterman et al. (199?)
  • 29. Three goals of LNDB • 1) to assess the neurological basis for the patient’s complains (the issue of organicity) • 2) to identify the weakness of electrophysiological organization of the brain (the issue of neurotherapy design) • 3) to evaluate the efficacy of treatment ( the issue of treatment evaluation) • Thatcher, 1999
  • 30. Active and “passive” conditions for NDB • 1) Eyes opened and eyes closed conditions are often used in NDB, because of simplicity and relative uniformity of recording conditions. • 2) Active tasks depend of many uncontrolled factors, such as intensity of stimuli, the subject’s involvement, the distance from stimuli, etc. There are no standards for active conditions.