Download Digital EEG System - Illinois Society of Electroneurodiagnostic

The Illinois Society of
Electroneurodiagnostic
Technologists (ISET)
Fall Meeting:
Electronics Crash Course for
Technologists
Saturday, November 9, 2013
Michael A. Stein, MD
Digital EEG System:
Transformation

PART 2:

‘BlackBox’ Transformation
Digital EEG System:
Transformation

The next stage in the
EEG system serves the
following functions:



(1) Filtering of unwanted
activity outside of the
desired bandwidth.
(2) Amplification of
Desired Signal within the
bandwidth.
(3) Noise reduction.
Digital EEG System:
Transformation

In this regards, 3 important
characteristics of EEG
amplifiers are:




(a) A flat frequency response
within the passband (discussed
in Part 1 of this course).
(b) A high common mode
rejection ratio.
(c) A high input impedance.
The latter 2 properties will be
discussed later in this course.
Digital EEG System:
Transformation

First, a reminder from Part 1 about :

In this regards, 3 important characteristics of EEG amplifiers
are:
 (a)
A flat frequency response within the
passband (discussed in Part 1 of this
course).


(b) A high common mode rejection ratio.
(c) A high input impedance.


In the case of a hi-fidelity sound system a bandwidth of approximately (20 –
20k Hz) with approximately equal gain is important since this is the range of
audible frequencies.
If the gain is not approximately equal in this range then the reproduced
sound heard by the listener will differ from the sound which was recorded.

Since the audio of cellular phones typically only
includes voice data, the frequency response needs to
have relatively equal gain over a narrower bandwidth of
about (300 – 3,000)Hz.


Since the EEG activity generated by the cortex which reaches the scalp has an
even narrower bandwidth, and part of this is obscured by muscle artifact, the
frequency response only needs to be equal in gain from about (0.5 - 70) Hz.
Since lower and higher frequencies consist of artifacts, they are deliberately
filtered out.
Digital EEG System:
Transformation

Although it is easier to understand these 3 functions if thought
of separately, they are typically built into a single amplifier
circuit.



(1) Filtering of unwanted activity outside of the desired bandwidth.
(2) Amplification of Desired Signal within the bandwidth.
(3) Noise reduction.
Operational
Amplifier – aka:
OpAmp
Differential
Amplifier
Digital EEG System:
Transformation:
(1) Filtering of Unwanted Signal
Reminder from Part 1:
Terminology


Therefore, need to filter out frequencies that are both lower than and higher than the
desired bandwidth of the signal being measured (EEG).
This can be done with either analog or digital electronics by use of both:





(1) Low frequency/high pass filters, and
(2) High frequency/low pass filters.
These two together (low frequency filter + high frequency filter) form a bandpass or
passband filter. Ideally, the bandpass will be the same as the bandwidth of the desired signal
(EEG).
In Part 1 the filtering which was discussed is due to the biophysical properties of the
electrode and is unintended and can lead to degradation in EEG signal quality.
In contrast, at this stage of the EEG amplifier, the filtering is designed to filter out
unwanted signals outside of the desired bandwidth, while passing EEG activity within
the desired passband without change.
Digital EEG System:
Transformation:
(1) Filtering of Unwanted Signal


Since there are both low frequency and high
frequency sources of noise, both low
frequency and high frequency filters are
needed.
Examples of low frequency noise sources:




Examples of high frequency noise sources:





Cardiac pulsation
Sweat
Roving eye movements
Line/Mains/60 Hz
Medical devices (oscillating ventilators, etc.)
Cellular telephones, radios, etc.
Together these 2 filter types combine to form
a bandpass filter.
The objectives of the bandpass filter are:


To filter out as much undesired signal as
possible
To pass as much desired signal as possible
without altering it
Digital EEG System:
Transformation:
(1) Filtering of Unwanted Signal
(1) Low Frequency Filtering:


Since scalp EEG contains very low
frequency information (slow wave
sleep, slow spike and wave, etc.),
the low frequency filter will need to
have a low cutoff frequency.
In almost all systems there is
overlap in frequency between
desired signal and unwanted signal.


(e.g. Slow spike and wave and
cardiac pulsation artifact).
A tradeoff is therefore necessary in
the degree of filtering and the
chosen cutoff frequency.
Reminder from Part 1:
Digital EEG System:
Low Frequency Filters

(A) Low frequency (aka high pass)
filters:

(fc) = 1 / (2π x RC) =
1 / (2π x tc)

Example:
R = 10,000Ω
 C = 16μF
 (fc) = 1 / (2π x RC) =
1 / (2π x 10,000 x 16x10-6) =
1Hz.

(Therefore, this circuit creates a
single pole, low frequency filter
with a cutoff frequency of 1 Hz.)
Digital EEG System:
Transformation:
(1) Filtering of Unwanted Signal
(2) High Frequency Filtering:


Since scalp EEG begins to be
obscured by muscle artifact above
30 Hz but EEG signal includes
activity in this range as well, the
high frequency filter cutoff
frequency is chosen as a tradeoff
between these factors.
In almost all systems there is
overlap in frequency between
desired signal and unwanted signal.

(e.g. Paroxysmal fast EEG activity
and cellular telephone artifact).
Reminder from Part 1:
Digital EEG System:
High Frequency Filters

(A) High frequency (aka low pass)
filters:

(fc) = 1 / (2π x RC) =
1 / (2π x tc)

Example:
R = 100Ω
 C = 16μF
 (fc) = 1 / (2π x RC) =
1 / (2π x 100 x 16x10-6) =
100 Hz.

(Therefore, this circuit creates a
single pole, high frequency filter
with a cutoff frequency of 100
Hz.)
Digital EEG System:
Transformation:
(1) Filtering of Unwanted Signal

Together these two filters (low frequency filter and high frequency filter)
create a bandpass filter.

Although this passband has some overlap with both low and high frequency
sources of noise/artifact, these occur mostly beyond the 3 dB cutoff
frequencies and will therefore be reduced in amplitude at the output of the
EEG amplifier.
+
=
EEG Filter Examples:
(1) Background Activity
No filters
Filters: (LFF = 1 Hz, HFF = 50 Hz)
EEG Filter Examples:
(2) Interical Epileptiform Activity
No filters
Filters: (LFF = 1 Hz, HFF = 50 Hz)
EEG Filter Examples:
(3a) Ictal/Seizure Activity
No filters
Filters: (LFF = 1 Hz, HFF = 50 Hz)
EEG Filter Examples:
(3b) Ictal/Seizure Activity
No filters
Filters: (LFF = 1 Hz, HFF = 50 Hz, Notch Filter = 60 Hz)
Digital EEG System:
Transformation:
(2) Amplification of Desired Signal


Terminology:
Operational Amplifiers (aka: OpAmps).


Simple electronic circuits which amplify the signal so that the output is larger than
the input.
Examples:

(1) Cellular telephone transmission:


(2) Hi-fidelity sound system:


Signal needs to be amplified so there is enough power to carry over great distances.
Signal needs to be amplified so there is sufficient power to mechanically move the
loudspeakers enough to create audible sound.
(3) EEG system:

Signal needs to be amplified so that it is large enough to be viewed on a computer
monitor.
Digital EEG System:
Transformation:
(2) Amplification of Desired Signal

There are different types of OpAmps and
OpAmp circuits.

(a) For a basic inverting OpAmp:




Rin = input resistance
Rf = feedback resistance
Gain = amplification factor -(Vout / Vin) = -(Rf / Rin)
(b) For a non-inverting OpAmp:

Gain = +(Vout / Vin) = +(1 + (R2 / R1))
Digital EEG System:
Transformation:
(2) Amplification of Desired Signal

(c) For a Differential
OpAmp:

There are 2 inputs




(The difference between the 2 inputs
is amplified.)
Rin = input resistance
Rf = feedback resistance
Rg = ground resistance
Vout = (Rf + R1)xRg
(Rg + R2)xR1
x V2
_ (R ) x V
f
(R1)
1
Digital EEG System:
Transformation:
(2) Amplification of Desired Signal

Differential Amplifiers:



Used for nearly all
neurodiagnostic
applications.
More meaningful since
difference between two
inputs is amplified.
Better noise reduction.
Digital EEG System:
Transformation:
(2) Amplification of Desired Signal

Differential Amplifier Function:

(The difference between the 2 inputs is amplified.)
Digital EEG System:
Transformation:
(2) Amplification of Desired Signal


Use of Differential Inputs for typical EEG
montages:
(a) Bipolar Montage:
Digital EEG System:
Transformation:
(2) Amplification of Desired Signal


Use of Differential Inputs for typical EEG
montages:
(b) Referential Montages:
Common Reference
Common Average Reference
Digital EEG System:
Transformation:
(3) Noise Reduction

Why is noise reduction improved with a differential amplifier
compared to a unipolar OpAmp?


The unipolar OpAmp amplifies the difference between a single input
channel and ground.
In biomedical applications, ground is typically physically far removed
from the signal being measured (e.g. EEG electrodes).
Unipolar
Operational
Amplifier – aka:
OpAmp
Differential
Amplifier
Digital EEG System:
Transformation:
(3) Noise Reduction

Why is noise reduction improved with a differential amplifier compared to
a unipolar OpAmp?


Since the two input channels (signal and ground) are separated in space, they will be
subject to different noise sources (environmental noise (radio, cell phone, medical
instrumentation, etc), 60 Hz line noise, etc.).
This difference in noise sources creates a difference at the input of the amplifier
which then gets amplified by the gain factor of the unipolar amplifier along with the
desired signal. This leads to a noisy output.
Digital EEG System:
Transformation:
(3) Noise Reduction

Why is noise reduction improved with a differential amplifier compared to
a unipolar OpAmp?


Amplifiers also generate their own internal electronic noise.
Since the 2 inputs in a unipolar amplifier have unbalanced resistance/impedance,
there will be a difference in the level of noise at each of the 2 amplifier inputs which
will be amplified along with the desired signal also leading to a relatively noisy output
signal.
Digital EEG System:
Transformation:
(3) Noise Reduction

Why is noise reduction improved with a differential amplifier compared to
a unipolar OpAmp?



In comparison, with EEG systems, a differential amplifier typically amplifies the
differences between 2 nearby biological inputs (e.g. 2 adjacent EEG electrodes).
Since these input signals are close, they are subject to essentially the same noise
sources.
Since the same noise sources are present at both inputs, and the difference between
the two inputs is amplified, the noise should cancel when the 2 input signals are
“subtracted”.
Digital EEG System:
Transformation:
(3) Noise Reduction

Why is noise reduction improved with a differential amplifier compared to
a unipolar OpAmp?


Also, both inputs of the differential amplifier have similar input
resistance/impedance.
Therefore the internal noise from the amplifier is nearly the same at both input
channels and nearly cancels as well.
Digital EEG System:
Transformation:
(3) Noise Reduction


Terminology:
One important property of amplifiers relating to
noise reduction is their Common Mode
Reduction Ratio (CMRR).
Digital EEG System:
Transformation:
(3) Noise Reduction


Terminology: CMRR
Since a differential amplifier amplifies the
difference between the signals present at its 2
inputs, the components of the signals which are
the same (or in common) at the 2 inputs will be
cancelled.
Digital EEG System:
Transformation:
(3) Noise Reduction


Terminology: CMRR
Because CMRR can vary over a very wide range
(roughly 1:1,000,000) this value is typically expressed on
a logarithmic scale in decibels (dB).


CMRR in dB = 20 x log (reduction ratio).
Example:

If a differential amplifier reduces the common mode signal at its 2
inputs by a factor of 10,000 compared to the desired/differential (e.g.
EEG signal), then:


CMRR = 20 x log 10,000 = 20 x log 104 = 20 x 4 = 80 dB.
The CMRR in this case then is 10,000 = 80 dB.
Digital EEG System:
Transformation

In this regards, 3 important
characteristics of EEG amplifiers
are:




(a) A flat frequency response
within the passband (discussed in
Part 1 of this course).
(b) A high common mode
rejection ratio.
(c) A high input
impedance.
The latter 2 properties will be
discussed later in this course.
Reminder from Part 1:
Digital EEG System:
Input: Electrodes

The scalp/conductive gel/electrode interface acts
as a load on the EEG amplifier input.

The primary property which differs at the scalp/conductive gel/electrode
interface level is the impedance.
Keratin and oils in the skin increase impedance. These can be reduced during
skin preparation by use of abrasives and alcohol prep respectively.
Even with these preparation measures, the skin leads to the highest degree of
signal quality loss in the input stage of the EEG system.
The impedance of the electrode/electrolyte interface ranges from 100’s of
Ohms (Ωs) to MegaΩs depending on the frequency of the signal and the
quality of skin preparation.



Digital EEG System:
Transformation:
Amplifier Input Impedance


High EEG amplifier input impedance is also important
in order to maintain a flat frequency response within
the desired bandwidth.
The impedance of the EEG electrodes act as a load on
the input of the differential amplifier.
Input
Amplifier

Since the skin/electrolyte/electrode interface is the input to the
amplifier and has both resistive and capacitive components, once
connected to the amplifier, the resulting circuit has:



(a) voltage divider properties.
(b) filter properties
Both of these are undesired properties in this application which we try
to minimize with proper skin preparation techniques and choice of
electrode materials.
Input
Amplifier
Reminder from Part 1:
Digital EEG System:
Low Frequency Filters

(A) Low frequency (aka
high pass) filters:

(fc) = 1 / (2π x RC) =
1 / (2π x tc)
Input Interface Stage:
Undesired Filter Properties

The circuit to the right is a simplified model
of the reactance component of the
combined EEG electrode-Amplifier input
interface.

This functions as a low frequency filter and
filters out low frequencies.

Unlike the electronic filters built into the
EEG amplifier circuit to filter out unwanted
signals outside of the desired passband, this
filtering is undesired and if not properly
controlled can lead to unintentional and
undesired filtering of frequencies within the
desired passband and distort the recorded
EEG signal.

This undesired filtering is due to the
capacitive properties of the
skin/electrolyte/electrode interface.
Reminder from Part 1:
Digital EEG System:
Input: Electrodes



For a voltage divider:
Vout = Vin x (R2/R1+R2)
In other words, the voltage divider divides the input voltage by
the ratio of resistances in the circuit.
Input Interface Stage:
Undesired Voltage Divider Properties

The circuit to the right is a simplified
model of the resistive component of
the combined EEG electrodeAmplifier input interface.

This functions as a voltage divider.

This leads to unintended/undesired
attenuation of the signal being
measured which decreases the signalto-noise ratio of the EEG system
which leads to a poorer quality signal.

This undesired attenuation is due to
the resistive properties of the
skin/electrolyte/electrode interface.
Digital EEG System:
Transformation

In this regards, 3 important characteristics
of EEG amplifiers are:

(a) A flat frequency response within the
passband (discussed in Part 1 of this
course).
(b) A high common mode rejection ratio.

(c) A high input impedance.


The latter 2 properties will be discussed later
in this course.
This voltage divider effect at the input stage of the loaded EEG amplifier
also explains why a high input impedance amplifier is needed.
Digital EEG System:
Transformation
This voltage divider effect at the input stage of the loaded EEG amplifier
also explains why a high input impedance amplifier is needed.

Therefore, to avoid undesirable
signal loss at the input stage of the
EEG amplifier, the following are
necessary:


Low electrode impedance.
High amplifier input impedance.
Reminder from Part 1:
Digital EEG System:
Input: Electrodes



For a voltage divider:
Vout = Vin x (R2/R1+R2)
In other words, the voltage divider divides the input voltage by
the ratio of resistances in the circuit.
Digital EEG System:
Input: Electrodes


For a voltage divider:
Vout = Vin x (R2/R1+R2)



R2 = the amplifier input resistance
R1 = the resistance of the electrode complex
Example1:




R2 = the input impedance of the EEG amplifier =1 MΩ
R1 = the resistance of the EEG electrode complex = 100Ω
The voltage is divided/attenuated by a factor of (R2/R1+R2) = 1,000,000/(1,000,000 + 100) = 0.999.
Therefore, there is very little loss or attenuation in this circuit.
Digital EEG System:
Input: Electrodes


For a voltage divider:
Vout = Vin x (R2/R1+R2)



R2 = the amplifier input resistance
R1 = the resistance of the electrode complex
Example2:

R2 = 1 MΩ

R1 = 100,000Ω (due to poor scalp preparation and/or a defective electrode).

The voltage is divided/attenuated by a factor of (R2/R1+R2) = 1,000,000/(1,000,000 + 100,000) =
0.910.
This leads to 9% loss or attenuation in this circuit which will lead to significant decrease in the signal-tonoise ratio, and imbalance of this channel compared to the other EEG channels.

Digital EEG System:
Input: Electrodes


For a voltage divider:
Vout = Vin x (R2/R1+R2)



R2 = the amplifier input resistance
R1 = the resistance of the electrode complex
Example3:

R2 = 10,000 Ω (due to a poor or inexpensive amplifier design with low input impedance).

R1 = 1,000Ω.
The voltage is divided/attenuated by a factor of (R2/R1+R2) = 10,000/(10,000 + 1,000) = 0.910.
This also leads to 9% loss or attenuation in this circuit which again will lead to significant decrease in the
signal-to-noise ratio, and imbalance of this channel compared to the other EEG channels.

