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Back to BasicsElectronics & Filters

In PSG Systems

Will Eckhardt, BS,RPSGT, CRT

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Conflicts

• I work for Respironics, Inc.

• I do not believe this has any influence on the content of this presentation.

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What Will Be Answered in this Presentation

• Where do EEG potentials originate?• We record various physiological signals what

means of processing do we utilize ?• What are the analog components of signal

processing?• What are the digital components of signal

processing?• An understanding some basic underlying

principles of the technology by looking at the analog signal output.

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Pyramidal Neuron

EEG is derived from thousands of synchronized pyramidal cell postsynaptic potentials.

Volume Conduction is the process of current flow through the tissues between the electrical generator and the electrode.

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Amplitude of the Recorded Potentials

• Depends on:– Intensity of the Electrical Source

– Distance of Source to Recording Electrodes

– Spatial Orientation• Orientation of the electrical generator to the electrode

– Electrical Resistance• Scalp-electrode interface• Recording electrodes

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Electrode Placement

• Exploring electrode

• Reference electrode

• Referential derivation

• Bipolar derivation

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Components of Polysomnography Equipment

and their relationship to signal processing.

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Path of Signals from the Patient to the Tracing

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Recording Electrodes

• Electrode types• Gold, Silver Chloride, Tin, Platinum

• Placement• 10-20 system

• Application• Electrode impedance

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Headbox• The headbox is an intermediate

connection conducting the electrical signal from the electrode to the amplifier.

• Enables multi-sensor output to one low impedance cable.

• The cable then connects to:– electrode selector panel (analog)– amplifier

• Note: the headbox may include the systems

amplifiers.

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Wave Form - Input & Output

• Voltage input to output using a known input.– 50µV– Square wave

• Gain setting (amount of amplification)• Filters (high, low, notch)• Sensitivity (amplifier output voltage to pen

deflection)

• Verify signal integrity– Like channels give the same output

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Types of Calibration

• Machine Cal – All channels respond the same

• Montage Cal – Channels respond as set

• Bio-Cal – Channels respond appropriately for the

maneuver/sensor– Should be performed at the beginning & end

of the study.

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Amplifiers

• Function: Signal modification– Amplification (↑ voltage of potential to drive pens or

card)– Discrimination (reveal differences in inputs 1 & 2)

• Inputs: Input 1 (G1) – Input 2 (G2)G1 exploring G2 reference

• Types: AC & DC Amplifiers• Digital and Analog Amplifiers

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Differential Amplifier

• Amplifies only the difference in voltage between two inputs.

• Does not amplify equal voltages.

• Has the ability to reject external interference.

• The amount that an amplifier will reject a common mode signal is called “common mode rejection ratio (CMRR).

• 10,000/1- Common mode/output voltageIdentical signals

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Signal Polarity

• Designed such that (-) voltage to input G1 of a differential amplifier [with respect to G2] will result in a upward deflection.

• When G1 becomes more (+) than G2 this will result in a downward deflection.

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AC Amplifier

• This type of amplifier is used for signals that vary frequently from positive to negative.

Examples: EEG, EMG, EOG

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DC Amplifier

• This type of amplifier is used for signals that slowly increase or decrease.

• Use DC amplifiers: – Used for signals i.e. oximetry, respiration, temp, PH.– Used to generate an output that is linear and can

scale (i.e. 0-100%).

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Display Features

• Controls that change the output from the amplifiers. – Amplification– Filters– Sampling rate– Monitor settings– Analog features

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Amplification

• Increases voltage difference between inputs.

• Small potentials° Voltage to drive pens (not often anymore)° Voltage for analog to digital converter (ADC)

• Boost voltage of biological signal µV to V• Characterized by:

° Gain° Sensitivity

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Gain

• Gain is a ratio: amplifier output voltage to input voltage.– Output of 10 V for input 10 µV = gain of 1

million

• Gain is the degree of magnification of the amplifier signal.

• We do not directly measured gain.

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Sensitivity• Relates to Ohm’s Law I=E/R or in PSG D=V/S

– Current (I) = Pen Deflection (D

– Voltage (E) = Input voltage (V)

– Resistance (R) = Sensitivity (S)

• Sensitivity is a ratio: of input voltage to deflection produced. Sensitivity = Voltage/Deflection

• Sensitivity is a measure of the response of an instrument to an incoming signal.– A sensitive instrument will produce a large response

to a small incoming signal.– A low sensitivity setting produces a large signal

change (deflection). • µV/mm (voltage per unit of pen deflection)• Exam may express as µV/cm

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Video Sensitivity

Sensitivity 2 2008_05_04_10_30_38.avi

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Computing the Voltage

• Measure the amplitude of the wave– Peak to trough

• The vertical distance of the rise or deflection (in mm) is multiplied by the sensitivity of the amplifier.– Analog sensitivity is on a dial

• Gives us the voltage of the wave.

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Sensitivity Settings

•The higher the sensitivity setting the smaller the wave (deflection).•V/S=D •The sensitivity setting affects how the wave is displayed, it does not change the actual voltage.

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Sensitivity Equations

• S=V/D 5=50µV/10mm

• V=SxD 50µV=5x10mm

• D=V/S 10mm=50µV/5

Settings:Adult 5-7 µV/mmChildren 10 µV/mm

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Filters

• Filters give us the ability to focus on only the signal frequencies that we wish to see.• Bandwidth

• They attenuate unwanted signals.• Each channel can be optimized, using

filters, to allow only signals in the desired frequency range.

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Bandwidth

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Low Frequency Filter (LFF)

• The low frequency filter is also known as the “High Pass” filter.

• This means that the LFF allows higher frequencies to pass unchanged while lower frequencies are attenuated.

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Low Frequency Filtering on EEG Channels

Note: Increasing the filter setting attenuates slow waves.

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Low Frequency Filters

Examples of typical LFF settings by derivation:

• EEG = 0.3 Hz (C4-C3-O1-O2)• EOG = 0.3 Hz (LOC-ROC)• EMG = 10 Hz (Chin, Leg, Intercostals)• EKG = 0.3 Hz

The AASM Manual for the Scoring of Sleep and Associated Events Rules, Terminology and Technical Specifications, 2007

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High Frequency Filter (HFF)

• The high frequency filter is also known as the “Low Pass” filter.

• This filter lets slower waves through and attenuates higher frequencies.

• Examples– HFF eliminates muscle artifact or external electrical

artifact in the EEG channels.– Caution: This filter can also attenuate desired high

frequencies such as arousals

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High Frequency Filters

Note: Increasing the filter setting allows more fast waves to be seen.

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High Frequency Filters

• EEG = 35 Hz

• E0G = 35 Hz

• EMG = 100 Hz

• ECG = 70 Hz

The AASM Manual for the Scoring of Sleep and Associated Events Rules, Terminology and Technical Specifications, 2007

Examples of typical HFF settings by derivation:

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• The time constant is a measure of how a signal is displayed and is determined by the voltage of the signal and the low and high frequency filters used. – Time constant = time (seconds) for the signal

to change a specified amount. – Two time constants come into play, the rise

time constant and the fall time constant.

Time Constants

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Time Constants

• Fall time constant = the time it takes (in seconds) for a square wave to decay to 37% of its maximum amplitude.– The fall time constant is usually what the term “time

constant” refers to in polysomnography.– The LFF determines the fall time constant. – ↑ the LFF setting will ↓ the time constant.

• Rise time constant = the time it takes (in seconds) for the square wave to reach 63% of its maximum amplitude. – The HFF determines the rise time constant.

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Time Constants

Time Constant

Fall time constant = time for the signal to decay from its peak to 37%

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Video Time Constant

Time Constant 3 2008_05_04_14_40_05.avi

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LFF - Fall Time Constant

LFF (HZ) TC (sec)

0.1

0.3

1

5

1

0.4

0.12

0.05

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60 Hertz / Notch Filter

• 60 Hz artifact is a high frequency artifact caused by:– Poor impedance – Interference from surrounding electrical

equipment – Poor application of electrodes

• Notch filters attenuate specific frequencies.• Do not use unless you must!

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Sampling RateDigital Systems

• The shape of the wave form on the display is determined by how frequently the signal is sampled. – The higher the sampling rate, the more frequently the

signal is sampled. – The more frequent the sampling, the more accurate

the shape. • The minimum acceptable sampling rate is 2.5

times greater than the highest high frequency filter.

• Nyquist theorem: – 2x the fastest freq. = The Nyquist Rate

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sampling rate

Low sampling rate

Input signalLow sampling rate

High sampling rate

Samplling Rates

Signal Desirable Minimal

EEG 500 Hz 200 Hz

EOG 500 Hz 200 Hz

EMG 500 Hz 200 Hz

ECG 500 Hz 200 Hz

Airflow/Pr 100 Hz 25 Hz

Oximetry 25 Hz 10 Hz

Effort 100 Hz 25 Hz

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Waveform DisplayDigital Systems

• The resolution capabilities:– Computer -bits– Monitor – Resolution

• bits – refer to the digital amplitude resolution by the ADC. – E.g. 8-bit ADC has 28 or 256 amplitude levels

• The resolution of the monitor is expressed by the number of pixels, or points of light.– The higher the number of pixels, the greater the

resolution of the monitor. – The number of pixels is stated for the horizontal and

vertical axis of the monitor (must be >:1600 x 1200). The AASM Manual for the Scoring of Sleep and Associated Events Rules, Terminology and Technical Specifications, 2007

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Dynamic Range

• Analog & Digital systems

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Troubleshooting from the Patient to the Tracing

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Questions?

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References• EEG Primer Basic Principles of Digital and Analog

EEG, B Fisch• Fundamentals of EEG Technology Basic Concepts

and Methods, F Tyner, J Knott• Principles and Practice of Sleep Medicine, M Kryger,

T Roth, W Dement• Sleep Disorders Medicine Basic Science, Technical

Considerations, and Clinical Aspects, S Chokroverty• Sleep Medicine, T Lee-Chiong, M Sateia, M

Carskadon• The AASM Manual for the Scoring of Sleep and

Associated Events - Rules, Terminology and Technical Specifications, 2007