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PEAK-TO-PEAK AMPLITUDE OF EEG FOR THE MONITORING OF BRAIN FUNCTION

Michael NavakatikyanBrainZ Instruments, Auckland,

New Zealand

Aims

To introduce:

• A new measure of peak-to-peak amplitude (ppA)

And to describe:

• Its differences and similarities with another ppA measure, namely, aEEG.

peak

trough

ppA

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aEEG: A Representation of ppA

Example of cardiac arrest

Designed for continuous long-term monitoring of ppA in unconscious adults

Maynard, Prior & Scott (1969) BMJ. 4: 545-6

aEEG: Application for Neonates

0

10

100

µV

Quiet Sleep

Awake/Active Sleep

• Found application in neonatal EEG monitoring, producing distinct patterns for different:

a) background statesb) seizures andc) sleep-wake cycling

• Proved to be sensitive to high frequency artefact

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But does aEEG measure ppA in neonates accurately?

aEEG: ppA Distortion that Depends on Frequency

aEEG

0

10 Hz

100 µV

1 s

57 µV

5 Hz 1 Hz

8 µV

Raw EEG

100µV

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How aEEG depends on frequency of cEEG?

• Reduces the values of ppA greatly around α-rhythm• α-rhythm is not present in neonates, its average frequency is much lower• Thus values of aEEG are about 3 to 6 times lower than ppA of raw EEG signal, but we never know how much

FREQUENCY, HZ

0 10 20 30

aEEG, % of Input ppA of sine wave

0

50

100 Effectively – a detector of α-rhythm, which is not present in neonates

The aim: to create a method for measuringppA without frequency distortion

New method transforms raw EEG into another signal, called rEEG

rEEG

0

10 Hz

100 µV 100 µV

5 Hz 1 Hz

100 µV

Raw EEG

100µV

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What is the main idea behind our method of

ppA calculation?

rEEG: The Idea

There are 3 waves in a selected interval. Values of ppA range from 34 to 45 µV

45µV42µV 34µV

max

min

47µV

If we subtract min from max on this interval we will get a ppA-estimate of 47 µV

It is higher than average ppA on interval but close enough

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rEEG: Calculation

New method transforms cEEG into another signal, called rEEG, from word “range”.(Note: Range in statistics is difference between max and min)

EEG

rEEG

0

2-sec

max

min

max

min

min

max

rEEG = Max – Min on time interval

0

rEEG: Calculation Example – Upper Estimate of ppA

ppAµV

0

30

0 2 4 6 8 10 12 14

time, sManualrEEG

EEGµV

-15

15

ppAµV

0

30

0 2 4 6 8 10 12 14

time, sManualrEEG

EEGµV

-15

15

ppAµV

0

30

0 2 4 6 8 10 12 14

time, sManualrEEG

ppAµV

0

30

0 2 4 6 8 10 12 14

time, sManualrEEG

EEGµV

-15

15

ppAµV

0

30

0 2 4 6 8 10 12 14

time, sManualrEEG

EEGµV

-15

15

ppAµV

0

30

0 2 4 6 8 10 12 14

time, sManualrEEG

EEGµVEEGµV

-15

15

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rEEG – Examples of recording

rEEG is also (as aEEG) a compressed representation, it has a semi-logarithmic scale with cut off value of 50 µV

34 weeks

25 weeks

0

50

250

25

500

0

50

250

25

500

1:00:00 2:00:00 3:00:00 4:00:000

Cut off50 µV

rEEG : we can discern conventional EEG amplitude from it rather accurately

LM = 5-15 µV?

UM = 100-200 µV?rEEG, 3 hr

µV

0

50

250

25

500

100

10

8

μV

0

100

-100

Raw EEG

rEEG0

50

25

500

100

10

On 5-min stretch: Yes – ppA = 10 to 250 µV But does rEEG produce distinct patterns we used to see in neonates?

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0

50

250

25

0

10

50μV aEEG

rEEG

rEEG - aEEG: Sleep-wake Cycles Similarity

The reason for similarities in aEEG and rEEG pattern is that they both represent ppA, albeit

with a different degree of accuracy

DNV LV FTCNV BS

0

10

50μV 0

50

250

25rEEG

aEEG

rEEG – aEEG: Background Patterns Similarity

Thresholds of 25 and 10 µV are suggested as roughly equivalent to 10 and 5 µV thresholds for aEEG

Classification by Hellstrőm-Westas, de Vries and Greisen (2006) NeoReviews, 7: c76-c87

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rEEG - aEEG: Seizures Similarity

Seizures look like the narrowing amplitude band with elevated lower margin, because ppA becomes more

uniform during seizure activity

Seizures

rEEG - aEEG: High frequency artefact mimicking seizures is less pronounced

EMG artefact

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Conclusions

• An accurate measure of ppA (peak-to-peak amplitude)

• Has similar to aEEG patterns

• Can bridge the gap between cEEG-based and aEEG-based assessment of brain function

• For example, it can be used to assess discontinuity and IBI (inter-burst interval) on raw EEG

rEEG:

Any questions, please?