Proceedings of the 25' Annual lntemational Conference of the IEEE EMBS Cancun, Mexico September 17-21,2003

Comparing Objective MLAEP Detection Techniques in Time- and Frequency- Domain for Anaesthesia Monitoring

M. Cagy and A. F. C. Infantosi Biomedical Engineering Program, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil

mcagy@peh.ufrj.hr; afci@peh.ufrj .br

Absfracf - The mid-latency auditory evoked potential (MLAEP) has been used to monitor anaesthesia by means of objective methods, such as Magnitude Squared Coherence (MSC), an Objective Response Detection (ORD). This work compares MSC with a time-domain ORD technique, the Evoked Potential Detector (DPE), using simulation and real EEG under auditory stimulation during propofol-induced anaesthesia. Using simulation, MSC distinguishes the changes in the amplitude and stretching better than DPE. For EEG under auditory stimulation, both MSC and DPE reflect infusion protocol. For the first, the choice of maximal response harmonic before infusion is a good criterion (even for simulated signal). Besides, the well-established distribution for the alternative hypothesis of existence of response allows the estimation of confidence limits to MSC and so the comparison with a pre-established threshold in order to suggest the transition from consciousness to unconsciousness and vice- versa. On the other hand, DPE is a. much simpler technique, involving considerably fewer computational calculations. Therefore, both MSC and DPE can be pointed out as potential techniques to be used in anaesthesia monitoring based on MLAEP.

Keywords - Monitoring, Auditory Evoked Potential, Anaesthesia.

INTRODUCTION

As signals directly related to the Central Nervous System, , the electroencephalogram (EEG) and some modalities of evoked potentials have been investigated in monitoring depth of anaesthesia. The mid-latency auditory evoked potential (MLAEP) suffers dose-dependent changes with the use of several anaesthetic drugs.

Some objective methods for anaesthesia monitoring based on MLAEP use frequency-domain techniques to analyse the evoked potential, such as Magnitude Squared Coherence (MSC), an Objective Response Detection (ORD) 111. Nevertheless, the use of frequency-domain techniques depends on the choice of the frequency-hand to monitor. For MSC specifically, as its probability distribution has been already stated for both null and alternative hypothesis [2], the maximum-response hand could he pointed as the one to he monitored [3].

This work aims to compare MSC with a time-domain ORD technique (Evoked Potential Detector - DPE) using simulation and real EEG under auditory stimulation during propofol-induced anaesthesia.

MATERIALS AND METHODS

A. The Magnitude Squared Coherence (MSC)

MSC is a statistical test that provides a p value (significance level) for, in our case; the repetitive click auditory stimulation effect on EEG. The MSC between one deterministic periodic signal (pulse train of stimuli) and other random (observed EEG) can he defined as:

where 2, (f) is the Discrete Fourier Transform (DFT) of

the jth epoch of EEG signal, xj[n], sampled at A with N samples,f= kfo (for k0,I ,..., N-l and f, = $',!, ), and M is the number of epochs.

Assuming x [ n ] a Gaussian white noise, the statistical distribution of MSCV), for the null hypothesis of no response, is related to the F-distribution [Z] and this can be used to detect responses by comparing the value of MSCY) to critical values, according to

where FCrir l,2M.z,a is the critical value of the F-distribution

for a significance level a.. For the alternative hypothesis of response presence, the

distrihution'of MSCV) follows a non-central F-distribution [2]. Critical values can he approximately derived from fitting a central F-distribution as:

true unknown value of MSC. Then, the confidence limits for the true MSC can be derived based on the critical values of its estimation [2].

This work received financial suppon from CNPq and FAPERJ, Brazil

0-7803-7789-3/03/$17.00 02003 IEEE 3199

B. The Evoked Potenfial Detector (DPE)

The DPE can be defined, similarly to MSC, as:

, ,

(4)

where

N , = N'N,+1 and [N,, NI] define the interest window within each epoch of EEG, which is previously high-pass (20 Hz) and low-pass (60 Hz) filtered (Znd order Bufferworth).

For the null hypothesis of no response, assuming x[n] a Gaussian white noise, the statistical distribution of A[n] is related to the F-distribution just like MSC but with different degrees of freedom (FI.M.I). Considering the Central Limit Theorem, the distribution of DPE approximates a normal distribution with the same mean as A[n] and a variance N , times lower. Based on this distribution, critical values can be derived to detect response.

C. Simulation

The waveform referring to the j lh signal epoch was simulated as:

where x j [ n l = z j [ n ] + r j [ n ] , (6)

corresponds to MLAEP and q[n] refers to spontaneous EEG (modelled as Gaussian white noise); fi = 1 kHz, Aj and Bj are parameters of amplitude and stretching. Each epoch contains 654 samples with five concatenated responses (corresponding to a stimulation frequency&, = 7.645 Hz).

Keeping noise variance constant, the MLAEP evolution during anaesthesia was simulated varying the parameters A, e 4. in order to reflect amplitude and latencies changes. During the first 15 min, both Aj e Bj values were unitary (no infusion). Then Aj was progressively decreased and Ej increased, denoting the anaesthesia effect, for 90 min. In the last 15 min, these parameters resumed values close to the starting. Signal-to-noise ratio (SNR) varied between -34 dB (before infusion) and -44 dB (minimum AI).

D. Experimental Protocol

Venous propofol was used for induction and maintenance of anaesthesia without pre-anaesthetic drugs. Two volunteers (normal adults) after oral and written explanation, had EEG acquired during auditory stimulation in the Bristol Royal Infirmary (UK), being the protocol ethically approved. This signal was collected using a 1401-

family system from Cambridge Electronic Design (12 bits) as follows:

'no anaesthetic infusion, for about 650 s; step-infusion during 4!i minutes at the rate of 3 mg/Kg/h (within the recommended range for sedation in adults: 0.3 to 4 mgKgih); step-infusion during additional 45 minutes at the rate of 9 mgiKgih (anaesthesia range: 4 to 12 mgKgih); infusion interruption, being the EEG acquired until the subjects woke up. The consciousness level of the volunteers was assessed

based on the pressing of B soft-touch switch in response to the lighting of a LED each 15 s. The unconsciousness (non- responsiveness) is assumed when the pressing is interrupted. For the auditory stimulation, clicks during 700 ps were used, yielding a true stimulation period of 130.8 ms (&,;m = 7.645 Hz); sound pi-essure level was of 75 dBspL

E. Acquisition and Pre-processing

The electrodes were located in accordance with the 10- 20 system at Cz (vertex) and A1 or A2 (auricular lobes), grounded in FPz. Mains interference (50 Hz) was attenuated using an odd-half-length srimulation period, and so successive epochs show interference in phase opposition., The EEG was both high-pass (17 Hz) and low-pass (250 Hz) filtered (and order Butfenvarfh) and then digitised at 1 kHz.

F. Esfimafing MSC and LlPE

For real EEG, MSC was estimated in 2 min-long segments ( M = 183) according to expression (1) with each I,(f) calculated in epochs of raw EEG with N=654 samples (five stimuli), and so a spectral resolution of 0.2f,,,. In the example of Fig. 1 (volunteer #1 under no anaesthetic effect), highly significant peaks of MSCY) occurred in the harmonics off,im within the range from 45 to 120 Hz. For frequencies among these harmonics, MSCY) shows values below 0.0150 (MSC,,;,, for a = 1%). After around 26 min of infusion, MSCV) has values generally below MSC,,;,, even for the harmonics offr,;", suggesting the suppression of auditory rer:ponse.

I l l

Fig. 1. MSCY) before infusiori (volunteer # I ) , The maximal-response harmonic (6'h = 45.9 Hz) was used for monitoring. The horizontal line

indicates the 1% critical value.

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Using also M = 183 for simulated signal, the most significant response occurs in the 51h harmonic of (38.2 Hz) before simulated infusion (Fig. 2). Based on [3], this highest significant harmonic was used to monitor MSC. The same procedure is employed with real EEG.

0.08

0.06. 0 cn 5 0.04-

-

-'

Frequency (Hz)

Fig. 2. MSCV) of simulated signal before infusion. The maximal- response harmonic (Sh = 38.2 Hz) was used for monitoring.

Horizontal line indicates 1% critical value.

DPE was estimated using the same durations for segments and epochs as MSC. All the five response intervals within each epoch were windowed between 15 and 100 ms, considered the usual limits of MLAEP occurrence. The critical value of DPE for a = 1% was obtained using simulation (DPECn, = 0.0063). Further, in order to make visualization easier, the time-evolution of both parameters suffered null-phase (forward and backward) moving-average filtering (time-constant = 6 min).

RESULTS

A. Simulation

The time-evolution of both parameters is depicted in Fig. 3, where one can note that MSC reflects better the signal changes than DPE. In the first and last 15 min, both are greater then their rcspective critical values, and hence resemble a situation without infusion. During the time (90min) when the anaesthetic effect on MLAEP was mimetized, MSC and DPE initially show a progressive decreasing but the trespassing of the 1% critical value (horizontal line) occurs only for MSC. During this period, DPE fluctuates around DPE,,,.

B. MLAEP Acquired During Anaesthesia

The time evolution of MSCM at thc most significant harmonic of (6Ih for both volunteers) chosen from the maximal-response band (Fig. 4a and 4c) reflects the infusion protocol, as wcll as DPE (Fig. 4b and 4d). For volunteer #1 (Fig. 4a and 4b), both parameters show a more pronounced reduction after circa 25 min of anaesthetic infusion, staying

I I

3201

around or below the critical value (not rejecting the null hypothesis of no response for a = 1%) and showing a recover trend at the end.

M S C 0.2

0.1 n

0

OPE

0.01

0.005 -

I o 1 1 5 60 105

Fig. 3 . MSC and DPE o f simulated signal during infusion. Horizontal lines indicate 1% +tical values.

Anaesthesia Evolution (min)

. .

For volunteer #2 (Fig. 4c and 4d), although there is a reduction of both parameters during the sedation period, one can distinguish the values during the two infusion rates. During anaesthesia both parameters show values around the critical values, being the inferior confidence limit (5%) of MSC below this threshold. After the end of infusion the consciousness recover is suggested by the increase of the parameters. The high peak occurring at the beginning of anaesthesia is due to the arousal effect of a noxious stimulus (blood sampling).

(b) OPE

. ,.. , , . . ,

55 100 (4

0.6

0.4

0.2 0.05 T:

Anaesthesia Evolution (min) O 10 55 100 Anaesthesia Evolution (min)

Fig. 4. Time-Evolution of. (a and c) MSC and its confidence IimiU (5%) in the 6'h harmonic ofJ,,& (b and d) DPE. The horizontal dotted lines

represent the critical values for ci = I % The vertical lines indicate the transitions of anaesthetic infusion rate.

D i s c u s s i o ~ AND CONCLUSION

Using simulation, MSC shows higher sensitivity than DPE, distinguishing better the changes in the amplitude and stretching. It is related to the narrow-band composition of the response waveform (around 40 Hz). As the maximal

stretching (5, = 1.25) shifted the waveform band to around 32 Hz, still within the filtering band of DPE (20-60 Hz), this parameter was not affected by waveform stretching. On the other hand, the frequency-specific nature of MSC reflected both attenuation and stretching effects. Although both parameters are dependent on SNR, MSC should bring better results when S N R changes are concentrated in a frequency band.

For the EEG under auditory stimulation, both MSC and DPE reflect infusion protocol. The choice of maximal response harmonic [3] before infusion to monitor MSC can be considered a good criterion, even for simulated signal. Besides, the well-established distribution for the alternative hypothesis of existence of response [2 ] allows the estimation of confidence limits to MSC and so the comparison with a pre-established threshold in order to suggest the transition from consciousness to unconsciousness and vice-versa. On the other hand, DPE is a much simpler technique, involving considerably fewer computational calculations.

Therefore, both MSC and DPE can be pointed out as potential techniques to be used in anaesthesia monitoring based on MLAEP.

ACKNOWLEDGEMENTS

The authors gratefully acknowledge the assistance from Dr. Albert0 Esteves Gema.1 for collecting the EEG data.

REFERENCES

M. Cagy and A. F. I:. Infantmi, “Estimating unconsciousness onset using frequency- and time-domain parameters extracted from MLAEP”, Proc, NBC 2002, Reykjavik, Iceland, pp. 397-

A. M. F. L. Miranda de SA, A. F. C. lnfantosi and D. M. Simpson, “Coherence between one random and one periodic signal for measuring the strength of responses in the EEG during sensory stimulation”, Med. B i d E n g Compul., vol. 40, n. I , pp.

M. Cagy, A. F. C. Infantosi, “Assessing maximal-response frequencies for anaesthesia”, IFMBE Proc. EMBEC’ 2002, Vienna - Austria, vol. 3, p. 392-393.2002,

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