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Monitoring and Control in

Anaesthesia: an Implementation

Example

Catarina S. Nunes

Department of Applied Mathematics

Faculty of Sciences, University of Porto, Portugal

Research

Main Investigation topics

Modelling, identification and forecasting methods

Data analysis, clustering and knowledge extraction

Neural and decision support networks

Mathematical aspects of control systems design

Fault detection and alarm systems

Development and implementation of hybrid control algorithms

Software development

Medical Applications

Automatic control of drug delivery systems

Decision support and control in anaesthesia

Modelling and control of physiologic variables

http://pharmaria.fc.up.pt

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• Anaesthesia includes paralysis, unconsciousness (i.e. DOA) and

analgesia;

• Balanced anaesthesia, i.e. use of 3 drugs;

• DOA direct measurements are not available;

• The Bispectral Index (BIS) of the Electroencephalogram (EEG), a

multivariable regression model combining different features into a

linear numeric index, ranging from 0 (isoelectric EEG) to 100 (fully

awake).

• Auditory evoked potentials (AEP), i.e. evoked brain potentials, are

used to measure DOA (AEP are EEG responses to clicks applied to

both ears).

• State Entropy: EEG and EMG processing using Spectral Entropy.

Case Study: Depth of Anaesthesia (DOA)

Awareness

• “Anesthesia awareness is the phenomenon of being mentally alert (and terrified) while supposedly under full general anesthesia. The patient is paralyzed, unable to speak, and totally helpless to communicate his/her awareness. Actual cutting pain may or may not be present. “

• “The mission of the Anesthesia Awareness Campaign is to prevent patients (even one) from experiencing anesthesia awareness and its consequences through education, prevention, and empowerment by replacing ignorance or fear with knowledge.”

• “Anesthesia awareness continues to be reported between 100-200 times daily in the United States, in addition to an unknown number worldwide. Researchers believe that anesthesia awareness is under-reported by 50%-100% and occurs between 4-6 times more often in pediatric surgeries.”

http://www.anesthesiaawareness.com/

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Model Variability

ControlReference Error Action Unconsciousness

Analgesia

DEPTH OF ANAESTHESIA

Drug Interaction

AIM

Research Team

Faculty of Sciences

(Department of Applied

Mathematics)

Catarina S. Nunes

Teresa Feio Mendonça

Scholarships:

Nadja Bressan

Ana Castro

PhD Students:

Susana Brás

Hospital Geral de Santo António

(Department of Anaesthesiology)

Pedro Amorim

Francisco Lobo (also PhD Student)

Neurosurgery:

Isabel Alexandra Santos

Manuela Casal

Leónia Ferreira

Urology:

Eduarda Amadeu

Paula Sá Couto

Fátima Martins

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Research Team

University of Trás-os-Montes &

Alto Douro

(Department of Veterinary)

Luís Antunes

David A. Ferreira

PhD Students:

Heber Alves

Animal Hospital of Porto

Lénio Ribeiro (also PhD Student)

Institute of Molecular and Celular

Biology (Animal Welfare)

Ana Olsen,

Ana MariaValentim (Scholarship)

University Fernando Pessoa – Porto

(Pharmacology)

Pedro Barata

Institute of Oncology (Genetics)

Rui Medeiros

Case Study: Depth of Anaesthesia (DOA)

induced effectsensor

time varying

clinician

control

algorithm

computer infusion

pump

intravenous

administration

disturbances

observation noise

patient

Global main features:

!high interindividual variability

!input constraints in the control action

!level noise in measurements

!high degree of reliability

!good performance

!time varying parameters

Control objective: tracking a reference level

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Pharmacodynamic Drug Interactions

• Zero-interaction: the effect of the combination is the sum of the effects of the individual agents;

• Synergistic: the effect of the combination is greater than that expected as based on the concentration effect relationships of the individual agents;

• Antagonistic: the effect of the combination is less than the sum of the effects of the individuals;

• Propofol (anaesthetic) and Remifentanil (analgesic) have a synergistic interaction.

Anaesthesiologist

Initial Patient Response

!!!! 15 minutes (non-steady state)

Goal: Extracting from initial data Patient individual features

Control Modelling

Nunes CS, Mendonça TF, Antunes L, Ferreira DA, Lobo F, Amorim P. Modelling Drug’s Pharmacodynamic Interaction during General

Anaesthesia: the choice of Pharmacokinetic Model. Modelling and Control in Biomedical Systems 2006 (Including Biological Systems).

D. D. Feng, O. Dubios, J. Zaytoon and E. Carson, eds. Oxford, United Kingdom, Elsevier Science Ltd: 447-452, 2006.

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Potency

of the

mixture

Number of units (U)associated with 50%

of maximum effect

at ratio "

Normalised

concentrations

to the respective

potencies

Effect =

Interaction Model

Bruhn, J.; et al., 2003, Anesthesiology, vol. 98, pp. 621-627.

Real BIS values – 45 PatientsModelled BIS

0 5 10 1510

20

30

40

50

60

70

80

90

100

minutes

BIS

0 5 10 1510

20

30

40

50

60

70

80

90

100

minutes

BIS

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Predictive Adaptive Control of the Bispectral Index of the

EEG (BIS) - using the intravenous anaesthetic drug propofol

Mendonça T, Nunes CS, Magalhães H, Lemos JM, Amorim P: Predictive Adaptive Control of Unconsciousness –

Exploring Remifentanil as an Accessible Disturbance. Proceedings of the IEEE International Conference on Control Applications,

CCA06, Munich, Germany, October 4-6, pp. 205-210, 2006.

MUSMAR

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LNAI 4253 (Springer), Part 2: pp. 148-1455, 2006.

Fuzzy Logic – ANFIS – Modelling BIS

Journal of Intelligent and Fuzzy Systems 16(1):15-22, 2005

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Trainning Data

Testing Data