Fuzzy logic control of depth of anaesthesia using auditory evoked responses

Linkens, D.A.; Abbod, Maysam F.; Backory, J.K.

doi:10.1049/ic:19961127

Cited by 10 publications

(3 citation statements)

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“…The output variable (DOA) has six linguistic levels: awake, light, okFlight, ok, okFdeep and deep. The details of the rule-bases derived either from anaesthetists' experience or self-learning via clinical trials have been reported in a previous study by Linkens et al (1996). Table 2 shows a rule-base for the CVFDOA classifier where the input variable ranges are given by the following base lines of the inputs: SAP range:…”

Section: Fuzzy Logic Rule-based Classifier For Cv-based Doamentioning

confidence: 99%

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Clinical implementation of advanced control in anaesthesia

Linkens

Abbod

Peacock

2000

Transactions of the Institute of Measurement and Control

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A multi-sensor fusion system for monitoring and control of depth of anaesthesia in the operating theatre is described. Two types of anaesthesia measures are considered, the first being based on auditory evoked responses, while the second measure is based on cardiovascular system signals. The first measure is based on analysis of the signal using wavelets and a neuro-fuzzy system, while the second measure is based on analysis of the measurements using a rule-based fuzzy logic system. The two measures are combined to give a final level of depth of anaesthesia using another rule-based fuzzy logic system. The depth of anaesthesia level is fed back to a target controlled infusion system (TCI) to control the infusion of the drug propofol for maintaining a constant level of depth of anaesthesia.

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Section: Fuzzy Logic Rule-based Classifier For Cv-based Doamentioning

confidence: 99%

“…Muscle relaxation has been controlled using a fuzzy logic controller. In recent work by the authors, neural networks and fuzzy logic have been used to control the amount of infused drug using a rule-based fuzzy logic controller (Linkens et al, 1996). This paper describes the structure of a real-time data-fusion system based on fuzzy logic.…”

Section: Introductionmentioning

confidence: 99%

Clinical implementation of advanced control in anaesthesia

Linkens

Abbod

Peacock

2000

Transactions of the Institute of Measurement and Control

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“…In various studies, the latencies of the characteristic peaks of the MLAEP are obtained after visual inspection, and these are interpreted by an expert to get the DOA. In an automated system, these features have to be automatically extracted; such a feature extraction method using a neural network as a time-series approximation was described and used in (4). Previous studies (5,6) have also required that the baseline observations be obtained as these are used with the intra-operative observations to calculate the depth of anaesthesia.…”

Section: Introductionmentioning

confidence: 99%

Diagnosis and decision-making for awareness during general anaesthesia

Backory

Abbod

Linkens

1998

UKACC International Conference on Control (CONTROL '98)

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This is the post-print version of the article. The official published version can be obtained from the link below.We describe the design process of a diagnostic system for monitoring the anaesthetic state of patients during surgical interventions under general anaesthesia. Mid-latency auditory evoked potentials (MLAEPs) obtained during general anaesthesia are used to design a neuro-fuzzy system for the determination of the level of unconsciousness after feature extraction using multiresolution wavelet analysis (MRWA). The neuro-fuzzy system proves to be a useful tool in eliciting knowledge for the fuzzy system: the anaesthetist's expertise is indirectly coded in the knowledge rule-base through the learning process with the training data. The anaesthetic depth of the patient, as deduced by the anaesthetist from the clinical signs and other haemodynamic variables, noted down during surgery, is subsequently used to label the MLAEP data accordingly. This anaesthetist-labelled data, used to train the neuro-fuzzy system, is able to produce a classifier that successfully interprets unseen data recorded from other patients. This system is not limited, however, to the combination of drugs used here. Indeed, the similar effects of inhalational and analgesic anaesthetic drugs on the MLAEPs demonstrate that the system could potentially be used for any anaesthetic and analgesic drug combination. We also suggest the use of a closed-loop architecture that would automatically provide the drug profile necessary to maintain the patient at a safe level of sedation

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Constrained closed‐loop control of depth of anaesthesia in the operating theatre during surgery

Mahfouf

2005

Adaptive Control & Signal

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The constrained version of generalized predictive control (GPC) which employs the quadratic programming (QP) approach is evaluated for on-line administration of an anaesthetic drug in the operating theatre during surgery. In the first instance, a patient simulator was developed using a physiological model of the patient and the necessary control software was validated via a series of extensive simulation experiments. Such a validated system was then transferred into the operating theatre for a series of clinical evaluation trials. The clinical trials, which were performed with little involvement of the design engineer, led to a good regulation of unconsciousness using fixed-parameters as well the adaptive version of the algorithm. Furthermore, the constrained algorithm displayed good robustness properties against disturbances such as high stimulus levels and allowed for safe and economically effective administration of the anaesthetic agent isoflurane.

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Fuzzy logic control of depth of anaesthesia using auditory evoked responses

Cited by 10 publications

References 0 publications

Clinical implementation of advanced control in anaesthesia

Clinical implementation of advanced control in anaesthesia

Diagnosis and decision-making for awareness during general anaesthesia

Constrained closed‐loop control of depth of anaesthesia in the operating theatre during surgery

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