Depth of hypnosis regulation using nonlinear control approach

Khaqan, Ali; Riaz, Raja Ali

doi:10.1109/eit.2016.7535222

Cited by 4 publications

(7 citation statements)

References 6 publications

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“…The varying in the induction phase period for patients will affected by many parameters like age, weight, gender and height. These parameters also affected on the infusion rate for each patient as we see in drug rate, more drug dose as shown also in [4,6,9] while in [8] the rate for the two-drug used was changed always with time. This mean that it needs good monitoring from the doctors responsible of anesthesia process then when the patient is stable and entered in the hypnosis level.…”

Section: Discussionmentioning

confidence: 88%

“…But if analyzing the controlling action for the induction and maintenance phase, induction period will start from the starting of the surgery till reach 50 seconds. It is shown in Figure 5, but in [4], it will start from the starting till at approximately two and half minute it mean after 150 seconds and in [6] start from starting to approximately 80 seconds while in [7] reach to five minutes and then the maintenance phase will start after that till finishing the surgery for all [4,6,7,9]. The varying in the induction phase period for patients will affected by many parameters like age, weight, gender and height.…”

Section: Discussionmentioning

confidence: 97%

“…The response of the proposed controller obtained in this study was compared with the other studies. In fact, the same patient model and the same propofol drug used for controlling the action in [4,6] while in [5,9] used two drug propofol and regimental. But if analyzing the controlling action for the induction and maintenance phase, induction period will start from the starting of the surgery till reach 50 seconds.…”

Section: Discussionmentioning

confidence: 99%

“…While in [6] a nonlinear design method is presented by using the SMC method for calculating the infusion rate, all the cases give better values as compared with the desired value within the acceptable range for surgery. Also, in [7] extended prediction, selfadaptive control (EPSAC) method has been used.…”

Section: Introductionmentioning

confidence: 99%

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Design of adaptive neuro sliding mode controller for anesthesia drug delivery based on biogeography based optimization

Abood¹,

Karam²,

Issa³

2019

IJACR

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Monitoring depth of anesthesia (DOA) is a significant point in general anesthesia (GA). It can be obtained from the assessment of the drug dose carefully and preciously. As a benefit of drug delivery automation, closed-loop method will present several advantages. It may prevent excessive dose amount or less needed dose and the controlled feedback system can decrease the cost of the healthcare by reducing the patient recovery period. This paper addresses the use of adaptive sliding mode controllers (ASMC) for calculating the depth of anesthesia by administrating a dose of propofol drug and measure patient state according to the monitoring device the bispectral index (BIS). In this study, we suggest a simple nonlinear control strategy consists of an ASMC combined with single neuron self-tune neural controller. It is used for maintaining DOA and reducing the effect of the nonlinear element. The adaptive controller uses the BIS value measured as a reference tracking value and propofol dose rate as a control signal. The parameters of the controller are tuned using a procedure based on the biogeography-based optimization (BBO) algorithm. The results indicate that including adaptive parts of the controller and tune its gains needed by BBO algorithm may enable optimal and stable performance for controller for all patients. It also provides fast reach to the induction phase and stay in a stable value in maintenance phase, which reflects the efficient response of the suggested controller if it compared to other nonlinear controllers. It is also justified by the results obtained that the suggested controller gives a very good response.

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Section: Discussionmentioning

confidence: 88%

Section: Discussionmentioning

confidence: 97%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Design of adaptive neuro sliding mode controller for anesthesia drug delivery based on biogeography based optimization

Abood¹,

Karam²,

Issa³

2019

IJACR

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“…Although control of analgesia is still a challenge, significant advances have been made in the automatic control of hypnosis and neuromuscular blockade [ 3 , 4 ]. For hypnosis control, different techniques using both signal-based and mode-based methodologies have been used successfully [ 5 , 6 , 7 ]. “Intelligent” techniques have also been implemented [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Intelligent System to Perform Fault Detection on BIS Sensor During Surgeries

Casteleiro‐Roca

Calvo-Rolle

Pérez

et al. 2017

Sensors

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This paper presents a new fault detection system in hypnotic sensors used for general anesthesia during surgery. Drug infusion during surgery is based on information received from patient monitoring devices; accordingly, faults in sensor devices can put patient safety at risk. Our research offers a solution to cope with these undesirable scenarios. We focus on the anesthesia process using intravenous propofol as the hypnotic drug and employing a Bispectral Index (BISTM) monitor to estimate the patient’s unconsciousness level. The method developed identifies BIS episodes affected by disturbances during surgery with null clinical value. Thus, the clinician—or the automatic controller—will not take those measures into account to calculate the drug dose. Our method compares the measured BIS signal with expected behavior predicted by the propofol dose provider and the electromyogram (EMG) signal. For the prediction of the BIS signal, a model based on a hybrid intelligent system architecture has been created. The model uses clustering combined with regression techniques. To validate its accuracy, a dataset taken during surgeries with general anesthesia was used. The proposed fault detection method for BIS sensor measures has also been verified using data from real cases. The obtained results prove the method’s effectiveness.

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Optimized Intelligent PID Controller for Propofol Dosing in General Anesthesia Using Coati Optimization Algorithm

Namel,

Sahib

2024

Communications in Computer and Information Science

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Depth of hypnosis regulation using nonlinear control approach

Cited by 4 publications

References 6 publications

Design of adaptive neuro sliding mode controller for anesthesia drug delivery based on biogeography based optimization

Design of adaptive neuro sliding mode controller for anesthesia drug delivery based on biogeography based optimization

Hybrid Intelligent System to Perform Fault Detection on BIS Sensor During Surgeries

Optimized Intelligent PID Controller for Propofol Dosing in General Anesthesia Using Coati Optimization Algorithm

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