Online and personalised control of the Depth of hypnosis during induction using fractional order PID
Year: 2025
Type: article
Abstract: INTRODUCTION: The integration of information technology and control engineering has significantly increased in clinical practice research, especially in the management of drug dosing for general anaesthesia. OBJECTIVE: The main focus of the research is to achieve a personalised control of the Depth of Hypnosis based on a novel approach. The primary objective is to regulate the Bispectral Index by administering Propofol during the hypnotic phase of anaesthesia. METHODS: A fractional order time delay model is proposed to replace the conventional PK-PD model. This model is estimated online during the induction phase. A fractional order Proportional-Integral-Derivative (PID) controller is then individually tuned for each patient. RESULTS: The closed loop simulation results demonstrate that the proposed controllers effectively minimise undershoot and achieve a short time to reach the desired time-to-target for the majority of the patients. The analysis indicates that the proposed controller is capable of maintaining the BIS signal within a safe range. Comparative analyses with similar research are provided to effectively contextualise this study within the existing literature. Disturbance rejection tests during the maintenance phase are performed to demonstrate the effectiveness of personalised control. CONCLUSION: The online adaptation that this research brings, compared to the previous attempts, allows for significantly improved results for the hypnosis phase.
Source: Journal of Advanced Research
Language: English
Subfield: Anesthesiology and Pain Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $4,000
Awards: G1196538527, G1806829325, G2121609774, G2658751756, G285739660, G370840381, G4147897318, G4523609416, Development of an integrated end-to-end simulation platform for continuous manufacturing of oral tablets, G4912250859, G5675888258, G6167187853, Adaptive robust control of general anesthesia with event-based surgery optimization
OpenAlex ID: W4409016715
