The use of a PID controller to model vecuronium pharmacokinetics and pharmacodynamics during liver transplantation. Proportional-integral-derivative

Model-based closed-loop control of thalamic deep brain stimulation

Introduction: Closed-loop control of deep brain stimulation (DBS) is beneficial for effective and automatic treatment of various neurological disorders like Parkinson's disease (PD) and essential tremor (ET). Manual (open-loop) DBS programming solely based on clinical observations relies on neurologists' expertise and patients' experience. Continuous stimulation in open-loop DBS may decrease battery life and cause side effects. On the contrary, a closed-loop DBS system uses a feedback biomarker/signal to track worsening (or improving) of patients' symptoms and offers several advantages compared to the open-loop DBS system. Existing closed-loop DBS control systems do not incorporate physiological mechanisms underlying DBS or symptoms, e.g., how DBS modulates dynamics of synaptic plasticity. Methods: In this work, we propose a computational framework for development of a model-based DBS controller where a neural model can describe the relationship between DBS and neural activity and a polynomial-based approximation can estimate the relationship between neural and behavioral activities. A controller is used in our model in a quasi-real-time manner to find DBS patterns that significantly reduce the worsening of symptoms. By using the proposed computational framework, these DBS patterns can be tested clinically by predicting the effect of DBS before delivering it to the patient. We applied this framework to the problem of finding optimal DBS frequencies for essential tremor given electromyography (EMG) recordings solely. Building on our recent network model of ventral intermediate nuclei (Vim), the main surgical target of the tremor, in response to DBS, we developed neural model simulation in which physiological mechanisms underlying Vim-DBS are linked to symptomatic changes in EMG signals. By using a proportional-integral-derivative (PID) controller, we showed that a closed-loop system can track EMG signals and adjust the stimulation frequency of Vim-DBS so that the power of EMG reaches a desired control target. Results and discussion: We demonstrated that the model-based DBS frequency aligns well with that used in clinical studies. Our model-based closed-loop system is adaptable to different control targets and can potentially be used for different diseases and personalized systems.

MUSCLE RELAXATION CONTROLLED BY AUTOMATED ADMINISTRATION OF CISATRACURIUM

In this paper, the muscle relaxant agent (i.e., cisatracurium) and three clinical control methods (i.e., 13 patients undergoing intermitted bolus control, 15 patients undergoing intensive manual control and 15 patients) undergoing automatic fuzzy logic control (FLC), were used for maintaining depth of muscle relaxation (DOM) during surgery. Cisatracurium, a muscle relaxation drug with long-term effect, low metabolic loading, but long delay time, is widely used in operating rooms and ICUs. Meanwhile, the rules for the FLC were developed from the experimental experience of intensive manual control after learning from 15 patient trials. According to experts' experimental experience, our FLC inputs were chosen from T1% error and trend of T1% which differ from other previous studies on eliminating the effect of time delay from cisatracurium. In individual clinical experimental results, the mean(SD) of the mean T1% error in 13 patients for intermitted bolus control, in 15 patients for intensive manual control, and in 15 patients for automatic control was 8.76(1.46), 1.65(1.67), and 0.48(1.43), respectively. The t test results show that automatic control is not significantly different from intensive manual control. The results show that a simple fuzzy logic controller derived from anesthetists ' clinical trials can provide good accuracy without being affected by the pharmacological time delay problem.