Closed-Loop Vagus Nerve Stimulation Based on State Transition Models

Abstract

Objective: Vagus nerve stimulation (VNS) is a potential therapeutic approach in a number of clinical applications. Although VNS is commonly delivered in an open-loop approach, it is now recognized that closed-loop stimulation may be necessary to optimize the therapy. In this paper, we propose an original generic closed-loop control system that can be readily integrated into an implantable device and allows for the adaptive modulation of multiple VNS parameters.

Methods: The proposed control method consists of a state transition model (STM), in which each state represents a set of VNS parameters, and a state transition algorithm that optimally selects the best STM state, minimizing the error between an observed physiological variable and a given target value. The proposed method has been integrated into a real-time adaptive VNS prototype system and has been applied here to the regulation of the instantaneous heart rate, working synchronously with cardiac cycles. A quantitative performance evaluation is performed on seven sheep by computing classical control performance indicators. A comparison with a proportional-integral (PI) controller is also performed.

Results: The STM controller presents a median mean square error, overshoot, and settling time, respectively, equal to 622.21 ms , 72.8%, and 7.5 beats.

Conclusion: The proposed control method yields satisfactory accuracy and time response, while presenting a number of benefits over classical PI controllers. It represents a feasible approach for multiparametric VNS control on implantable devices.

Significance: Closed-loop multiparametric stimulation may improve response and minimize side effects on current pathologies treated by VNS.