Fleming John E, Senneff Sageanne, Lowery Madeleine M
Neuromuscular Systems Laboratory, UCD School of Electrical & Electronic Engineering, University College Dublin, Dublin, Ireland.
Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Mansfield Road, Oxford OX1 3TH, United Kingdom.
J Neural Eng. 2023 Oct 4;20(5). doi: 10.1088/1741-2552/acfbfa.
. Closed-loop deep brain stimulation (DBS) methods for Parkinson's disease (PD) to-date modulate either stimulation amplitude or frequency to control a single biomarker. While good performance has been demonstrated for symptoms that are correlated with the chosen biomarker, suboptimal regulation can occur for uncorrelated symptoms or when the relationship between biomarker and symptom varies. Control of stimulation-induced side-effects is typically not considered.A multivariable control architecture is presented to selectively target suppression of either tremor or subthalamic nucleus beta band oscillations. DBS pulse amplitude and duration are modulated to maintain amplitude below a threshold and avoid stimulation of distal large diameter axons associated with stimulation-induced side effects. A supervisor selects between a bank of controllers which modulate DBS pulse amplitude to control rest tremor or beta activity depending on the level of muscle electromyographic (EMG) activity detected. A secondary controller limits pulse amplitude and modulates pulse duration to target smaller diameter axons lying close to the electrode. The control architecture was investigated in a computational model of the PD motor network which simulated the cortico-basal ganglia network, motoneuron pool, EMG and muscle force signals.Good control of both rest tremor and beta activity was observed with reduced power delivered when compared with conventional open loop stimulation, The supervisor avoided over- or under-stimulation which occurred when using a single controller tuned to one biomarker. When DBS amplitude was constrained, the secondary controller maintained the efficacy of stimulation by increasing pulse duration to compensate for reduced amplitude. Dual parameter control delivered effective control of the target biomarkers, with additional savings in the power delivered.Non-linear multivariable control can enable targeted suppression of motor symptoms for PD patients. Moreover, dual parameter control facilitates automatic regulation of the stimulation therapeutic dosage to prevent overstimulation, whilst providing additional power savings.
迄今为止，用于帕金森病（PD）的闭环深部脑刺激（DBS）方法通过调节刺激幅度或频率来控制单一生物标志物。虽然已证明对于与所选生物标志物相关的症状具有良好性能，但对于不相关症状或生物标志物与症状之间的关系发生变化时，可能会出现调节欠佳的情况。通常不考虑对刺激引起的副作用进行控制。
本文提出了一种多变量控制架构，以选择性地针对震颤或丘脑底核β波段振荡的抑制。调节DBS脉冲幅度和持续时间，以将幅度维持在阈值以下，并避免刺激与刺激引起的副作用相关的远端大直径轴突。一个监督器在一组控制器之间进行选择，这些控制器根据检测到的肌肉肌电图（EMG）活动水平来调节DBS脉冲幅度，以控制静止性震颤或β活动。一个辅助控制器限制脉冲幅度并调节脉冲持续时间，以针对靠近电极的较小直径轴突。该控制架构在PD运动网络的计算模型中进行了研究，该模型模拟了皮质-基底神经节网络、运动神经元池、EMG和肌肉力量信号。
与传统的开环刺激相比，观察到静止性震颤和β活动均得到良好控制，且传递的功率降低。监督器避免了使用针对一种生物标志物进行调谐的单个控制器时出现的过度刺激或刺激不足。当DBS幅度受到限制时，辅助控制器通过增加脉冲持续时间来维持刺激效果，以补偿幅度降低。双参数控制实现了对目标生物标志物的有效控制，并额外节省了传递的功率。
非线性多变量控制能够对PD患者的运动症状进行靶向抑制。此外，双参数控制有助于自动调节刺激治疗剂量，以防止过度刺激，同时还能额外节省功率。
