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安全且可耐受的闭环深部脑刺激的斜率评估与配置

Ramp Rate Evaluation and Configuration for Safe and Tolerable Closed-Loop Deep Brain Stimulation.

作者信息

Petrucci Matthew N, Wilkins Kevin B, Orthlieb Gerrit C, Kehnemouyi Yasmine M, O'Day Johanna J, Herron Jeffrey A, Bronte-Stewart Helen M

机构信息

Department of Neurology and Neurological Sciences at Stanford University, Stanford, CA, 94305 USA.

Department of Bioengineering at Stanford University, Stanford, CA, 94305 USA.

出版信息

Int IEEE EMBS Conf Neural Eng. 2021 May;2021:959-962. doi: 10.1109/ner49283.2021.9441336. Epub 2021 Jun 2.

Abstract

Closed-loop deep brain stimulation is a novel form of therapy that has shown benefit in preliminary studies and may be clinically available in the near future. Initial closed-loop studies have primarily focused on responding to sensed biomarkers with adjustments to stimulation amplitude, which is often perceptible to study participants depending on the slew or "ramp" rate of the amplitude changes. These subjective responses to stimulation ramping can result in transient side effects, illustrating that ramp rate is a unique safety parameter for closed-loop neural systems. This presents a challenge to the future of closed-loop neuromodulation systems: depending on the goal of the control policy, clinicians will need to balance ramp rates to avoid side effects and keep the stimulation therapeutic by responding in time to affect neural dynamics. In this paper, we demonstrate the results of an initial investigation into methodology for finding safe and tolerable ramp rates in four people with Parkinson's disease (PD). Results suggest that optimal ramp rates were found more accurately during varying stimulation when compared to simply toggling between maximal and minimal intensity levels. Additionally, switching frequency instantaneously was tolerable at therapeutic levels of stimulation. Future work should focus on including optimization techniques to find ramp rates.

摘要

闭环深部脑刺激是一种新型治疗方式,在初步研究中已显示出益处,且可能在不久的将来应用于临床。最初的闭环研究主要集中在根据感知到的生物标志物调整刺激幅度,而刺激幅度的变化速率(即“斜坡”速率)往往会让研究参与者察觉到这种调整。对刺激斜坡的这些主观反应可能会导致短暂的副作用,这表明斜坡速率是闭环神经系统的一个独特安全参数。这给闭环神经调节系统的未来带来了挑战:根据控制策略的目标,临床医生需要平衡斜坡速率,以避免副作用,并通过及时做出反应来影响神经动力学,从而使刺激保持治疗效果。在本文中,我们展示了对四名帕金森病(PD)患者寻找安全且可耐受的斜坡速率方法的初步研究结果。结果表明,与简单地在最大和最小强度水平之间切换相比,在不同刺激过程中能更准确地找到最佳斜坡速率。此外,在治疗性刺激水平下,瞬间切换频率是可耐受的。未来的工作应侧重于纳入优化技术来寻找斜坡速率。

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本文引用的文献

1
3
Demonstration of Kinematic-Based Closed-loop Deep Brain Stimulation for Mitigating Freezing of Gait in People with Parkinson's Disease.
Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:3612-3616. doi: 10.1109/EMBC44109.2020.9176638.
5
Deep Brain Stimulation Programming for Movement Disorders: Current Concepts and Evidence-Based Strategies.
Front Neurol. 2019 May 21;10:410. doi: 10.3389/fneur.2019.00410. eCollection 2019.
6
7
Dual threshold neural closed loop deep brain stimulation in Parkinson disease patients.
Brain Stimul. 2019 Jul-Aug;12(4):868-876. doi: 10.1016/j.brs.2019.02.020. Epub 2019 Feb 25.
8
A Chronically Implantable Neural Coprocessor for Investigating the Treatment of Neurological Disorders.
IEEE Trans Biomed Circuits Syst. 2018 Dec;12(6):1230-1245. doi: 10.1109/TBCAS.2018.2880148. Epub 2018 Nov 7.
9
Neuromodulation targets pathological not physiological beta bursts during gait in Parkinson's disease.
Neurobiol Dis. 2018 Dec;120:107-117. doi: 10.1016/j.nbd.2018.09.004. Epub 2018 Sep 6.
10
Eight-hours adaptive deep brain stimulation in patients with Parkinson disease.
Neurology. 2018 Mar 13;90(11):e971-e976. doi: 10.1212/WNL.0000000000005121. Epub 2018 Feb 14.

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