用于治疗神经精神疾病的深部脑刺激闭环系统。

IF 2.7 Expert review of medical devices Pub Date : 2024-12-01 Epub Date: 2024-12-10 DOI:10.1080/17434440.2024.2438309
Arjun Balachandar, Onanong Phokaewvarangkul, Alfonso Fasano
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引用次数: 0

摘要

一个闭环或反馈控制系统是一个过程,它考虑系统的输出,以自动调整输入。与传统的开环系统相比,闭环系统可以在最少的人为干预下实现更高的精度。闭环“适应性”深部脑刺激(aDBS)的新方法正在被开发。涵盖领域:本综述侧重于aDBS治疗各种神经精神疾病的现状:常见的运动障碍,如帕金森病、肌张力障碍、原发性震颤和图雷特综合征,以及抑郁症和强迫症等精神障碍。最后,讨论了闭环神经调节治疗的未来发展方向。专家意见:最近,与开环DBS相比,aDBS已被证明具有优势。然而,了解各种疾病病理状态的生物标志物对于aDBS的实施至关重要,改进的传感硬件和机器学习的进步将使其有效实施。
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Closed-loop systems for deep brain stimulation to treat neuropsychiatric disorders.

Introduction: A closed-loop or feedback-control system is a process which considers the system's output in order to automatically adjust the input. Compared to a traditional open-loop system, a closed-loop system allows for a higher degree of accuracy with minimal human intervention. Novel methods of closed loop 'adaptive' deep brain stimulation DBS (aDBS) are being developed.

Areas covered: This review focuses on the current state of aDBS for various neuropsychiatric conditions: common movement disorders such as Parkinson's disease, dystonia, essential tremor, and Tourette syndrome, as well as psychiatric disorders of depression and obsessive-compulsive disorder. Finally, the future directions of closed-loop neuromodulation treatments are also discussed.

Expert opinion: Recently, aDBS has been shown to offer benefits compared to open-loop DBS. Understanding the biomarkers of pathological states across various disorders is, however, crucial to implementation of aDBS, and improved sensing-capable hardware and advances in machine learning are poised to allow its effective implementation.

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