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用于癫痫丘脑刺激的Percept™ PC BrainSense记录的神经信号数据收集与分析

Neural signal data collection and analysis of Percept™ PC BrainSense recordings for thalamic stimulation in epilepsy.

作者信息

Sanger Zachary T, Henry Thomas R, Park Michael C, Darrow David, McGovern Robert A, Netoff Theoden I

机构信息

Department of Biomedical Engineering, University of Minnesota, Minneapolis, United States of America.

Department of Neurology, University of Minnesota, Minneapolis, United States of America.

出版信息

J Neural Eng. 2024 Feb 6;21(1). doi: 10.1088/1741-2552/ad1dc3.

DOI:10.1088/1741-2552/ad1dc3
PMID:38211344
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11299490/
Abstract

Deep brain stimulation (DBS) using Medtronic's Percept™ PC implantable pulse generator is FDA-approved for treating Parkinson's disease (PD), essential tremor, dystonia, obsessive compulsive disorder, and epilepsy. Percept™ PC enables simultaneous recording of neural signals from the same lead used for stimulation. Many Percept™ PC sensing features were built with PD patients in mind, but these features are potentially useful to refine therapies for many different disease processes. When starting our ongoing epilepsy research study, we found it difficult to find detailed descriptions about these features and have compiled information from multiple sources to understand it as a tool, particularly for use in patients other than those with PD. Here we provide a tutorial for scientists and physicians interested in using Percept™ PC's features and provide examples of how neural time series data is often represented and saved. We address characteristics of the recorded signals and discuss Percept™ PC hardware and software capabilities in data pre-processing, signal filtering, and DBS lead performance. We explain the power spectrum of the data and how it is shaped by the filter response of Percept™ PC as well as the aliasing of the stimulation due to digitally sampling the data. We present Percept™ PC's ability to extract biomarkers that may be used to optimize stimulation therapy. We show how differences in lead type affects noise characteristics of the implanted leads from seven epilepsy patients enrolled in our clinical trial. Percept™ PC has sufficient signal-to-noise ratio, sampling capabilities, and stimulus artifact rejection for neural activity recording. Limitations in sampling rate, potential artifacts during stimulation, and shortening of battery life when monitoring neural activity at home were observed. Despite these limitations, Percept™ PC demonstrates potential as a useful tool for recording neural activity in order to optimize stimulation therapies to personalize treatment.

摘要

使用美敦力公司的Percept™ PC植入式脉冲发生器进行的深部脑刺激(DBS)已获得美国食品药品监督管理局(FDA)批准,用于治疗帕金森病(PD)、特发性震颤、肌张力障碍、强迫症和癫痫。Percept™ PC能够同时记录用于刺激的同一根电极导线的神经信号。许多Percept™ PC传感功能在设计时就考虑到了PD患者,但这些功能对于优化多种不同疾病进程的治疗可能也很有用。在启动我们正在进行的癫痫研究时,我们发现很难找到关于这些功能的详细描述,因此从多个来源收集了信息,以便将其作为一种工具来理解,特别是用于PD以外的患者。在这里,我们为有兴趣使用Percept™ PC功能的科学家和医生提供一个教程,并举例说明神经时间序列数据通常是如何表示和保存的。我们阐述了记录信号的特征,并讨论了Percept™ PC在数据预处理、信号滤波和DBS电极导线性能方面的硬件和软件功能。我们解释了数据的功率谱以及它是如何由Percept™ PC的滤波器响应以及由于对数据进行数字采样而导致的刺激混叠所塑造的。我们展示了Percept™ PC提取可能用于优化刺激治疗的生物标志物的能力。我们展示了电极导线类型的差异如何影响我们临床试验中七名癫痫患者植入电极导线的噪声特性。Percept™ PC具有足够的信噪比、采样能力和刺激伪迹抑制能力用于神经活动记录。观察到采样率的限制、刺激期间的潜在伪迹以及在家中监测神经活动时电池寿命的缩短。尽管存在这些限制,Percept™ PC仍显示出作为记录神经活动的有用工具的潜力,以便优化刺激治疗以实现个性化治疗。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdb7/11299490/ac74e4e5ff9f/nihms-2011101-f0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdb7/11299490/fb64ce3167f4/nihms-2011101-f0001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdb7/11299490/ac74e4e5ff9f/nihms-2011101-f0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdb7/11299490/fb64ce3167f4/nihms-2011101-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdb7/11299490/19ccde6b0f12/nihms-2011101-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdb7/11299490/a5b9ce4fe0a8/nihms-2011101-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdb7/11299490/800a6bb4f144/nihms-2011101-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdb7/11299490/b0c92df643cc/nihms-2011101-f0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdb7/11299490/ac74e4e5ff9f/nihms-2011101-f0007.jpg

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Epilepsia. 2023 Nov;64(11):3025-3035. doi: 10.1111/epi.17758. Epub 2023 Sep 11.
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Clin Neurophysiol. 2023 Feb;146:147-161. doi: 10.1016/j.clinph.2022.11.011. Epub 2022 Dec 2.
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Chronobiology of epilepsy and sudden unexpected death in epilepsy.
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