用于多电极经颅电刺激的个性化3d打印头套。

IF 1.2 4区 综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES
Benjamin M Hampstead, Annalise Rahman-Filipiak, Kayla Rinna, Stephen Schlaefflin, Kenneth Petscavage, Alexander R Guillen, Kamran Nazim, Jeffrey Moreno, Abhishek Datta, Marom Bikson, Alexandru D Iordan
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引用次数: 0

摘要

我们介绍了一种新颖的专利方法,用于创建个性化的3d打印头戴设备,即使在家中也可以实现多电极经颅电刺激。结构磁共振成像(MRI)扫描用于优化针对关键大脑区域/网络的蒙太奇,然后上传到安全服务器上设计定制的头戴设备,最终进行3d打印。头套允许快速多电极放置(
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Personalized 3D-printed Headgear for Multi-electrode Transcranial Electrical Stimulation.

We present an overview of a novel, patented, approach for creating personalized 3D-printed headgear that enables multi-electrode transcranial electrical stimulation, even in the home. A structural magnetic resonance imaging (MRI) scan is used to optimize a montage that targets key brain areas/networks and is then uploaded to a secure server to design customized headgear that is ultimately 3D-printed. The headgear allows rapid multi-electrode placement (<1 min per electrode) with comparable accuracy as manual 10-10 measurements. We performed over 1,400 sessions across 63 older adults with neurological injury or disease. We describe an efficient training program for study partners (e.g., spouses) that enabled a 100% success rate and over 900 remotely administered sessions. Study partners and participants reported high levels of confidence and satisfaction with the experience. Because the electrode locations are based on personalized computational modeling, the headgear is ideal for techniques requiring precision (e.g., temporal interference stimulation, transcranial focused ultrasound, transcranial magnetic stimulation).

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来源期刊
Jove-Journal of Visualized Experiments
Jove-Journal of Visualized Experiments MULTIDISCIPLINARY SCIENCES-
CiteScore
2.10
自引率
0.00%
发文量
992
期刊介绍: JoVE, the Journal of Visualized Experiments, is the world''s first peer reviewed scientific video journal. Established in 2006, JoVE is devoted to publishing scientific research in a visual format to help researchers overcome two of the biggest challenges facing the scientific research community today; poor reproducibility and the time and labor intensive nature of learning new experimental techniques.
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