TMS-EEG 实验仪器:ArTGen 和定制脑电图接口

IF 3 4区 计算机科学 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Giuseppe Varone, Wadii Boulila, Angelo Pascarella, Sara Gasparini, Umberto Aguglia
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引用次数: 0

摘要

在经颅磁刺激(TMS)和脑电图(EEG)实验中,实验室通常需要两名研究人员合作。本研究解决了单个研究人员在操作经颅磁刺激线圈时管理经颅磁刺激实验计时所面临的挑战。它引入了 Arduino 触发发生器 (ArTGen),使用脚踏开关踏板远程控制 TMS 实验的计时。此外,还设计了一块定制的印刷电路板(PCB),用于连接 eegoMylab 放大器和现成的脑电图帽。ArTGen 通过脚踏开关踏板实现了对 TMS 刺激器脉冲间隔 (IPI) 的精确计时,增强了研究人员对 TMS-EEG 实验的控制。印刷电路板接口为扩展 eegoMylab 放大器的功能提供了一种经济有效的工具。通过分析 TMS 诱发电位 (TEP)、全局平均场功率 (GMFP)、蝴蝶图和事件相关频谱电位 (ERSP),我们在定制的 TMS-EEG 设置中验证了 PCB 接口的集成性。印刷电路板可靠地保持了脑电图信号的完整性,确保了数据采集的准确性。对各组件进行彻底的通道一致性检查确认了数据的准确性。ArTGen 的便携性和脚踏开关功能简化了实验控制,有助于 TMS-EEG 研究和临床应用。此外,我们的印刷电路板还解决了 eegoMylab 放大器和 Waveguard EEG 帽之间的兼容性问题,使放大器能够连接到现成的 EEG 帽。ArTGen 可作为 TMS 刺激器的强大远程控制工具,而我们的 PCB 接口则为集成定制的 TMS-EEG 设置提供了解决方案。这项研究通过引入创新技术,不仅增强了实验灵活性,还简化了程序工作流程,从而弥补了现有 TMS-EEG 研究的不足。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Instrumentation for TMS-EEG Experiment: ArTGen and a Custom EEG Interface

Instrumentation for TMS-EEG Experiment: ArTGen and a Custom EEG Interface

In transcranial magnetic stimulation (TMS) and electroencephalography (EEG) experiments, two researchers typically collaborate in the lab. This study addresses the challenge a single researcher faces in managing the TMS experiment's timing while operating the TMS coil. It introduces the Arduino Trigger Generator (ArTGen) to remotely control the timing of TMS experiments using a footswitch pedal. Moreover, a bespoke printed circuit board (PCB) is designed to interface the eegoMylab amplifier with off-the-shelf EEG caps. The ArTGen facilitates accurate timing of the TMS stimulator's inter-pulse intervals (IPIs) through a footswitch pedal, enhancing researchers' control over TMS-EEG experiments. The PCB interface provides a cost-effective tool to extend the functionality of the eegoMylab amplifier. The integration of our PCB interface has been validated in a custom TMS-EEG setup by analyzing TMS-evoked potentials (TEPs), global mean field power (GMFP), butterfly plots, and event-related spectral potentials (ERSPs). The PCB reliably preserved EEG signal integrity, ensuring accurate data acquisition. Thorough channel-wise consistency checks across components confirmed data accuracy. ArTGen's portability and footswitch feature streamline experimental control, aiding TMS-EEG research and clinical applications. Moreover, our PCB resolves compatibility between the eegoMylab amplifier and the Waveguard EEG cap by extending the amplifier to connect to off-the-shelf EEG caps. The ArTGen serves as a robust remote control tool for TMS stimulators, while our PCB interface presents a solution for integrating a customized TMS-EEG setup. This study addresses the gap in existing TMS-EEG research by introducing innovative technological enhancements that not only augment experimental flexibility but also streamline procedural workflows.

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来源期刊
International Journal of Imaging Systems and Technology
International Journal of Imaging Systems and Technology 工程技术-成像科学与照相技术
CiteScore
6.90
自引率
6.10%
发文量
138
审稿时长
3 months
期刊介绍: The International Journal of Imaging Systems and Technology (IMA) is a forum for the exchange of ideas and results relevant to imaging systems, including imaging physics and informatics. The journal covers all imaging modalities in humans and animals. IMA accepts technically sound and scientifically rigorous research in the interdisciplinary field of imaging, including relevant algorithmic research and hardware and software development, and their applications relevant to medical research. The journal provides a platform to publish original research in structural and functional imaging. The journal is also open to imaging studies of the human body and on animals that describe novel diagnostic imaging and analyses methods. Technical, theoretical, and clinical research in both normal and clinical populations is encouraged. Submissions describing methods, software, databases, replication studies as well as negative results are also considered. The scope of the journal includes, but is not limited to, the following in the context of biomedical research: Imaging and neuro-imaging modalities: structural MRI, functional MRI, PET, SPECT, CT, ultrasound, EEG, MEG, NIRS etc.; Neuromodulation and brain stimulation techniques such as TMS and tDCS; Software and hardware for imaging, especially related to human and animal health; Image segmentation in normal and clinical populations; Pattern analysis and classification using machine learning techniques; Computational modeling and analysis; Brain connectivity and connectomics; Systems-level characterization of brain function; Neural networks and neurorobotics; Computer vision, based on human/animal physiology; Brain-computer interface (BCI) technology; Big data, databasing and data mining.
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