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NeuroKit2:一个用于神经生理信号处理的 Python 工具包。

NeuroKit2: A Python toolbox for neurophysiological signal processing.

机构信息

School of Social Sciences, Nanyang Technological University, HSS 04-19, 48 Nanyang Avenue, Singapore, Singapore.

Behavioural Science Institute, Radboud University, Nijmegen, Netherlands.

出版信息

Behav Res Methods. 2021 Aug;53(4):1689-1696. doi: 10.3758/s13428-020-01516-y. Epub 2021 Feb 2.

Abstract

NeuroKit2 is an open-source, community-driven, and user-centered Python package for neurophysiological signal processing. It provides a comprehensive suite of processing routines for a variety of bodily signals (e.g., ECG, PPG, EDA, EMG, RSP). These processing routines include high-level functions that enable data processing in a few lines of code using validated pipelines, which we illustrate in two examples covering the most typical scenarios, such as an event-related paradigm and an interval-related analysis. The package also includes tools for specific processing steps such as rate extraction and filtering methods, offering a trade-off between high-level convenience and fine-tuned control. Its goal is to improve transparency and reproducibility in neurophysiological research, as well as foster exploration and innovation. Its design philosophy is centred on user-experience and accessibility to both novice and advanced users.

摘要

NeuroKit2 是一个开源的、社区驱动的、以用户为中心的 Python 包,用于神经生理信号处理。它为各种身体信号(例如 ECG、PPG、EDA、EMG、RSP)提供了全面的处理例程。这些处理例程包括高级功能,可使用经过验证的管道在几行代码内处理数据,我们在两个示例中说明了这一点,涵盖了最典型的场景,例如事件相关范式和区间相关分析。该包还包括特定处理步骤的工具,例如速率提取和滤波方法,在高级便利性和精细控制之间提供了权衡。它的目标是提高神经生理研究的透明度和可重复性,并促进探索和创新。它的设计理念以用户体验为中心,兼顾新手和高级用户的可访问性。

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