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.

NeuroKit2 是用于神经生理学信号处理的开源、社区驱动和以用户为中心的 Python 包。它为各种身体信号（例如，ECG、PPG、EDA、EMG、RSP）提供了一整套处理程序。这些处理例程包括使用经过验证的管道在几行代码中启用数据处理的高级函数，我们在两个涵盖最典型场景的示例中进行了说明，例如与事件相关的范式和与间隔相关的分析。该软件包还包括用于特定处理步骤的工具，例如速率提取和过滤方法，可在高级便利性和微调控制之间进行权衡。其目标是提高神经生理学研究的透明度和可重复性，并促进探索和创新。