NeuroKit2: A Python toolbox for neurophysiological signal processing


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.

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We would like to thank Prof. C. F. Xavier for inspiration, all the current and future contributors (, and the users for their support. Additionally, François Lespinasse would like to thank the Courtois Foundation for its support through the Courtois-NeuroMod project (

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Correspondence to Dominique Makowski.

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Makowski, D., Pham, T., Lau, Z.J. et al. NeuroKit2: A Python toolbox for neurophysiological signal processing. Behav Res (2021).

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  • Neurophysiology
  • Biosignals
  • Python
  • ECG
  • EDA
  • EMG