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NeuroKit2: A Python toolbox for neurophysiological signal processing

2021; Springer Science+Business Media; Volume: 53; Issue: 4 Linguagem: Inglês

10.3758/s13428-020-01516-y

1554-3528

Dominique Makowski, Tam Pham, Zen Juen Lau, Jan C. Brammer, François Lespinasse, Hung Pham, Christopher Schölzel, Shen‐Hsing Annabel Chen,

Heart Rate Variability and Autonomic Control

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.