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|Title:||NeuroKit2: a Python toolbox for neurophysiological signal processing||Authors:||Makowski, Dominique
Lau, Zen Juen
Brammer, Jan C.
Chen, Annabel Shen-Hsing
|Keywords:||Science::Medicine||Issue Date:||2021||Source:||Makowski, D., Pham, T., Lau, Z. J., Brammer, J. C., Lespinasse, F., Pham, H., Schölzel, C. & Chen, A. S. (2021). NeuroKit2: a Python toolbox for neurophysiological signal processing. Behavior Research Methods, 53(4), 1689-1696. https://dx.doi.org/10.3758/s13428-020-01516-y||Journal:||Behavior Research Methods||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.||URI:||https://hdl.handle.net/10356/159711||ISSN:||1554-351X||DOI:||10.3758/s13428-020-01516-y||Rights:||© 2021 The Psychonomic Society, Inc. All rights reserved.||Fulltext Permission:||none||Fulltext Availability:||No Fulltext|
|Appears in Collections:||LKCMedicine Journal Articles|
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