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.

Makowski, D., Pham, T., Lau, Z.J., Brammer, J.C., Lespinasse, F., Pham, H., Scholzel, C., & Chen, S.H.A. (2021) NeuroKit2: A Python toolbox for neurophysiological signal processing. Behavior Research Methods, 1-8.
Dominique Makowski
Dominique Makowski

Trained as neuropsychologist and CBT psychotherapist, I am currently working as a lecturer at the University of Sussex, United Kingdom, where where we study the neurophysiological underpinnings of reality perception.

Annabel Chen
Annabel Chen
Professor of Psychology
Lab Director

Dr. SH Annabel Chen is a clinical neuropsychologist, and currently a Faculty member of Psychology at the School of Social Sciences.