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.

Behavior Research Methods, 53, 1689–1696
Dominique Makowski
Dominique Makowski
Presidential Research Fellow

Trained as neuropsychologist and CBT psychotherapist, I am currently working as a researcher at the Clinical Brain Lab in Singapore, on the neuroscience of reality perception.

Tam Pham
Tam Pham
Research Assistant (2019-22)
Current: Student (master of clinical psychology)

I’m interested in suicide and interoception and I aspire to become a clinical psychologist.