| Literature DB >> 33528817 |
Dominique Makowski1, Tam Pham2, Zen J Lau2, Jan C Brammer3, François Lespinasse4,5, Hung Pham6, Christopher Schölzel7, S H Annabel Chen2,8,9.
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.Entities:
Keywords: Biosignals; ECG; EDA; EMG; Neurophysiology; Python
Year: 2021 PMID： 33528817 DOI： 10.3758/s13428-020-01516-y
Source DB: PubMed Journal: Behav Res Methods ISSN： 1554-351X