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NeuroKit

swMATH ID: 38164
Software Authors:
Description: NeuroKit: The 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.
Homepage: https://neurokit2.readthedocs.io/en/latest/
Source Code:  https://github.com/neuropsychology/NeuroKit/
Dependencies: Python
Related Software: Python; Systole; SciPy; Matplotlib; NumPy; pyHRV; HeartPy; BioSPPy; PhysioToolkit; PsychoPy; pandas; Numba; bokeh; PySiology; Kubios HRV; Scikit; Jupyter; Binder 2.0; cvxEDA; HRV
Cited in: 1 Document

Standard Articles

1 Publication describing the Software Year
NeuroKit2: A Python toolbox for neurophysiological signal processing Link
Makowski, Dominique; Pham, Tam; Lau, Zen J.; Brammer, Jan C.; Lespinasse, François; Pham, Hung; Schölzel, Christopher; Chen, S. H. Annabel
2021

Cited in 1 Serial

1 Physica D

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