NeuroKit
An open-source Python package for physiological signal processing.
NeuroKit2 is an open-source Python package designed for the processing and analysis of physiological signals. It is widely used in neuroscience, psychophysiology, and biomedical engineering for its comprehensive suite of tools that facilitate the extraction of meaningful information from raw physiological data.
Overview[edit | edit source]
NeuroKit2 provides a user-friendly interface for researchers and practitioners to analyze a variety of physiological signals, including ECG, EEG, EMG, and GSR. The package is designed to be accessible to users with varying levels of programming expertise, offering both high-level functions for quick analysis and low-level functions for more detailed investigations.
Features[edit | edit source]
NeuroKit2 includes a wide range of features that support the analysis of physiological data:
- Signal Preprocessing: Functions for filtering, detrending, and normalizing signals to prepare them for analysis.
- Feature Extraction: Tools for extracting features such as heart rate, heart rate variability, and respiratory rate from physiological signals.
- Visualization: Capabilities for plotting signals and their features, aiding in the interpretation of data.
- Event Detection: Algorithms for detecting events such as R-peaks in ECG signals or peaks in GSR data.
- Statistical Analysis: Functions for performing statistical tests and analyses on physiological data.
Applications[edit | edit source]
NeuroKit2 is used in a variety of research and clinical settings. It is particularly valuable in studies of autonomic nervous system function, stress and emotion research, and sleep studies. Its ability to handle multiple types of physiological data makes it a versatile tool for interdisciplinary research.
Development and Community[edit | edit source]
NeuroKit2 is developed by a community of researchers and developers who contribute to its ongoing improvement and expansion. The project is hosted on GitHub, where users can access the source code, report issues, and contribute to the development of new features.
Related pages[edit | edit source]
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Contributors: Prab R. Tumpati, MD
