NeuroKit2 Biosignal Processing

About

NeuroKit2 provides a comprehensive suite of tools for the advanced analysis of physiological data, enabling researchers and developers to process multi-modal signals using standardized pipelines for cleaning, feature extraction, and statistical analysis. It supports a wide range of biosignals such as heart rate, brain activity, and muscle movement, offering specialized guidance for complexity analysis, heart rate variability (HRV), and event-related responses. This skill is ideal for psychophysiological research, clinical studies, or human-computer interaction experiments where high-level signal processing and multi-modal integration are required.

Key Features

• Comprehensive Heart Rate Variability (HRV) analysis across time, frequency, and nonlinear domains
• Multi-modal signal integration for synchronized physiological data processing
• Advanced complexity and entropy measures for nonlinear signal dynamics
• 16 GitHub stars
• End-to-end processing pipelines for ECG, EEG, EDA, and respiratory signals
• Event-related analysis and automated epoch creation for stimulus-locked responses

Use Cases

• Processing EEG data for frequency power analysis and microstate segmentation
• Conducting psychophysiological research using skin conductance and respiratory patterns
• Analyzing heart rate variability and cardiac health markers from ECG or PPG data