neurokit2

Topics in the source

• NeuroKit2
• Overview
• When to Use This Skill
• Core Capabilities
• 1. Cardiac Signal Processing (ECG/PPG)
• 2. Heart Rate Variability Analysis
• 3. Brain Signal Analysis (EEG)
• 4. Electrodermal Activity (EDA)

NeuroKit2 is a comprehensive Python toolkit for processing and analyzing physiological signals (biosignals). Use this skill to process cardiovascular, neural, autonomic, respiratory, and muscular signals for psychophysiology research, clinical applications, and human-computer interaction studies. Apply this skill when working with: Cardiac signals: ECG, PPG, heart rate variability (HRV), pulse analysis Brain signals: EEG frequency bands, microstates, complexity, source localization Autonomic signals: Electrodermal activity (EDA/GSR), skin conductance responses (SCR) Respiratory signals: Breathing rate, respiratory variability (RRV), volume per time Muscular signals: EMG amplitude, muscle activation detection Eye tracking: EOG, blink detection and analysis Multi-modal integration: Processing multiple physiological signals simultaneously Complexity analysis: Entropy measures, fractal dimensions, nonlinear dynamics Process electrocardiogram and photoplethysmography signals for cardiovascular analysis. See references/ecgcardiac.md for detailed workflows. Primary workflows: ECG processing pipeline: cleaning → R-peak detection → delineation → quality assessment HRV analysis across time,

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