neurokit2listed

# NeuroKit2 ## Overview 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. ## When to Use This Skill 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 ## Core Capabilities ### 1. Cardiac Signal Processing (ECG/PPG) Process electrocardiogram and photoplethysmography signals for cardiovascular analysis. See `references/ecg_cardiac.md` for detailed workflows. **Primary workflows:** - ECG processing pipeline: cleaning → R-peak detection → delineation → quality assessment - HRV analysis across time, frequency, and nonlinear domains - PPG pulse analysis and quality assessment - ECG-derived respiration extraction **Ke