neurokit2

Process and analyze physiological signals like ECG, EEG, and EDA with neurokit2.

1|Updated Jan 14, 2026
One-click install
npx skills add https://github.com/Sologa/codex-pipeline --skill neurokit2-sologa
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: neurokit2
Source: https://github.com/Sologa/codex-pipeline/tree/main/.codex/skills/neurokit2
Command: npx skills add https://github.com/Sologa/codex-pipeline --skill neurokit2-sologa

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides a comprehensive toolkit for processing and analyzing complex physiological signals, enabling deep insights into human health and behavior.

Core Features & Use Cases

  • Multi-Signal Processing: Analyze ECG, EEG, EDA, RSP, PPG, EMG, EOG signals individually or in combination.
  • Advanced Analysis: Perform detailed analysis including Heart Rate Variability (HRV), EEG microstates, complexity measures, and event-related responses.
  • Use Case: Analyze a multi-modal recording of ECG, respiration, and EDA during a stress-inducing task to understand the interplay of cardiovascular, respiratory, and autonomic responses.

Quick Start

Use the neurokit2 skill to process an ECG signal and analyze its heart rate variability.

Frequently Asked Questions about neurokit2

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I perform ECG analysis and heart rate variability calculation in Python?▼

To perform ECG analysis and heart rate variability (HRV) calculation in Python, you can use this toolkit to process electrocardiogram signals, extract heart beats, and compute detailed HRV metrics for psychophysiology research.

Can I process multi-modal physiological signals like EEG and EDA simultaneously?▼

Yes, you can process multi-modal physiological signals like EEG and EDA simultaneously. The toolkit supports analyzing ECG, EEG, EDA, RSP, PPG, EMG, and EOG signals individually or in combination to study autonomic and cardiovascular interplay.

What is the best way to analyze EEG microstates and event-related responses?▼

The best way to analyze EEG microstates and event-related responses is using a comprehensive biosignal processing library that provides built-in functions to extract and evaluate these specific neural patterns from raw electroencephalogram data.

Does this physiological signal processing toolkit support complexity measures for respiration data?▼

Yes, this physiological signal processing toolkit supports complexity measures for respiration data. It enables detailed analysis of RSP signals alongside other biosignals to compute complexity metrics for clinical and human-computer interaction studies.

Do I need the neurokit2 library installed to analyze biosignals for psychophysiology research?▼

Yes, you need the neurokit2 library installed to analyze biosignals for psychophysiology research. This Skill requires the neurokit2 library as its underlying engine for processing physiological signals and computing advanced metrics.