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neurokit2

Process and analyze physiological signals like ECG and EEG with NeuroKit2.

Updated Jan 10, 2026
Search Tags:#neuroscience#HRV#biosignal processing#physiology#ECG analysis#EEG analysis#microstates
One-click install
npx skills add https://github.com/robinbarvaag/poynt --skill neurokit2-robinbarvaag
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: neurokit2
Source: https://github.com/robinbarvaag/poynt/tree/main/.github/skills/neurokit2
Command: npx skills add https://github.com/robinbarvaag/poynt --skill neurokit2-robinbarvaag

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill simplifies the complex task of processing and analyzing physiological signals, making advanced biosignal analysis accessible for research and applications.

Core Features & Use Cases

  • Comprehensive Signal Processing: Analyze ECG, EEG, EDA, RSP, PPG, EMG, EOG signals.
  • Advanced Analytics: Perform HRV, complexity, microstate, and source localization analyses.
  • Use Case: Researchers can use this Skill to automatically process multi-modal physiological data from an experiment, extract key metrics like heart rate variability and brain activity patterns, and generate reports for publication.

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 analyze heart rate variability from ECG signals?▼

To analyze heart rate variability from ECG signals, you process the raw ECG data to extract key HRV metrics. This simplifies complex biosignal processing for deep physiological insights.

What biosignal types are supported for physiological data processing?▼

Supported biosignal types for physiological data processing include ECG, EEG, EDA, RSP, PPG, EMG, and EOG. This range allows multi-modal data analysis from a single experiment.

Can I perform EEG microstate analysis and source localization together?▼

You can perform EEG microstate analysis and source localization together. The toolkit facilitates these advanced neurophysiological workflows by integrating directly with MNE-Python.

Do I need MNE-Python to process neurophysiological data?▼

You do not strictly need MNE-Python for basic signal processing, but it is integrated for advanced neurophysiological workflows like source localization. It extends capabilities for complex EEG analysis.

What is the best way to extract metrics from multi-modal physiological data?▼

The best way to extract metrics from multi-modal physiological data is using a comprehensive biosignal processing toolkit. It automatically processes multi-modal signals to extract complexity measures and brain activity patterns.

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