neurokit2

Process and analyze physiological signals with neurokit2 for feature extraction.

Updated May 10, 2026

Search Tags:#analysis #multi-modal #eda #biosignals #hrv #eeg

Ready to run

npx skills add https://github.com/Imad-Oute/ResearchForge --skill neurokit2-imad-oute

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: neurokit2
Source: https://github.com/Imad-Oute/ResearchForge/tree/main/OpenSource-Projects/claude-scientific-skills/scientific-skills/neurokit2
Command: npx skills add https://github.com/Imad-Oute/ResearchForge --skill neurokit2-imad-oute

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires neurokit2, mne, pandas, numpy, scipy, and includes scripts (resource) and references (resource) components.

What problem does it solve?

It simplifies the complex process of processing and analyzing diverse biosignals, reducing technical barriers for researchers and clinicians.

Core Features & Use Cases

Multi-modal Signal Processing: Analyze ECG, EEG, EDA, PPG, EMG, EOG, and respiratory signals within a unified framework.
Advanced Analysis Tools: Automate time, frequency, and nonlinear feature extraction, including HRV, microstates, and entropy.
Use Case: A psychologist records ECG and EDA during an experiment; with this Skill, they can automatically compute HRV metrics and skin conductance responses to assess emotional arousal.

Quick Start

Use the neurokit2 skill to process your ECG and respiratory data for heart rate and breathing analysis.

Frequently Asked Questions about neurokit2

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

FAQPage Schema

How do I extract HRV and EEG microstates from raw biosignals?▼

You can extract HRV and EEG microstates from raw biosignals by using this Skill to automate time, frequency, and nonlinear feature extraction within a unified framework. It processes ECG and EEG data to compute detailed physiological metrics.

What is the best way to process multi-modal physiological signals like ECG and EDA together?▼

Processing multi-modal physiological signals like ECG and EDA is best handled by analyzing them within a unified framework. This Skill supports diverse biosignals including ECG, EEG, EDA, PPG, EMG, EOG, and respiratory data to extract comprehensive features.

Can I compute skin conductance responses to assess emotional arousal using Python?▼

Yes, you can compute skin conductance responses to assess emotional arousal by processing EDA recordings with this Skill. It automates the extraction of physiological features from electrodermal activity for psychological research.

Does this biosignal analysis approach work with MNE and pandas dependencies?▼

Yes, this biosignal analysis approach works directly with MNE and pandas, alongside neurokit2, numpy, and scipy. These dependencies combine to provide detailed feature extraction and visualizations from raw physiological recordings.

How do I analyze event-related responses and entropy in EEG data?▼

To analyze event-related responses and entropy in EEG data, this Skill applies advanced neurophysiological Python libraries to extract nonlinear features. It facilitates detailed processing of EEG recordings for neuroscience research.

Can I use this Skill to measure heart rate and breathing from ECG and respiratory data?▼

Yes, you can use this Skill to measure heart rate and breathing by processing your ECG and respiratory data. It streamlines physiological signal analysis to compute heart rate and breathing metrics for health research.