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neurokit2

Process and analyze multichannel biosignals to extract HRV, EEG, EDA, and respiration metrics.

6|Updated Dec 30, 2025
Search Tags:#multimodal#eda#biosignals#hrv#eeg#neurokit2#rsp
One-click install
npx skills add https://github.com/pur3v4d3r/pur3-pkb-codebase --skill neurokit2-pur3v4d3r
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: neurokit2
Source: https://github.com/pur3v4d3r/pur3-pkb-codebase/tree/main/.claude/skills/__scientific-skills/neurokit2
Command: npx skills add https://github.com/pur3v4d3r/pur3-pkb-codebase --skill neurokit2-pur3v4d3r

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

NeuroKit2 provides a unified Python toolkit to preprocess, analyze, and visualize a wide range of physiological signals (ECG, EEG, EDA, RSP, EMG, EOG), enabling researchers to extract reliable metrics (HRV, spectral power, microstates, SCRs, etc) from single or multi-modal recordings.

Core Features & Use Cases

  • End-to-end biosignal processing: from cleaning to metric extraction across multiple modalities.
  • Event-related and interval analyses: supports epoch creation, averaging, and cross-signal coupling (e.g., RSA).
  • Multimodal integration: synchronized analysis of ECG, EEG, EDA, RSP, EMG, and EOG with cross-signal metrics.
  • Reference-heavy documentation: extensive references and tutorials for neuroscience and psychophysiology research.

Use cases include psychophysiology experiments, sleep/stress assessments, HCI studies, clinical research, and educational demonstrations.

Quick Start

Load your multi-modal biosignal dataset and run the NeuroKit2 bio_process workflow to start synchronized preprocessing and feature extraction.

Frequently Asked Questions about neurokit2

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

FAQPage Schema
How do I process multichannel biosignals to extract HRV and EEG metrics?▼

Load your multi-modal dataset into the bio_process workflow to run synchronized preprocessing and extract HRV, EEG, EDA, and respiration metrics from multichannel biosignals.

What is event-related analysis in psychophysiology research?▼

Event-related analysis in psychophysiology creates signal epochs around stimuli to compute averaged responses and cross-signal coupling metrics like respiratory sinus arrhythmia and EEG microstates.

Does this biosignal processing toolkit integrate with MNE for EEG source localization?▼

Yes, the toolkit integrates with MNE for advanced EEG source localization alongside built-in microstate analysis and spectral power extraction within your research workflow.

Can I analyze EDA and respiration data synchronously with ECG and EMG?▼

Yes, multimodal integration supports synchronized analysis of EDA, respiration, ECG, and EMG to provide cross-signal metrics for psychophysiology and HCI experiments.

What is the best way to start preprocessing physiological signals for sleep studies?▼

The best way to start preprocessing physiological signals for sleep studies is to load multi-modal recordings and run the automated bio_process workflow for end-to-end cleaning and feature extraction.

Are there limitations when extracting skin conductance responses from noisy EDA recordings?▼

Extracting reliable skin conductance responses from noisy EDA recordings requires applying modular preprocessing and epoch creation steps prior to metric extraction to ensure signal quality.

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