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neurokit2

Process and analyze physiological biosignals like ECG and EEG with neurokit2.

8|Updated Jan 13, 2026
Search Tags:#neuroscience#hrv#ecg#eeg#physiology#biosignal analysis
One-click install
npx skills add https://github.com/hxk622/TokenDance --skill neurokit2-hxk622
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: neurokit2
Source: https://github.com/hxk622/TokenDance/tree/main/backend/app/skills/builtin/scientific/clinical/neurokit2
Command: npx skills add https://github.com/hxk622/TokenDance --skill neurokit2-hxk622

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires neurokit2, and includes references (resource) components.

What problem does it solve?

This Skill simplifies the complex process of analyzing physiological biosignals, making advanced psychophysiology and clinical research accessible.

Core Features & Use Cases

  • Comprehensive Signal Processing: Analyze ECG, EEG, EDA, EMG, EOG, and PPG signals with a unified toolkit.
  • Advanced Analytics: Perform HRV, complexity, microstate, and event-related analyses.
  • Use Case: Analyze a multi-day ECG recording to assess heart rate variability and identify potential cardiac irregularities, providing detailed reports on autonomic nervous system function.

Quick Start

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

Frequently Asked Questions about neurokit2

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

FAQPage Schema
How do I compute heart rate variability metrics from an ECG recording?▼

This toolkit processes ECG signals to compute heart rate variability (HRV) metrics by cleaning the raw biosignal, detecting R-peaks, and extracting time-domain, frequency-domain, and non-linear HRV features to assess autonomic nervous system function.

Can I analyze EEG and EDA biosignals using the same Python toolkit?▼

Yes, you can analyze EEG and EDA biosignals using this unified Python toolkit. It supports processing workflows for multiple physiological signals, including EEG, EDA, EMG, EOG, and PPG, for comprehensive psychophysiology research.

What is the best way to perform EEG microstate analysis on raw signal data?▼

The best way to perform EEG microstate analysis is using a comprehensive biosignal toolkit like neurokit2, which facilitates advanced microstate segmentation and event-related response analysis directly on raw physiological data to uncover neural dynamics.

Does neurokit2 support complexity measures for physiological signal analysis?▼

Yes, neurokit2 supports complexity measures for physiological signal analysis. The toolkit includes advanced analytics functions to compute complexity metrics for various biosignals, enabling detailed assessment of signal dynamics and autonomic regulation.

Do I need to install the neurokit2 library to run ECG and EMG processing workflows?▼

Yes, you need to install the neurokit2 Python library to run ECG and EMG processing workflows. The Skill requires this dependency to execute its internal signal processing, cleaning, and advanced physiological analysis routines.

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