Can I use NeuroKit2 for event-related experimental designs?

Absolutely. NeuroKit2 features specialized functions for event-related analysis, allowing you to create epochs around stimulus markers and analyze physiological responses to specific events.

What types of physiological signals can NeuroKit2 process?

NeuroKit2 supports a wide range of biosignals including ECG (heart), EEG (brain), EDA/GSR (skin conductance), RSP (respiration), PPG (blood volume pulse), EMG (muscle), and EOG (eye movement).

Does this skill support Heart Rate Variability (HRV) analysis?

Yes, it provides comprehensive HRV analysis covering time-domain, frequency-domain, and nonlinear metrics, including RSA and Poincaré plots.

Is NeuroKit2 suitable for nonlinear signal analysis?

Yes, it includes advanced tools for complexity analysis, such as various entropy measures, fractal dimensions, and Lyapunov exponents to characterize nonlinear dynamics in biological signals.

NeuroKit2 Biosignal Processing

Name: NeuroKit2 Biosignal Processing
Author: Zehong-Wang

byZehong-Wang

0•

数据科学与机器学习

Processes and analyzes complex physiological signals including ECG, EEG, EDA, and respiratory patterns for research and clinical applications.

NeuroKit2 is a specialized Python toolkit designed for the comprehensive analysis of biosignals, providing researchers and developers with robust pipelines for cardiovascular, neural, and autonomic data. It automates complex workflows such as heart rate variability (HRV) analysis, EEG frequency mapping, and electrodermal activity decomposition, making it an essential tool for psychophysiology research, human-computer interaction studies, and clinical data processing within the Claude Code environment.

主要功能

01Support for both event-related (stimulus-locked) and interval-related analysis modes

02Multi-modal biosignal processing for ECG, EEG, EDA, PPG, EMG, and EOG

030 GitHub stars

04Automated signal cleaning, peak detection, and quality assessment pipelines

05Comprehensive complexity measures including entropy, fractal dimensions, and nonlinear dynamics

06Advanced Heart Rate Variability (HRV) analysis across time, frequency, and nonlinear domains

使用场景

01Processing brain activity and microstates for neuroscientific research and BCI applications

02Monitoring autonomic nervous system responses in psychological experiments and HCI studies

03Analyzing cardiovascular health and stress through detailed HRV metrics

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add zehong-wang/kosmos neurokit2

For use in Claude.ai and ChatGPT

Download Skill