Does it support EEG microstate analysis?

Yes, the skill includes specialized functions for EEG microstate segmentation, transition dynamics, and global field power analysis.

How does it handle stimulus-locked experimental data?

It features a robust event-related analysis mode that automatically creates epochs around stimulus triggers to calculate average physiological responses.

What types of physiological signals can NeuroKit2 process?

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

Can this skill perform Heart Rate Variability (HRV) analysis?

Yes, it provides a complete suite of HRV metrics across time-domain, frequency-domain, and nonlinear domains, including SDNN, RMSSD, and Poincare plots.

NeuroKit2 Biosignal Analysis

Name: NeuroKit2 Biosignal Analysis
Author: jimmc414

byjimmc414

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324

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Data Science & ML

Processes and analyzes complex physiological data including ECG, EEG, and EDA for scientific research and health tech applications.

NeuroKit2 is a comprehensive Python toolkit designed for the advanced processing and analysis of physiological signals, also known as biosignals. This skill enables Claude to handle multi-modal data streams such as heart rate variability (HRV), brain activity patterns, and respiratory dynamics, providing automated workflows for cleaning, peak detection, and feature extraction. It is an essential capability for researchers and developers working in psychophysiology, clinical diagnostics, and human-computer interaction who require precise, publication-grade physiological analysis.

Key Features

01Comprehensive cardiovascular processing for ECG, PPG, and deep HRV metrics

02324 GitHub stars

03Autonomic assessment through EDA/GSR decomposition and SCR detection

04Nonlinear dynamics analysis using various entropy and fractal dimension measures

05Multi-modal integration for synchronized processing of multiple physiological streams

06Neural signal analysis including EEG frequency bands, microstates, and complexity

Use Cases

01Analyzing heart rate variability and respiratory patterns for clinical health research

02Processing EEG and EOG data for cognitive neuroscience and brain-computer interface development

03Quantifying emotional arousal and stress levels via skin conductance and autonomic assessment

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add jimmc414/kosmos neurokit2

For use in Claude.ai and ChatGPT