Can I use NeuroKit2 for event-related analysis?

Absolutely. The skill includes functions for creating epochs around stimulus events, performing baseline correction, and calculating event-related averages.

What types of physiological signals can NeuroKit2 handle?

NeuroKit2 supports a wide array of signals including ECG (heart), EEG (brain), EDA/GSR (skin), RSP (breathing), PPG (pulse), EMG (muscle), and EOG (eye movement).

Is it possible to analyze signal complexity and entropy?

Yes, NeuroKit2 features an extensive complexity module for calculating Shannon entropy, fractal dimensions, Lyapunov exponents, and other nonlinear dynamics.

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

Yes, it provides comprehensive HRV metrics across time, frequency, and nonlinear domains, including specialized measures like Respiratory Sinus Arrhythmia (RSA).

NeuroKit2 Biosignal Analysis

Name: NeuroKit2 Biosignal Analysis
Author: x-cmd

byx-cmd

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データサイエンスとML

Processes and analyzes physiological signals including ECG, EEG, and EDA for psychophysiology research and clinical applications.

概要

NeuroKit2 is a comprehensive Python toolkit designed for the advanced processing and interpretation of physiological signals (biosignals). This skill empowers Claude to assist with complex tasks such as cleaning raw sensor data, detecting peaks, extracting features, and performing sophisticated analyses like Heart Rate Variability (HRV) or EEG microstate segmentation. It is an essential tool for researchers and developers working in psychophysiology, human-computer interaction, and health informatics who need to transform raw cardiovascular, neural, and autonomic data into actionable research insights.

主な機能

Neural signal analysis for EEG frequency bands, microstates, and complexity
Electrodermal Activity (EDA) decomposition into tonic and phasic components
Nonlinear dynamics analysis including entropy, fractal dimensions, and DFA
Comprehensive cardiac processing for ECG and PPG including HRV indices
8 GitHub stars
Unified multi-modal integration for processing multiple biosignals simultaneously

ユースケース

Automating heart rate variability (HRV) analysis for clinical research studies
Processing EEG data to identify cognitive states or neural microstates
Analyzing skin conductance responses (EDA) for emotional arousal studies

概要

主な機能

Neural signal analysis for EEG frequency bands, microstates, and complexity
Electrodermal Activity (EDA) decomposition into tonic and phasic components
Nonlinear dynamics analysis including entropy, fractal dimensions, and DFA
Comprehensive cardiac processing for ECG and PPG including HRV indices
8 GitHub stars
Unified multi-modal integration for processing multiple biosignals simultaneously

ユースケース

Automating heart rate variability (HRV) analysis for clinical research studies
Processing EEG data to identify cognitive states or neural microstates
Analyzing skin conductance responses (EDA) for emotional arousal studies