Can I use this for event-related potential (ERP) studies?

Absolutely, the skill includes tools for event-marker detection, epoch creation, and grand averaging for stimulus-locked analysis.

What types of physiological signals can NeuroKit2 handle?

NeuroKit2 supports a wide range of signals including ECG (heart), EEG (brain), EDA (skin conductance), RSP (respiration), EMG (muscle), and EOG (eye movement).

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

Yes, it provides comprehensive HRV analysis across time, frequency, and nonlinear domains, including metrics like SDNN, RMSSD, and Poincaré plots.

How does NeuroKit2 handle different recording durations?

It automatically switches between Event-related analysis (for trials under 10 seconds) and Interval-related analysis (for longer resting state or continuous recordings).

NeuroKit2 Biosignal Processing

Name: NeuroKit2 Biosignal Processing
Author: Activer007

byActiver007

数据科学与机器学习

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

关于

NeuroKit2 is a comprehensive Python toolkit designed for the advanced processing and analysis of biosignals such as heart rate, brain activity, and skin conductance. This skill enables users to implement sophisticated workflows for psychophysiological research, clinical diagnostics, and human-computer interaction by providing automated pipelines for signal cleaning, peak detection, and multi-modal integration, allowing researchers to extract meaningful physiological markers with minimal code.

主要功能

Advanced cardiovascular analysis including ECG, PPG, and HRV metrics
Neural signal processing for EEG frequency bands and microstate patterns
Nonlinear complexity analysis including entropy and fractal dimensions
0 GitHub stars
Autonomic nervous system assessment via EDA and respiratory patterns
Unified multi-modal integration for simultaneous signal processing

使用场景

Analyzing heart rate variability (HRV) for clinical or wellness monitoring
Conducting psychophysiology research and event-related potential studies
Processing EEG data for brain-computer interface (BCI) development

关于

主要功能

Advanced cardiovascular analysis including ECG, PPG, and HRV metrics
Neural signal processing for EEG frequency bands and microstate patterns
Nonlinear complexity analysis including entropy and fractal dimensions
0 GitHub stars
Autonomic nervous system assessment via EDA and respiratory patterns
Unified multi-modal integration for simultaneous signal processing

使用场景

Analyzing heart rate variability (HRV) for clinical or wellness monitoring
Conducting psychophysiology research and event-related potential studies
Processing EEG data for brain-computer interface (BCI) development