Process and analyze physiological signals like ECG, EEG, and EDA with neurokit2.
npx skills add https://github.com/Yezez9/Research-Agent --skill neurokit2-yezez9
Please help me install this Agent Skill. Skill: neurokit2 Source: https://github.com/Yezez9/Research-Agent/tree/main/scientific-skills/neurokit2 Command: npx skills add https://github.com/Yezez9/Research-Agent --skill neurokit2-yezez9
This Skill simplifies the complex task of analyzing physiological signals like ECG, EEG, and EDA, making advanced biosignal processing accessible for research and clinical applications.
Use the neurokit2 skill to process an ECG signal and compute its heart rate variability.
High-intent search queries and answers about installing and using this skill.
You compute heart rate variability (HRV) by processing ECG signals using the neurokit2 Python library. This toolkit provides unified functions to clean ECG data, detect R-peaks, and calculate advanced HRV metrics for physiological analysis.
Yes, you can analyze multiple biosignals like EEG and EDA simultaneously. The toolkit processes ECG, EEG, EDA, RSP, EMG, EOG, and PPG together to identify changes in autonomic nervous system response during tasks.
The best way to perform event-related analysis on physiological signals is using a comprehensive Python biosignal processing library. neurokit2 facilitates event-related analysis alongside complexity measures and EEG microstates.
Yes, neurokit2 supports EEG microstate analysis. It provides a comprehensive Python toolkit for processing and analyzing physiological signals, specifically including advanced features for EEG microstates and complexity measures.
Yes, you need to install the neurokit2 library before processing biosignals. The Skill requires this dependency to execute its signal processing and advanced physiological analysis workflows.
Using a unified Python toolkit for biosignal processing simplifies analyzing signals like ECG, EEG, and EDA. It makes advanced physiological analysis accessible for research by providing consistent processing functions across multiple biosignal domains.
jackspaceProcess physiological biosignals for integrated multi-modal analysis in Python.
shushuznClean and analyze physiological biosignals from raw time-series data.
Imad-OuteProcess and analyze physiological signals with neurokit2 for feature extraction.
hxk622Process and analyze physiological biosignals like ECG and EEG with neurokit2.
