Processes and analyzes physiological signals like ECG, EEG, and EDA using the NeuroKit2 Python library.
This skill integrates the NeuroKit2 toolkit into Claude, providing a specialized framework for comprehensive biosignal processing and physiological data analysis. It empowers researchers and developers to handle cardiac, neural, autonomic, and muscular signals with ease, facilitating complex tasks such as heart rate variability (HRV) analysis, EEG microstate segmentation, and electrodermal activity (EDA) decomposition. Whether used for psychophysiology research, clinical applications, or human-computer interaction studies, this skill provides the patterns and functions needed to extract meaningful insights from multi-modal physiological data.
Key Features
01Advanced nonlinear dynamics metrics including entropy, fractals, and Lyapunov exponents
02Comprehensive cardiac processing for ECG/PPG and multi-domain HRV analysis
03Autonomic assessment via skin conductance (EDA) and respiratory pattern (RSP) analysis
04Unified multi-modal integration for processing multiple biosignals simultaneously
05Neural signal analysis including EEG frequency bands, microstates, and complexity
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Use Cases
01Analyzing psychophysiological datasets for research in stress, emotion, or cognition
02Processing experimental event-related potentials and stimulus-locked physiological responses
03Developing health-monitoring applications that require robust heart rate and breathing analysis
