neurokit2

Biosignal feature extraction for HRV, EDA, and other signals is handled through a unified, end-to-end pipeline that preprocesses ECG, EEG, and PPG data to generate physiological metrics. It supports multi-signal integration for comprehensive analysis.

An end-to-end biosignal pipeline covers preprocessing, feature extraction, and event-related analyses for ECG, EEG, EDA, RSP, EMG, EOG, and PPG data. It extracts HRV, EEG power, SCRs, respiration metrics, and EMG activation.

Yes, ECG and EEG data can be analyzed together for human-computer interaction studies. The pipeline supports multi-signal integration, allowing you to characterize autonomic and central nervous system activity simultaneously.

No prior preprocessing code is needed to extract skin conductance responses and respiration metrics. The pipeline provides automated preprocessing and feature extraction, handling signal cleaning and analysis automatically.

The best way to process EMG and EOG signals for neuroscience research is using a unified pipeline that provides automated extraction of EMG activation and EOG blink analysis alongside other physiological features.

Yes, NeuroKit2 supports event-related analysis for wearable study data. It enables rapid characterization of autonomic and central nervous system activity across psychophysiology, neuroscience, and clinical research contexts.