Process physiological biosignals into cleaned metrics for ECG, EEG, EDA, and respiration.
npx skills add https://github.com/dralkh/seerai --skill neurokit2-dralkh
Please help me install this Agent Skill. Skill: neurokit2 Source: https://github.com/dralkh/seerai/tree/main/skills/neurokit2 Command: npx skills add https://github.com/dralkh/seerai --skill neurokit2-dralkh
NeuroKit2 removes the complexity of cleaning, segmenting, and analyzing physiological time-series so you can turn raw biosignals into interpretable research metrics quickly and consistently.
Analyze the attached physiological recording with NeuroKit2 by cleaning the signal, detecting events or peaks, and returning the key metrics for the signal type I specify.
High-intent search queries and answers about installing and using this skill.
You can analyze HRV and EDA by cleaning raw physiological signals, detecting peaks, and extracting interpretable metrics like heart rate variability and skin conductance responses. The process removes noise and segments data into event-related epochs for psychophysiology research.
EEG processing supports bad-channel detection, rereferencing, and microstate segmentation. Brain and microstate analysis transforms raw electroencephalography into cleaned signal channels and segmented neural states for cognitive research monitoring.
Integrating multiple biosignals for stress studies involves combining ECG, EDA, respiration, and EEG workflows. Cross-signal integration yields unified psychophysiology metrics to compare arousal, attention, and emotion responses across experimental conditions.
Python is required for physiological signal preprocessing, peak detection, and spectral analysis. The workflow relies on Python-based processing to clean raw time-series data and compute nonlinear metrics for multi-modal physiological data analysis.
Respiratory sinus arrhythmia is extracted using cross-signal integration of ECG and respiration workflows. Combining these cleaned physiological signals allows you to compute cross-signal measures and quantify autonomic breathing and cardiac interactions.
fuzzy-dynamicsAutomate biosignal preprocessing and analysis to extract physiological metrics from ECG, EEG, EDA, RSP, EMG, and EOG data.
pur3v4d3rProcess and analyze multichannel biosignals to extract HRV, EEG, EDA, and respiration metrics.
silversteinClean physiological signals and compute domain-specific metrics from ECG, EEG, EDA, respiratory, PPG, EMG, and EOG time series.
jasrajtulsiProcess raw physiological signals into cleaned biosignal features for ECG, EEG, EDA, RSP, PPG, EMG, and EOG.
