Analyze physiological signals from wearables
neurokit2skillsetup L3★27,559
K-Dense-AI/scientific-agent-skills ↗What it does
Process physiological signals (ECG, EEG, EDA, RSP, EMG, EOG)
Best for
Rapidly extracting heart rate, HRV, brainwave power, or autonomic indices from raw biosignals without implementing DSP.
Inputs
- · Raw physiological signal arrays
- · Sampling rate
Outputs
- · Cleaned signals
- · Detected events (R-peaks, SCR, blinks)
- · HRV/complexity measures
Requires
- · numpy
- · scipy
- · scikit-learn
- · mne (optional for EEG)
Preconditions
- · Python 3.7+
- · Sampling rate known
Failure modes
- · Noise exceeds cleaning algorithm robustness
- · Missing or misidentified physiological events
Trust signals
- · Comprehensive multi-signal suite
- · Published psychophysiology workflows