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AI4Pain 2026 — Feature Extraction Pipeline
Physiological signal feature extraction for the AI4Pain 2026 Challenge.
Files
| File | Description |
|---|---|
feature_matrix.npz |
Extracted feature matrix (183 features, train + val splits) |
feature_pipeline.py |
Complete extraction pipeline script |
context_prompt.md |
Full context for continuing work in another session |
Quick Start
import numpy as np
data = np.load('feature_matrix.npz', allow_pickle=True)
X_train, y_train = data['X_train'], data['y_train'] # (864, 183), (864,)
X_val, y_val = data['X_val'], data['y_val'] # (612, 183), (612,)
# Labels: 0=NoPain, 1=ARM, 2=HAND
Features
61 base features × 3 normalization variants = 183 total features
- BVP (27): pulse rate, PRV, frequency-domain, amplitude, entropy, signal quality
- EDA (14): tonic/phasic decomposition via cvxEDA, SCR peaks, complexity
- RESP (8): respiratory rate, amplitude, Hjorth parameters
- SpO2 (4): mean, std, slope, range
- Cross-modal (8): BVP×EDA cross-correlation at multiple lags
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