A unified inference-time augmentation framework using 13 methods with Bayesian optimization improves AUROC up to 8.5% and AUPRC up to 10.6% for PPG AF detection on five datasets with over 400 patients.
COA-HAR: Exploring contrastive online test-time adaptation for wearable sensor-based human activity recognition using sensor data augmentation,
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A Comprehensive Inference-Time Augmentation Framework in Physiological Signals: Application to PPG-Based AF Detection
A unified inference-time augmentation framework using 13 methods with Bayesian optimization improves AUROC up to 8.5% and AUPRC up to 10.6% for PPG AF detection on five datasets with over 400 patients.