The paper proposes FEDT, an ensemble of decision trees for fall detection, integrated into a mobile-cloud system that filters ADLs on-device and achieves 1-3% higher sensitivity and specificity than compared methods.
L e v e r a g i n g t w o - s t a g e weighted ELM for multimodal wearables based fall detection[M]//Proceedings of ELM-2014 Volume 2
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A Mobile Cloud Collaboration Fall Detection System Based on Ensemble Learning
The paper proposes FEDT, an ensemble of decision trees for fall detection, integrated into a mobile-cloud system that filters ADLs on-device and achieves 1-3% higher sensitivity and specificity than compared methods.